diff --git a/configuration.ipynb b/configuration.ipynb
index b136e4cac..325c757e7 100644
--- a/configuration.ipynb
+++ b/configuration.ipynb
@@ -103,7 +103,7 @@
       "source": [
         "import azureml.core\n",
         "\n",
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
diff --git a/contrib/RAPIDS/azure-ml-with-nvidia-rapids.ipynb b/contrib/RAPIDS/azure-ml-with-nvidia-rapids.ipynb
index 3d8007cc4..5d45bbf47 100644
--- a/contrib/RAPIDS/azure-ml-with-nvidia-rapids.ipynb
+++ b/contrib/RAPIDS/azure-ml-with-nvidia-rapids.ipynb
@@ -188,13 +188,6 @@
         "### Script to process data and train model"
       ]
     },
-    {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "The _process_data.py_ script used in the step below is a slightly modified implementation of [RAPIDS Mortgage E2E example](https://github.com/rapidsai/notebooks-contrib/blob/master/intermediate_notebooks/E2E/mortgage/mortgage_e2e.ipynb)."
-      ]
-    },
     {
       "cell_type": "code",
       "execution_count": null,
@@ -373,7 +366,7 @@
         "run_config.target = gpu_cluster_name\n",
         "run_config.environment.docker.enabled = True\n",
         "run_config.environment.docker.gpu_support = True\n",
-        "run_config.environment.docker.base_image = \"mcr.microsoft.com/azureml/base-gpu:intelmpi2018.3-cuda10.0-cudnn7-ubuntu16.04\"\n",
+        "run_config.environment.docker.base_image = \"mcr.microsoft.com/azureml/openmpi4.1.0-cuda11.1-cudnn8-ubuntu20.04\"\n",
         "run_config.environment.spark.precache_packages = False\n",
         "run_config.data_references={'data':data_ref.to_config()}"
       ]
diff --git a/contrib/fairness/fairlearn-azureml-mitigation.ipynb b/contrib/fairness/fairlearn-azureml-mitigation.ipynb
index 89a95dc48..68040ed55 100644
--- a/contrib/fairness/fairlearn-azureml-mitigation.ipynb
+++ b/contrib/fairness/fairlearn-azureml-mitigation.ipynb
@@ -49,7 +49,7 @@
         "* `fairlearn>=0.6.2` (pre-v0.5.0 will work with minor modifications)\n",
         "* `joblib`\n",
         "* `liac-arff`\n",
-        "* `raiwidgets~=0.7.0`\n",
+        "* `raiwidgets`\n",
         "\n",
         "Fairlearn relies on features introduced in v0.22.1 of `scikit-learn`. If you have an older version already installed, please uncomment and run the following cell:"
       ]
diff --git a/contrib/fairness/fairlearn-azureml-mitigation.yml b/contrib/fairness/fairlearn-azureml-mitigation.yml
index 05e133254..5abbad2f4 100644
--- a/contrib/fairness/fairlearn-azureml-mitigation.yml
+++ b/contrib/fairness/fairlearn-azureml-mitigation.yml
@@ -6,4 +6,4 @@ dependencies:
   - fairlearn>=0.6.2
   - joblib
   - liac-arff
-  - raiwidgets~=0.16.0
+  - raiwidgets~=0.17.0
diff --git a/contrib/fairness/upload-fairness-dashboard.ipynb b/contrib/fairness/upload-fairness-dashboard.ipynb
index 2a3c13694..35623f152 100644
--- a/contrib/fairness/upload-fairness-dashboard.ipynb
+++ b/contrib/fairness/upload-fairness-dashboard.ipynb
@@ -51,7 +51,7 @@
         "* `fairlearn>=0.6.2` (also works for pre-v0.5.0 with slight modifications)\n",
         "* `joblib`\n",
         "* `liac-arff`\n",
-        "* `raiwidgets~=0.7.0`\n",
+        "* `raiwidgets`\n",
         "\n",
         "Fairlearn relies on features introduced in v0.22.1 of `scikit-learn`. If you have an older version already installed, please uncomment and run the following cell:"
       ]
diff --git a/contrib/fairness/upload-fairness-dashboard.yml b/contrib/fairness/upload-fairness-dashboard.yml
index 6867c1f93..3fa476b8c 100644
--- a/contrib/fairness/upload-fairness-dashboard.yml
+++ b/contrib/fairness/upload-fairness-dashboard.yml
@@ -6,4 +6,4 @@ dependencies:
   - fairlearn>=0.6.2
   - joblib
   - liac-arff
-  - raiwidgets~=0.16.0
+  - raiwidgets~=0.17.0
diff --git a/how-to-use-azureml/automated-machine-learning/automl_env.yml b/how-to-use-azureml/automated-machine-learning/automl_env.yml
index 7c4727488..cccd9fd7b 100644
--- a/how-to-use-azureml/automated-machine-learning/automl_env.yml
+++ b/how-to-use-azureml/automated-machine-learning/automl_env.yml
@@ -1,29 +1,33 @@
 name: azure_automl
+channels:
+  - conda-forge
+  - pytorch
+  - main
 dependencies:
   # The python interpreter version.
-  # Currently Azure ML only supports 3.5.2 and later.
-- pip==21.1.2
-- python>=3.5.2,<3.8
-- boto3==1.15.18
-- matplotlib==2.1.0
+  # Currently Azure ML only supports 3.6.0 and later.
+- pip==20.2.4
+- python>=3.6,<3.8
+- boto3==1.20.19
+- botocore<=1.23.19
+- matplotlib==3.3.4
 - numpy==1.18.5
-- cython
-- urllib3<1.24
+- cython==0.29.14
+- urllib3==1.26.7
 - scipy>=1.4.1,<=1.5.2
 - scikit-learn==0.22.1
-- pandas==0.25.1
-- py-xgboost<=0.90
-- conda-forge::fbprophet==0.5
-- holidays==0.9.11
+- py-xgboost<=1.3.3
+- holidays==0.10.3
+- conda-forge::fbprophet==0.7.1
 - pytorch::pytorch=1.4.0
 - cudatoolkit=10.1.243
-- tornado==6.1.0
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
-  - azureml-widgets~=1.38.0
+  - azureml-widgets~=1.39.0
   - pytorch-transformers==1.0.0
   - spacy==2.1.8
+  - pystan==2.19.1.1
   - https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz
-  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.38.0/validated_win32_requirements.txt [--no-deps]
+  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.39.0/validated_win32_requirements.txt [--no-deps]
   - arch==4.14
diff --git a/how-to-use-azureml/automated-machine-learning/automl_env_linux.yml b/how-to-use-azureml/automated-machine-learning/automl_env_linux.yml
index 57cb93533..2727261dd 100644
--- a/how-to-use-azureml/automated-machine-learning/automl_env_linux.yml
+++ b/how-to-use-azureml/automated-machine-learning/automl_env_linux.yml
@@ -1,29 +1,33 @@
 name: azure_automl
+channels:
+  - conda-forge
+  - pytorch
+  - main
 dependencies:
   # The python interpreter version.
-  # Currently Azure ML only supports 3.5.2 and later.
-- pip==21.1.2
-- python>=3.5.2,<3.8
-- boto3==1.15.18
-- matplotlib==2.1.0
+  # Currently Azure ML only supports 3.6.0 and later.
+- pip==20.2.4
+- python>=3.6,<3.8
+- boto3==1.20.19
+- botocore<=1.23.19
+- matplotlib==3.3.4
 - numpy==1.18.5
-- cython
-- urllib3<1.24
+- cython==0.29.14
+- urllib3==1.26.7
 - scipy>=1.4.1,<=1.5.2
 - scikit-learn==0.22.1
-- pandas==0.25.1
-- py-xgboost<=0.90
-- conda-forge::fbprophet==0.5
-- holidays==0.9.11
+- py-xgboost<=1.3.3
+- holidays==0.10.3
+- conda-forge::fbprophet==0.7.1
 - pytorch::pytorch=1.4.0
 - cudatoolkit=10.1.243
-- tornado==6.1.0
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
-  - azureml-widgets~=1.38.0
+  - azureml-widgets~=1.39.0
   - pytorch-transformers==1.0.0
   - spacy==2.1.8
+  - pystan==2.19.1.1
   - https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz
-  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.38.0/validated_linux_requirements.txt [--no-deps]
+  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.39.0/validated_linux_requirements.txt [--no-deps]
   - arch==4.14
diff --git a/how-to-use-azureml/automated-machine-learning/automl_env_mac.yml b/how-to-use-azureml/automated-machine-learning/automl_env_mac.yml
index a64b04ae6..9e6651e08 100644
--- a/how-to-use-azureml/automated-machine-learning/automl_env_mac.yml
+++ b/how-to-use-azureml/automated-machine-learning/automl_env_mac.yml
@@ -1,30 +1,34 @@
 name: azure_automl
+channels:
+  - conda-forge
+  - pytorch
+  - main
 dependencies:
   # The python interpreter version.
-  # Currently Azure ML only supports 3.5.2 and later.
-- pip==21.1.2
+  # Currently Azure ML only supports 3.6.0 and later.
+- pip==20.2.4
 - nomkl
-- python>=3.5.2,<3.8
-- boto3==1.15.18
-- matplotlib==2.1.0
+- python>=3.6,<3.8
+- boto3==1.20.19
+- botocore<=1.23.19
+- matplotlib==3.3.4
 - numpy==1.18.5
-- cython
-- urllib3<1.24
+- cython==0.29.14
+- urllib3==1.26.7
 - scipy>=1.4.1,<=1.5.2
 - scikit-learn==0.22.1
-- pandas==0.25.1
-- py-xgboost<=0.90
-- conda-forge::fbprophet==0.5
-- holidays==0.9.11
+- py-xgboost<=1.3.3
+- holidays==0.10.3
+- conda-forge::fbprophet==0.7.1
 - pytorch::pytorch=1.4.0
 - cudatoolkit=9.0
-- tornado==6.1.0
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
-  - azureml-widgets~=1.38.0
+  - azureml-widgets~=1.39.0
   - pytorch-transformers==1.0.0
   - spacy==2.1.8
+  - pystan==2.19.1.1
   - https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz
-  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.38.0/validated_darwin_requirements.txt [--no-deps]
+  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.39.0/validated_darwin_requirements.txt [--no-deps]
   - arch==4.14
diff --git a/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb b/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb
index a7dd83291..a39af35a4 100644
--- a/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb
@@ -105,7 +105,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
@@ -154,7 +154,7 @@
         "output['Resource Group'] = ws.resource_group\n",
         "output['Location'] = ws.location\n",
         "output['Experiment Name'] = experiment.name\n",
-        "pd.set_option('display.max_colwidth', -1)\n",
+        "pd.set_option('display.max_colwidth', None)\n",
         "outputDf = pd.DataFrame(data = output, index = [''])\n",
         "outputDf.T"
       ]
diff --git a/how-to-use-azureml/automated-machine-learning/classification-credit-card-fraud/auto-ml-classification-credit-card-fraud.ipynb b/how-to-use-azureml/automated-machine-learning/classification-credit-card-fraud/auto-ml-classification-credit-card-fraud.ipynb
index 5ef43e3bd..2337d7588 100644
--- a/how-to-use-azureml/automated-machine-learning/classification-credit-card-fraud/auto-ml-classification-credit-card-fraud.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/classification-credit-card-fraud/auto-ml-classification-credit-card-fraud.ipynb
@@ -93,7 +93,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
@@ -116,7 +116,7 @@
         "output['Resource Group'] = ws.resource_group\n",
         "output['Location'] = ws.location\n",
         "output['Experiment Name'] = experiment.name\n",
-        "pd.set_option('display.max_colwidth', -1)\n",
+        "pd.set_option('display.max_colwidth', None)\n",
         "outputDf = pd.DataFrame(data = output, index = [''])\n",
         "outputDf.T"
       ]
diff --git a/how-to-use-azureml/automated-machine-learning/classification-text-dnn/auto-ml-classification-text-dnn.ipynb b/how-to-use-azureml/automated-machine-learning/classification-text-dnn/auto-ml-classification-text-dnn.ipynb
index ec98657b4..ea69554e9 100644
--- a/how-to-use-azureml/automated-machine-learning/classification-text-dnn/auto-ml-classification-text-dnn.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/classification-text-dnn/auto-ml-classification-text-dnn.ipynb
@@ -97,7 +97,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
@@ -127,7 +127,7 @@
         "output['Resource Group'] = ws.resource_group\n",
         "output['Location'] = ws.location\n",
         "output['Experiment Name'] = experiment.name\n",
-        "pd.set_option('display.max_colwidth', -1)\n",
+        "pd.set_option('display.max_colwidth', None)\n",
         "outputDf = pd.DataFrame(data = output, index = [''])\n",
         "outputDf.T"
       ]
diff --git a/how-to-use-azureml/automated-machine-learning/continuous-retraining/auto-ml-continuous-retraining.ipynb b/how-to-use-azureml/automated-machine-learning/continuous-retraining/auto-ml-continuous-retraining.ipynb
index 497f8b75a..24cd27e10 100644
--- a/how-to-use-azureml/automated-machine-learning/continuous-retraining/auto-ml-continuous-retraining.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/continuous-retraining/auto-ml-continuous-retraining.ipynb
@@ -81,7 +81,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
@@ -127,7 +127,7 @@
         "output['Resource Group'] = ws.resource_group\n",
         "output['Location'] = ws.location\n",
         "output['Run History Name'] = experiment_name\n",
-        "pd.set_option('display.max_colwidth', -1)\n",
+        "pd.set_option('display.max_colwidth', None)\n",
         "outputDf = pd.DataFrame(data = output, index = [''])\n",
         "outputDf.T"
       ]
diff --git a/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env.yml b/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env.yml
index 5873e588f..bfdffe277 100644
--- a/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env.yml
+++ b/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env.yml
@@ -1,11 +1,11 @@
 name: azure_automl_experimental
 dependencies:
   # The python interpreter version.
-  # Currently Azure ML only supports 3.5.2 and later.
-- pip<=19.3.1
-- python>=3.5.2,<3.8
-- cython
-- urllib3<1.24
+  # Currently Azure ML only supports 3.6.0 and later.
+- pip<=20.2.4
+- python>=3.6.0,<3.9
+- cython==0.29.14
+- urllib3==1.26.7
 - PyJWT < 2.0.0
 - numpy==1.18.5
 
diff --git a/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env_mac.yml b/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env_mac.yml
index e5305d33b..0ca016913 100644
--- a/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env_mac.yml
+++ b/how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env_mac.yml
@@ -1,14 +1,16 @@
 name: azure_automl_experimental
+channels:
+  - conda-forge
+  - main
 dependencies:
   # The python interpreter version.
-  # Currently Azure ML only supports 3.5.2 and later.
-- pip<=19.3.1
+  # Currently Azure ML only supports 3.6.0 and later.
+- pip<=20.2.4
 - nomkl
-- python>=3.5.2,<3.8
-- cython
-- urllib3<1.24
+- python>=3.6.0,<3.9
+- urllib3==1.26.7
 - PyJWT < 2.0.0
-- numpy==1.18.5
+- numpy==1.19.5
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
diff --git a/how-to-use-azureml/automated-machine-learning/experimental/classification-credit-card-fraud-local-managed/auto-ml-classification-credit-card-fraud-local-managed.ipynb b/how-to-use-azureml/automated-machine-learning/experimental/classification-credit-card-fraud-local-managed/auto-ml-classification-credit-card-fraud-local-managed.ipynb
index 9eab021dd..64189e4ec 100644
--- a/how-to-use-azureml/automated-machine-learning/experimental/classification-credit-card-fraud-local-managed/auto-ml-classification-credit-card-fraud-local-managed.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/experimental/classification-credit-card-fraud-local-managed/auto-ml-classification-credit-card-fraud-local-managed.ipynb
@@ -92,7 +92,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
diff --git a/how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb b/how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb
index 1ddbe0a54..37b4b4ed1 100644
--- a/how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb
@@ -91,7 +91,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-backtest-many-models/auto-ml-forecasting-backtest-many-models.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-backtest-many-models/auto-ml-forecasting-backtest-many-models.ipynb
index 610948ed5..23f5a74be 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-backtest-many-models/auto-ml-forecasting-backtest-many-models.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-backtest-many-models/auto-ml-forecasting-backtest-many-models.ipynb
@@ -86,7 +86,7 @@
         "output[\"Resource Group\"] = ws.resource_group\n",
         "output[\"Location\"] = ws.location\n",
         "output[\"Default datastore name\"] = dstore.name\n",
-        "pd.set_option(\"display.max_colwidth\", -1)\n",
+        "pd.set_option(\"display.max_colwidth\", None)\n",
         "outputDf = pd.DataFrame(data=output, index=[\"\"])\n",
         "outputDf.T"
       ]
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-backtest-single-model/auto-ml-forecasting-backtest-single-model.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-backtest-single-model/auto-ml-forecasting-backtest-single-model.ipynb
index 64cada912..5270d3c4a 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-backtest-single-model/auto-ml-forecasting-backtest-single-model.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-backtest-single-model/auto-ml-forecasting-backtest-single-model.ipynb
@@ -100,7 +100,7 @@
         "output[\"SKU\"] = ws.sku\n",
         "output[\"Resource Group\"] = ws.resource_group\n",
         "output[\"Location\"] = ws.location\n",
-        "pd.set_option(\"display.max_colwidth\", -1)\n",
+        "pd.set_option(\"display.max_colwidth\", None)\n",
         "outputDf = pd.DataFrame(data=output, index=[\"\"])\n",
         "outputDf.T"
       ]
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/Beer_no_valid_split_test.csv b/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/Beer_no_valid_split_test.csv
deleted file mode 100644
index bf8759140..000000000
--- a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/Beer_no_valid_split_test.csv
+++ /dev/null
@@ -1,20 +0,0 @@
-DATE,grain,BeerProduction
-2017-01-01,grain,9049
-2017-02-01,grain,10458
-2017-03-01,grain,12489
-2017-04-01,grain,11499
-2017-05-01,grain,13553
-2017-06-01,grain,14740
-2017-07-01,grain,11424
-2017-08-01,grain,13412
-2017-09-01,grain,11917
-2017-10-01,grain,12721
-2017-11-01,grain,13272
-2017-12-01,grain,14278
-2018-01-01,grain,9572
-2018-02-01,grain,10423
-2018-03-01,grain,12667
-2018-04-01,grain,11904
-2018-05-01,grain,14120
-2018-06-01,grain,14565
-2018-07-01,grain,12622
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/Beer_no_valid_split_train.csv b/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/Beer_no_valid_split_train.csv
deleted file mode 100644
index 1b7293d86..000000000
--- a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/Beer_no_valid_split_train.csv
+++ /dev/null
@@ -1,301 +0,0 @@
-DATE,grain,BeerProduction
-1992-01-01,grain,3459
-1992-02-01,grain,3458
-1992-03-01,grain,4002
-1992-04-01,grain,4564
-1992-05-01,grain,4221
-1992-06-01,grain,4529
-1992-07-01,grain,4466
-1992-08-01,grain,4137
-1992-09-01,grain,4126
-1992-10-01,grain,4259
-1992-11-01,grain,4240
-1992-12-01,grain,4936
-1993-01-01,grain,3031
-1993-02-01,grain,3261
-1993-03-01,grain,4160
-1993-04-01,grain,4377
-1993-05-01,grain,4307
-1993-06-01,grain,4696
-1993-07-01,grain,4458
-1993-08-01,grain,4457
-1993-09-01,grain,4364
-1993-10-01,grain,4236
-1993-11-01,grain,4500
-1993-12-01,grain,4974
-1994-01-01,grain,3075
-1994-02-01,grain,3377
-1994-03-01,grain,4443
-1994-04-01,grain,4261
-1994-05-01,grain,4460
-1994-06-01,grain,4985
-1994-07-01,grain,4324
-1994-08-01,grain,4719
-1994-09-01,grain,4374
-1994-10-01,grain,4248
-1994-11-01,grain,4784
-1994-12-01,grain,4971
-1995-01-01,grain,3370
-1995-02-01,grain,3484
-1995-03-01,grain,4269
-1995-04-01,grain,3994
-1995-05-01,grain,4715
-1995-06-01,grain,4974
-1995-07-01,grain,4223
-1995-08-01,grain,5000
-1995-09-01,grain,4235
-1995-10-01,grain,4554
-1995-11-01,grain,4851
-1995-12-01,grain,4826
-1996-01-01,grain,3699
-1996-02-01,grain,3983
-1996-03-01,grain,4262
-1996-04-01,grain,4619
-1996-05-01,grain,5219
-1996-06-01,grain,4836
-1996-07-01,grain,4941
-1996-08-01,grain,5062
-1996-09-01,grain,4365
-1996-10-01,grain,5012
-1996-11-01,grain,4850
-1996-12-01,grain,5097
-1997-01-01,grain,3758
-1997-02-01,grain,3825
-1997-03-01,grain,4454
-1997-04-01,grain,4635
-1997-05-01,grain,5210
-1997-06-01,grain,5057
-1997-07-01,grain,5231
-1997-08-01,grain,5034
-1997-09-01,grain,4970
-1997-10-01,grain,5342
-1997-11-01,grain,4831
-1997-12-01,grain,5965
-1998-01-01,grain,3796
-1998-02-01,grain,4019
-1998-03-01,grain,4898
-1998-04-01,grain,5090
-1998-05-01,grain,5237
-1998-06-01,grain,5447
-1998-07-01,grain,5435
-1998-08-01,grain,5107
-1998-09-01,grain,5515
-1998-10-01,grain,5583
-1998-11-01,grain,5346
-1998-12-01,grain,6286
-1999-01-01,grain,4032
-1999-02-01,grain,4435
-1999-03-01,grain,5479
-1999-04-01,grain,5483
-1999-05-01,grain,5587
-1999-06-01,grain,6176
-1999-07-01,grain,5621
-1999-08-01,grain,5889
-1999-09-01,grain,5828
-1999-10-01,grain,5849
-1999-11-01,grain,6180
-1999-12-01,grain,6771
-2000-01-01,grain,4243
-2000-02-01,grain,4952
-2000-03-01,grain,6008
-2000-04-01,grain,5353
-2000-05-01,grain,6435
-2000-06-01,grain,6673
-2000-07-01,grain,5636
-2000-08-01,grain,6630
-2000-09-01,grain,5887
-2000-10-01,grain,6322
-2000-11-01,grain,6520
-2000-12-01,grain,6678
-2001-01-01,grain,5082
-2001-02-01,grain,5216
-2001-03-01,grain,5893
-2001-04-01,grain,5894
-2001-05-01,grain,6799
-2001-06-01,grain,6667
-2001-07-01,grain,6374
-2001-08-01,grain,6840
-2001-09-01,grain,5575
-2001-10-01,grain,6545
-2001-11-01,grain,6789
-2001-12-01,grain,7180
-2002-01-01,grain,5117
-2002-02-01,grain,5442
-2002-03-01,grain,6337
-2002-04-01,grain,6525
-2002-05-01,grain,7216
-2002-06-01,grain,6761
-2002-07-01,grain,6958
-2002-08-01,grain,7070
-2002-09-01,grain,6148
-2002-10-01,grain,6924
-2002-11-01,grain,6716
-2002-12-01,grain,7975
-2003-01-01,grain,5326
-2003-02-01,grain,5609
-2003-03-01,grain,6414
-2003-04-01,grain,6741
-2003-05-01,grain,7144
-2003-06-01,grain,7133
-2003-07-01,grain,7568
-2003-08-01,grain,7266
-2003-09-01,grain,6634
-2003-10-01,grain,7626
-2003-11-01,grain,6843
-2003-12-01,grain,8540
-2004-01-01,grain,5629
-2004-02-01,grain,5898
-2004-03-01,grain,7045
-2004-04-01,grain,7094
-2004-05-01,grain,7333
-2004-06-01,grain,7918
-2004-07-01,grain,7289
-2004-08-01,grain,7396
-2004-09-01,grain,7259
-2004-10-01,grain,7268
-2004-11-01,grain,7731
-2004-12-01,grain,9058
-2005-01-01,grain,5557
-2005-02-01,grain,6237
-2005-03-01,grain,7723
-2005-04-01,grain,7262
-2005-05-01,grain,8241
-2005-06-01,grain,8757
-2005-07-01,grain,7352
-2005-08-01,grain,8496
-2005-09-01,grain,7741
-2005-10-01,grain,7710
-2005-11-01,grain,8247
-2005-12-01,grain,8902
-2006-01-01,grain,6066
-2006-02-01,grain,6590
-2006-03-01,grain,7923
-2006-04-01,grain,7335
-2006-05-01,grain,8843
-2006-06-01,grain,9327
-2006-07-01,grain,7792
-2006-08-01,grain,9156
-2006-09-01,grain,8037
-2006-10-01,grain,8640
-2006-11-01,grain,9128
-2006-12-01,grain,9545
-2007-01-01,grain,6627
-2007-02-01,grain,6743
-2007-03-01,grain,8195
-2007-04-01,grain,7828
-2007-05-01,grain,9570
-2007-06-01,grain,9484
-2007-07-01,grain,8608
-2007-08-01,grain,9543
-2007-09-01,grain,8123
-2007-10-01,grain,9649
-2007-11-01,grain,9390
-2007-12-01,grain,10065
-2008-01-01,grain,7093
-2008-02-01,grain,7483
-2008-03-01,grain,8365
-2008-04-01,grain,8895
-2008-05-01,grain,9794
-2008-06-01,grain,9977
-2008-07-01,grain,9553
-2008-08-01,grain,9375
-2008-09-01,grain,9225
-2008-10-01,grain,9948
-2008-11-01,grain,8758
-2008-12-01,grain,10839
-2009-01-01,grain,7266
-2009-02-01,grain,7578
-2009-03-01,grain,8688
-2009-04-01,grain,9162
-2009-05-01,grain,9369
-2009-06-01,grain,10167
-2009-07-01,grain,9507
-2009-08-01,grain,8923
-2009-09-01,grain,9272
-2009-10-01,grain,9075
-2009-11-01,grain,8949
-2009-12-01,grain,10843
-2010-01-01,grain,6558
-2010-02-01,grain,7481
-2010-03-01,grain,9475
-2010-04-01,grain,9424
-2010-05-01,grain,9351
-2010-06-01,grain,10552
-2010-07-01,grain,9077
-2010-08-01,grain,9273
-2010-09-01,grain,9420
-2010-10-01,grain,9413
-2010-11-01,grain,9866
-2010-12-01,grain,11455
-2011-01-01,grain,6901
-2011-02-01,grain,8014
-2011-03-01,grain,9832
-2011-04-01,grain,9281
-2011-05-01,grain,9967
-2011-06-01,grain,11344
-2011-07-01,grain,9106
-2011-08-01,grain,10469
-2011-09-01,grain,10085
-2011-10-01,grain,9612
-2011-11-01,grain,10328
-2011-12-01,grain,11483
-2012-01-01,grain,7486
-2012-02-01,grain,8641
-2012-03-01,grain,9709
-2012-04-01,grain,9423
-2012-05-01,grain,11342
-2012-06-01,grain,11274
-2012-07-01,grain,9845
-2012-08-01,grain,11163
-2012-09-01,grain,9532
-2012-10-01,grain,10754
-2012-11-01,grain,10953
-2012-12-01,grain,11922
-2013-01-01,grain,8395
-2013-02-01,grain,8888
-2013-03-01,grain,10110
-2013-04-01,grain,10493
-2013-05-01,grain,12218
-2013-06-01,grain,11385
-2013-07-01,grain,11186
-2013-08-01,grain,11462
-2013-09-01,grain,10494
-2013-10-01,grain,11540
-2013-11-01,grain,11138
-2013-12-01,grain,12709
-2014-01-01,grain,8557
-2014-02-01,grain,9059
-2014-03-01,grain,10055
-2014-04-01,grain,10977
-2014-05-01,grain,11792
-2014-06-01,grain,11904
-2014-07-01,grain,10965
-2014-08-01,grain,10981
-2014-09-01,grain,10828
-2014-10-01,grain,11817
-2014-11-01,grain,10470
-2014-12-01,grain,13310
-2015-01-01,grain,8400
-2015-02-01,grain,9062
-2015-03-01,grain,10722
-2015-04-01,grain,11107
-2015-05-01,grain,11508
-2015-06-01,grain,12904
-2015-07-01,grain,11869
-2015-08-01,grain,11224
-2015-09-01,grain,12022
-2015-10-01,grain,11983
-2015-11-01,grain,11506
-2015-12-01,grain,14183
-2016-01-01,grain,8650
-2016-02-01,grain,10323
-2016-03-01,grain,12110
-2016-04-01,grain,11424
-2016-05-01,grain,12243
-2016-06-01,grain,13686
-2016-07-01,grain,10956
-2016-08-01,grain,12706
-2016-09-01,grain,12279
-2016-10-01,grain,11914
-2016-11-01,grain,13025
-2016-12-01,grain,14431
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.yml b/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.yml
deleted file mode 100644
index 103560d8a..000000000
--- a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.yml
+++ /dev/null
@@ -1,4 +0,0 @@
-name: auto-ml-forecasting-beer-remote
-dependencies:
-- pip:
-  - azureml-sdk
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-bike-share/auto-ml-forecasting-bike-share.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-bike-share/auto-ml-forecasting-bike-share.ipynb
index 48056752e..43fb82867 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-bike-share/auto-ml-forecasting-bike-share.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-bike-share/auto-ml-forecasting-bike-share.ipynb
@@ -89,7 +89,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
@@ -120,7 +120,7 @@
         "output[\"Resource Group\"] = ws.resource_group\n",
         "output[\"Location\"] = ws.location\n",
         "output[\"Run History Name\"] = experiment_name\n",
-        "pd.set_option(\"display.max_colwidth\", -1)\n",
+        "pd.set_option(\"display.max_colwidth\", None)\n",
         "outputDf = pd.DataFrame(data=output, index=[\"\"])\n",
         "outputDf.T"
       ]
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-energy-demand/auto-ml-forecasting-energy-demand.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-energy-demand/auto-ml-forecasting-energy-demand.ipynb
index fe04dbaab..ea791b87d 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-energy-demand/auto-ml-forecasting-energy-demand.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-energy-demand/auto-ml-forecasting-energy-demand.ipynb
@@ -100,7 +100,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-forecast-function/auto-ml-forecasting-function.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-forecast-function/auto-ml-forecasting-function.ipynb
index 23ae3e425..75dca2f7c 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-forecast-function/auto-ml-forecasting-function.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-forecast-function/auto-ml-forecasting-function.ipynb
@@ -94,7 +94,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/auto-ml-forecasting-github-dau.ipynb
similarity index 92%
rename from how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.ipynb
rename to how-to-use-azureml/automated-machine-learning/forecasting-github-dau/auto-ml-forecasting-github-dau.ipynb
index 29e70c8bd..c18587714 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/auto-ml-forecasting-github-dau.ipynb
@@ -30,7 +30,7 @@
       },
       "source": [
         "# Automated Machine Learning\n",
-        "**Beer Production Forecasting**\n",
+        "**Github DAU Forecasting**\n",
         "\n",
         "## Contents\n",
         "1. [Introduction](#Introduction)\n",
@@ -48,7 +48,7 @@
       },
       "source": [
         "## Introduction\n",
-        "This notebook demonstrates demand forecasting for Beer Production Dataset using AutoML.\n",
+        "This notebook demonstrates demand forecasting for Github Daily Active Users Dataset using AutoML.\n",
         "\n",
         "AutoML highlights here include using Deep Learning forecasts, Arima, Prophet,  Remote Execution and Remote Inferencing, and working with the `forecast` function. Please also look at the additional forecasting notebooks, which document lagging, rolling windows, forecast quantiles, other ways to use the forecast function, and forecaster deployment.\n",
         "\n",
@@ -104,7 +104,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "This sample notebook may use features that are not available in previous versions of the Azure ML SDK."
+        "This notebook is compatible with Azure ML SDK version 1.35.0 or later."
       ]
     },
     {
@@ -113,7 +113,6 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
@@ -139,7 +138,7 @@
         "ws = Workspace.from_config()\n",
         "\n",
         "# choose a name for the run history container in the workspace\n",
-        "experiment_name = \"beer-remote-cpu\"\n",
+        "experiment_name = \"github-remote-cpu\"\n",
         "\n",
         "experiment = Experiment(ws, experiment_name)\n",
         "\n",
@@ -149,7 +148,7 @@
         "output[\"Resource Group\"] = ws.resource_group\n",
         "output[\"Location\"] = ws.location\n",
         "output[\"Run History Name\"] = experiment_name\n",
-        "pd.set_option(\"display.max_colwidth\", -1)\n",
+        "pd.set_option(\"display.max_colwidth\", None)\n",
         "outputDf = pd.DataFrame(data=output, index=[\"\"])\n",
         "outputDf.T"
       ]
@@ -180,7 +179,7 @@
         "from azureml.core.compute_target import ComputeTargetException\n",
         "\n",
         "# Choose a name for your CPU cluster\n",
-        "cpu_cluster_name = \"beer-cluster\"\n",
+        "cpu_cluster_name = \"github-cluster\"\n",
         "\n",
         "# Verify that cluster does not exist already\n",
         "try:\n",
@@ -203,7 +202,7 @@
       },
       "source": [
         "## Data\n",
-        "Read Beer demand data from file, and preview data."
+        "Read Github DAU data from file, and preview data."
       ]
     },
     {
@@ -246,21 +245,19 @@
         "plt.tight_layout()\n",
         "\n",
         "plt.subplot(2, 1, 1)\n",
-        "plt.title(\"Beer Production By Year\")\n",
-        "df = pd.read_csv(\n",
-        "    \"Beer_no_valid_split_train.csv\", parse_dates=True, index_col=\"DATE\"\n",
-        ").drop(columns=\"grain\")\n",
+        "plt.title(\"Github Daily Active User By Year\")\n",
+        "df = pd.read_csv(\"github_dau_2011-2018_train.csv\", parse_dates=True, index_col=\"date\")\n",
         "test_df = pd.read_csv(\n",
-        "    \"Beer_no_valid_split_test.csv\", parse_dates=True, index_col=\"DATE\"\n",
-        ").drop(columns=\"grain\")\n",
+        "    \"github_dau_2011-2018_test.csv\", parse_dates=True, index_col=\"date\"\n",
+        ")\n",
         "plt.plot(df)\n",
         "\n",
         "plt.subplot(2, 1, 2)\n",
-        "plt.title(\"Beer Production By Month\")\n",
+        "plt.title(\"Github Daily Active User By Month\")\n",
         "groups = df.groupby(df.index.month)\n",
         "months = concat([DataFrame(x[1].values) for x in groups], axis=1)\n",
         "months = DataFrame(months)\n",
-        "months.columns = range(1, 13)\n",
+        "months.columns = range(1, 49)\n",
         "months.boxplot()\n",
         "\n",
         "plt.show()"
@@ -275,10 +272,10 @@
       },
       "outputs": [],
       "source": [
-        "target_column_name = \"BeerProduction\"\n",
-        "time_column_name = \"DATE\"\n",
+        "target_column_name = \"count\"\n",
+        "time_column_name = \"date\"\n",
         "time_series_id_column_names = []\n",
-        "freq = \"M\"  # Monthly data"
+        "freq = \"D\"  # Daily data"
       ]
     },
     {
@@ -308,19 +305,19 @@
         "datastore = ws.get_default_datastore()\n",
         "datastore.upload_files(\n",
         "    files=[\"./train.csv\"],\n",
-        "    target_path=\"beer-dataset/tabular/\",\n",
+        "    target_path=\"github-dataset/tabular/\",\n",
         "    overwrite=True,\n",
         "    show_progress=True,\n",
         ")\n",
         "datastore.upload_files(\n",
         "    files=[\"./valid.csv\"],\n",
-        "    target_path=\"beer-dataset/tabular/\",\n",
+        "    target_path=\"github-dataset/tabular/\",\n",
         "    overwrite=True,\n",
         "    show_progress=True,\n",
         ")\n",
         "datastore.upload_files(\n",
         "    files=[\"./test.csv\"],\n",
-        "    target_path=\"beer-dataset/tabular/\",\n",
+        "    target_path=\"github-dataset/tabular/\",\n",
         "    overwrite=True,\n",
         "    show_progress=True,\n",
         ")\n",
@@ -328,13 +325,13 @@
         "from azureml.core import Dataset\n",
         "\n",
         "train_dataset = Dataset.Tabular.from_delimited_files(\n",
-        "    path=[(datastore, \"beer-dataset/tabular/train.csv\")]\n",
+        "    path=[(datastore, \"github-dataset/tabular/train.csv\")]\n",
         ")\n",
         "valid_dataset = Dataset.Tabular.from_delimited_files(\n",
-        "    path=[(datastore, \"beer-dataset/tabular/valid.csv\")]\n",
+        "    path=[(datastore, \"github-dataset/tabular/valid.csv\")]\n",
         ")\n",
         "test_dataset = Dataset.Tabular.from_delimited_files(\n",
-        "    path=[(datastore, \"beer-dataset/tabular/test.csv\")]\n",
+        "    path=[(datastore, \"github-dataset/tabular/test.csv\")]\n",
         ")"
       ]
     },
@@ -397,7 +394,7 @@
         "forecasting_parameters = ForecastingParameters(\n",
         "    time_column_name=time_column_name,\n",
         "    forecast_horizon=forecast_horizon,\n",
-        "    freq=\"MS\",  # Set the forecast frequency to be monthly (start of the month)\n",
+        "    freq=\"D\",  # Set the forecast frequency to be daily\n",
         ")\n",
         "\n",
         "# We will disable the enable_early_stopping flag to ensure the DNN model is recommended for demonstration purpose.\n",
@@ -570,7 +567,7 @@
         "from azureml.core import Dataset\n",
         "\n",
         "test_dataset = Dataset.Tabular.from_delimited_files(\n",
-        "    path=[(datastore, \"beer-dataset/tabular/test.csv\")]\n",
+        "    path=[(datastore, \"github-dataset/tabular/test.csv\")]\n",
         ")\n",
         "# preview the first 3 rows of the dataset\n",
         "test_dataset.take(5).to_pandas_dataframe()"
@@ -582,7 +579,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "compute_target = ws.compute_targets[\"beer-cluster\"]\n",
+        "compute_target = ws.compute_targets[\"github-cluster\"]\n",
         "test_experiment = Experiment(ws, experiment_name + \"_test\")"
       ]
     },
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/auto-ml-forecasting-github-dau.yml b/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/auto-ml-forecasting-github-dau.yml
new file mode 100644
index 000000000..eee39bd4d
--- /dev/null
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/auto-ml-forecasting-github-dau.yml
@@ -0,0 +1,4 @@
+name: auto-ml-forecasting-github-dau
+dependencies:
+- pip:
+  - azureml-sdk
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/github_dau_2011-2018_test.csv b/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/github_dau_2011-2018_test.csv
new file mode 100644
index 000000000..6061b0d21
--- /dev/null
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/github_dau_2011-2018_test.csv
@@ -0,0 +1,455 @@
+date,count,day_of_week,month_of_year,holiday
+2017-06-04,104663,6.0,5.0,0.0
+2017-06-05,155824,0.0,5.0,0.0
+2017-06-06,164908,1.0,5.0,0.0
+2017-06-07,170309,2.0,5.0,0.0
+2017-06-08,164256,3.0,5.0,0.0
+2017-06-09,153406,4.0,5.0,0.0
+2017-06-10,97024,5.0,5.0,0.0
+2017-06-11,103442,6.0,5.0,0.0
+2017-06-12,160768,0.0,5.0,0.0
+2017-06-13,166288,1.0,5.0,0.0
+2017-06-14,163819,2.0,5.0,0.0
+2017-06-15,157593,3.0,5.0,0.0
+2017-06-16,149259,4.0,5.0,0.0
+2017-06-17,95579,5.0,5.0,0.0
+2017-06-18,98723,6.0,5.0,0.0
+2017-06-19,159076,0.0,5.0,0.0
+2017-06-20,163340,1.0,5.0,0.0
+2017-06-21,163344,2.0,5.0,0.0
+2017-06-22,159528,3.0,5.0,0.0
+2017-06-23,146563,4.0,5.0,0.0
+2017-06-24,92631,5.0,5.0,0.0
+2017-06-25,96549,6.0,5.0,0.0
+2017-06-26,153249,0.0,5.0,0.0
+2017-06-27,160357,1.0,5.0,0.0
+2017-06-28,159941,2.0,5.0,0.0
+2017-06-29,156781,3.0,5.0,0.0
+2017-06-30,144709,4.0,5.0,0.0
+2017-07-01,89101,5.0,6.0,0.0
+2017-07-02,93046,6.0,6.0,0.0
+2017-07-03,144113,0.0,6.0,0.0
+2017-07-04,143061,1.0,6.0,1.0
+2017-07-05,154603,2.0,6.0,0.0
+2017-07-06,157200,3.0,6.0,0.0
+2017-07-07,147213,4.0,6.0,0.0
+2017-07-08,92348,5.0,6.0,0.0
+2017-07-09,97018,6.0,6.0,0.0
+2017-07-10,157192,0.0,6.0,0.0
+2017-07-11,161819,1.0,6.0,0.0
+2017-07-12,161998,2.0,6.0,0.0
+2017-07-13,160280,3.0,6.0,0.0
+2017-07-14,146818,4.0,6.0,0.0
+2017-07-15,93041,5.0,6.0,0.0
+2017-07-16,97505,6.0,6.0,0.0
+2017-07-17,156167,0.0,6.0,0.0
+2017-07-18,162855,1.0,6.0,0.0
+2017-07-19,162519,2.0,6.0,0.0
+2017-07-20,159941,3.0,6.0,0.0
+2017-07-21,148460,4.0,6.0,0.0
+2017-07-22,93431,5.0,6.0,0.0
+2017-07-23,98553,6.0,6.0,0.0
+2017-07-24,156202,0.0,6.0,0.0
+2017-07-25,162503,1.0,6.0,0.0
+2017-07-26,158479,2.0,6.0,0.0
+2017-07-27,158192,3.0,6.0,0.0
+2017-07-28,147108,4.0,6.0,0.0
+2017-07-29,93799,5.0,6.0,0.0
+2017-07-30,97920,6.0,6.0,0.0
+2017-07-31,152197,0.0,6.0,0.0
+2017-08-01,158477,1.0,7.0,0.0
+2017-08-02,159089,2.0,7.0,0.0
+2017-08-03,157182,3.0,7.0,0.0
+2017-08-04,146345,4.0,7.0,0.0
+2017-08-05,92534,5.0,7.0,0.0
+2017-08-06,97128,6.0,7.0,0.0
+2017-08-07,151359,0.0,7.0,0.0
+2017-08-08,159895,1.0,7.0,0.0
+2017-08-09,158329,2.0,7.0,0.0
+2017-08-10,155468,3.0,7.0,0.0
+2017-08-11,144914,4.0,7.0,0.0
+2017-08-12,92258,5.0,7.0,0.0
+2017-08-13,95933,6.0,7.0,0.0
+2017-08-14,147706,0.0,7.0,0.0
+2017-08-15,151115,1.0,7.0,0.0
+2017-08-16,157640,2.0,7.0,0.0
+2017-08-17,156600,3.0,7.0,0.0
+2017-08-18,146980,4.0,7.0,0.0
+2017-08-19,94592,5.0,7.0,0.0
+2017-08-20,99320,6.0,7.0,0.0
+2017-08-21,145727,0.0,7.0,0.0
+2017-08-22,160260,1.0,7.0,0.0
+2017-08-23,160440,2.0,7.0,0.0
+2017-08-24,157830,3.0,7.0,0.0
+2017-08-25,145822,4.0,7.0,0.0
+2017-08-26,94706,5.0,7.0,0.0
+2017-08-27,99047,6.0,7.0,0.0
+2017-08-28,152112,0.0,7.0,0.0
+2017-08-29,162440,1.0,7.0,0.0
+2017-08-30,162902,2.0,7.0,0.0
+2017-08-31,159498,3.0,7.0,0.0
+2017-09-01,145689,4.0,8.0,0.0
+2017-09-02,93589,5.0,8.0,0.0
+2017-09-03,100058,6.0,8.0,0.0
+2017-09-04,140865,0.0,8.0,1.0
+2017-09-05,165715,1.0,8.0,0.0
+2017-09-06,167463,2.0,8.0,0.0
+2017-09-07,164811,3.0,8.0,0.0
+2017-09-08,156157,4.0,8.0,0.0
+2017-09-09,101358,5.0,8.0,0.0
+2017-09-10,107915,6.0,8.0,0.0
+2017-09-11,167845,0.0,8.0,0.0
+2017-09-12,172756,1.0,8.0,0.0
+2017-09-13,172851,2.0,8.0,0.0
+2017-09-14,171675,3.0,8.0,0.0
+2017-09-15,159266,4.0,8.0,0.0
+2017-09-16,103547,5.0,8.0,0.0
+2017-09-17,110964,6.0,8.0,0.0
+2017-09-18,170976,0.0,8.0,0.0
+2017-09-19,177864,1.0,8.0,0.0
+2017-09-20,173567,2.0,8.0,0.0
+2017-09-21,172017,3.0,8.0,0.0
+2017-09-22,161357,4.0,8.0,0.0
+2017-09-23,104681,5.0,8.0,0.0
+2017-09-24,111711,6.0,8.0,0.0
+2017-09-25,173517,0.0,8.0,0.0
+2017-09-26,180049,1.0,8.0,0.0
+2017-09-27,178307,2.0,8.0,0.0
+2017-09-28,174157,3.0,8.0,0.0
+2017-09-29,161707,4.0,8.0,0.0
+2017-09-30,110536,5.0,8.0,0.0
+2017-10-01,106505,6.0,9.0,0.0
+2017-10-02,157565,0.0,9.0,0.0
+2017-10-03,164764,1.0,9.0,0.0
+2017-10-04,163383,2.0,9.0,0.0
+2017-10-05,162847,3.0,9.0,0.0
+2017-10-06,153575,4.0,9.0,0.0
+2017-10-07,107472,5.0,9.0,0.0
+2017-10-08,116127,6.0,9.0,0.0
+2017-10-09,174457,0.0,9.0,1.0
+2017-10-10,185217,1.0,9.0,0.0
+2017-10-11,185120,2.0,9.0,0.0
+2017-10-12,180844,3.0,9.0,0.0
+2017-10-13,170178,4.0,9.0,0.0
+2017-10-14,112754,5.0,9.0,0.0
+2017-10-15,121251,6.0,9.0,0.0
+2017-10-16,183906,0.0,9.0,0.0
+2017-10-17,188945,1.0,9.0,0.0
+2017-10-18,187297,2.0,9.0,0.0
+2017-10-19,183867,3.0,9.0,0.0
+2017-10-20,173021,4.0,9.0,0.0
+2017-10-21,115851,5.0,9.0,0.0
+2017-10-22,126088,6.0,9.0,0.0
+2017-10-23,189452,0.0,9.0,0.0
+2017-10-24,194412,1.0,9.0,0.0
+2017-10-25,192293,2.0,9.0,0.0
+2017-10-26,190163,3.0,9.0,0.0
+2017-10-27,177053,4.0,9.0,0.0
+2017-10-28,114934,5.0,9.0,0.0
+2017-10-29,125289,6.0,9.0,0.0
+2017-10-30,189245,0.0,9.0,0.0
+2017-10-31,191480,1.0,9.0,0.0
+2017-11-01,182281,2.0,10.0,0.0
+2017-11-02,186351,3.0,10.0,0.0
+2017-11-03,175422,4.0,10.0,0.0
+2017-11-04,118160,5.0,10.0,0.0
+2017-11-05,127602,6.0,10.0,0.0
+2017-11-06,191067,0.0,10.0,0.0
+2017-11-07,197083,1.0,10.0,0.0
+2017-11-08,194333,2.0,10.0,0.0
+2017-11-09,193914,3.0,10.0,0.0
+2017-11-10,179933,4.0,10.0,1.0
+2017-11-11,121346,5.0,10.0,0.0
+2017-11-12,131900,6.0,10.0,0.0
+2017-11-13,196969,0.0,10.0,0.0
+2017-11-14,201949,1.0,10.0,0.0
+2017-11-15,198424,2.0,10.0,0.0
+2017-11-16,196902,3.0,10.0,0.0
+2017-11-17,183893,4.0,10.0,0.0
+2017-11-18,122767,5.0,10.0,0.0
+2017-11-19,130890,6.0,10.0,0.0
+2017-11-20,194515,0.0,10.0,0.0
+2017-11-21,198601,1.0,10.0,0.0
+2017-11-22,191041,2.0,10.0,0.0
+2017-11-23,170321,3.0,10.0,1.0
+2017-11-24,155623,4.0,10.0,0.0
+2017-11-25,115759,5.0,10.0,0.0
+2017-11-26,128771,6.0,10.0,0.0
+2017-11-27,199419,0.0,10.0,0.0
+2017-11-28,207253,1.0,10.0,0.0
+2017-11-29,205406,2.0,10.0,0.0
+2017-11-30,200674,3.0,10.0,0.0
+2017-12-01,187017,4.0,11.0,0.0
+2017-12-02,129735,5.0,11.0,0.0
+2017-12-03,139120,6.0,11.0,0.0
+2017-12-04,205505,0.0,11.0,0.0
+2017-12-05,208218,1.0,11.0,0.0
+2017-12-06,202480,2.0,11.0,0.0
+2017-12-07,197822,3.0,11.0,0.0
+2017-12-08,180686,4.0,11.0,0.0
+2017-12-09,123667,5.0,11.0,0.0
+2017-12-10,130987,6.0,11.0,0.0
+2017-12-11,193901,0.0,11.0,0.0
+2017-12-12,194997,1.0,11.0,0.0
+2017-12-13,192063,2.0,11.0,0.0
+2017-12-14,186496,3.0,11.0,0.0
+2017-12-15,170812,4.0,11.0,0.0
+2017-12-16,110474,5.0,11.0,0.0
+2017-12-17,118165,6.0,11.0,0.0
+2017-12-18,176843,0.0,11.0,0.0
+2017-12-19,179550,1.0,11.0,0.0
+2017-12-20,173506,2.0,11.0,0.0
+2017-12-21,165910,3.0,11.0,0.0
+2017-12-22,145886,4.0,11.0,0.0
+2017-12-23,95246,5.0,11.0,0.0
+2017-12-24,88781,6.0,11.0,0.0
+2017-12-25,98189,0.0,11.0,1.0
+2017-12-26,121383,1.0,11.0,0.0
+2017-12-27,135300,2.0,11.0,0.0
+2017-12-28,136827,3.0,11.0,0.0
+2017-12-29,127700,4.0,11.0,0.0
+2017-12-30,93014,5.0,11.0,0.0
+2017-12-31,82878,6.0,11.0,0.0
+2018-01-01,86419,0.0,0.0,1.0
+2018-01-02,147428,1.0,0.0,0.0
+2018-01-03,162193,2.0,0.0,0.0
+2018-01-04,163784,3.0,0.0,0.0
+2018-01-05,158606,4.0,0.0,0.0
+2018-01-06,113467,5.0,0.0,0.0
+2018-01-07,118313,6.0,0.0,0.0
+2018-01-08,175623,0.0,0.0,0.0
+2018-01-09,183880,1.0,0.0,0.0
+2018-01-10,183945,2.0,0.0,0.0
+2018-01-11,181769,3.0,0.0,0.0
+2018-01-12,170552,4.0,0.0,0.0
+2018-01-13,115707,5.0,0.0,0.0
+2018-01-14,121191,6.0,0.0,0.0
+2018-01-15,176127,0.0,0.0,1.0
+2018-01-16,188032,1.0,0.0,0.0
+2018-01-17,189871,2.0,0.0,0.0
+2018-01-18,189348,3.0,0.0,0.0
+2018-01-19,177456,4.0,0.0,0.0
+2018-01-20,123321,5.0,0.0,0.0
+2018-01-21,128306,6.0,0.0,0.0
+2018-01-22,186132,0.0,0.0,0.0
+2018-01-23,197618,1.0,0.0,0.0
+2018-01-24,196402,2.0,0.0,0.0
+2018-01-25,192722,3.0,0.0,0.0
+2018-01-26,179415,4.0,0.0,0.0
+2018-01-27,125769,5.0,0.0,0.0
+2018-01-28,133306,6.0,0.0,0.0
+2018-01-29,194151,0.0,0.0,0.0
+2018-01-30,198680,1.0,0.0,0.0
+2018-01-31,198652,2.0,0.0,0.0
+2018-02-01,195472,3.0,1.0,0.0
+2018-02-02,183173,4.0,1.0,0.0
+2018-02-03,124276,5.0,1.0,0.0
+2018-02-04,129054,6.0,1.0,0.0
+2018-02-05,190024,0.0,1.0,0.0
+2018-02-06,198658,1.0,1.0,0.0
+2018-02-07,198272,2.0,1.0,0.0
+2018-02-08,195339,3.0,1.0,0.0
+2018-02-09,183086,4.0,1.0,0.0
+2018-02-10,122536,5.0,1.0,0.0
+2018-02-11,133033,6.0,1.0,0.0
+2018-02-12,185386,0.0,1.0,0.0
+2018-02-13,184789,1.0,1.0,0.0
+2018-02-14,176089,2.0,1.0,0.0
+2018-02-15,171317,3.0,1.0,0.0
+2018-02-16,162693,4.0,1.0,0.0
+2018-02-17,116342,5.0,1.0,0.0
+2018-02-18,122466,6.0,1.0,0.0
+2018-02-19,172364,0.0,1.0,1.0
+2018-02-20,185896,1.0,1.0,0.0
+2018-02-21,188166,2.0,1.0,0.0
+2018-02-22,189427,3.0,1.0,0.0
+2018-02-23,178732,4.0,1.0,0.0
+2018-02-24,132664,5.0,1.0,0.0
+2018-02-25,134008,6.0,1.0,0.0
+2018-02-26,200075,0.0,1.0,0.0
+2018-02-27,207996,1.0,1.0,0.0
+2018-02-28,204416,2.0,1.0,0.0
+2018-03-01,201320,3.0,2.0,0.0
+2018-03-02,188205,4.0,2.0,0.0
+2018-03-03,131162,5.0,2.0,0.0
+2018-03-04,138320,6.0,2.0,0.0
+2018-03-05,207326,0.0,2.0,0.0
+2018-03-06,212462,1.0,2.0,0.0
+2018-03-07,209357,2.0,2.0,0.0
+2018-03-08,194876,3.0,2.0,0.0
+2018-03-09,193761,4.0,2.0,0.0
+2018-03-10,133449,5.0,2.0,0.0
+2018-03-11,142258,6.0,2.0,0.0
+2018-03-12,208753,0.0,2.0,0.0
+2018-03-13,210602,1.0,2.0,0.0
+2018-03-14,214236,2.0,2.0,0.0
+2018-03-15,210761,3.0,2.0,0.0
+2018-03-16,196619,4.0,2.0,0.0
+2018-03-17,133056,5.0,2.0,0.0
+2018-03-18,141335,6.0,2.0,0.0
+2018-03-19,211580,0.0,2.0,0.0
+2018-03-20,219051,1.0,2.0,0.0
+2018-03-21,215435,2.0,2.0,0.0
+2018-03-22,211961,3.0,2.0,0.0
+2018-03-23,196009,4.0,2.0,0.0
+2018-03-24,132390,5.0,2.0,0.0
+2018-03-25,140021,6.0,2.0,0.0
+2018-03-26,205273,0.0,2.0,0.0
+2018-03-27,212686,1.0,2.0,0.0
+2018-03-28,210683,2.0,2.0,0.0
+2018-03-29,189044,3.0,2.0,0.0
+2018-03-30,170256,4.0,2.0,0.0
+2018-03-31,125999,5.0,2.0,0.0
+2018-04-01,126749,6.0,3.0,0.0
+2018-04-02,186546,0.0,3.0,0.0
+2018-04-03,207905,1.0,3.0,0.0
+2018-04-04,201528,2.0,3.0,0.0
+2018-04-05,188580,3.0,3.0,0.0
+2018-04-06,173714,4.0,3.0,0.0
+2018-04-07,125723,5.0,3.0,0.0
+2018-04-08,142545,6.0,3.0,0.0
+2018-04-09,204767,0.0,3.0,0.0
+2018-04-10,212048,1.0,3.0,0.0
+2018-04-11,210517,2.0,3.0,0.0
+2018-04-12,206924,3.0,3.0,0.0
+2018-04-13,191679,4.0,3.0,0.0
+2018-04-14,126394,5.0,3.0,0.0
+2018-04-15,137279,6.0,3.0,0.0
+2018-04-16,208085,0.0,3.0,0.0
+2018-04-17,213273,1.0,3.0,0.0
+2018-04-18,211580,2.0,3.0,0.0
+2018-04-19,206037,3.0,3.0,0.0
+2018-04-20,191211,4.0,3.0,0.0
+2018-04-21,125564,5.0,3.0,0.0
+2018-04-22,136469,6.0,3.0,0.0
+2018-04-23,206288,0.0,3.0,0.0
+2018-04-24,212115,1.0,3.0,0.0
+2018-04-25,207948,2.0,3.0,0.0
+2018-04-26,205759,3.0,3.0,0.0
+2018-04-27,181330,4.0,3.0,0.0
+2018-04-28,130046,5.0,3.0,0.0
+2018-04-29,120802,6.0,3.0,0.0
+2018-04-30,170390,0.0,3.0,0.0
+2018-05-01,169054,1.0,4.0,0.0
+2018-05-02,197891,2.0,4.0,0.0
+2018-05-03,199820,3.0,4.0,0.0
+2018-05-04,186783,4.0,4.0,0.0
+2018-05-05,124420,5.0,4.0,0.0
+2018-05-06,130666,6.0,4.0,0.0
+2018-05-07,196014,0.0,4.0,0.0
+2018-05-08,203058,1.0,4.0,0.0
+2018-05-09,198582,2.0,4.0,0.0
+2018-05-10,191321,3.0,4.0,0.0
+2018-05-11,183639,4.0,4.0,0.0
+2018-05-12,122023,5.0,4.0,0.0
+2018-05-13,128775,6.0,4.0,0.0
+2018-05-14,199104,0.0,4.0,0.0
+2018-05-15,200658,1.0,4.0,0.0
+2018-05-16,201541,2.0,4.0,0.0
+2018-05-17,196886,3.0,4.0,0.0
+2018-05-18,188597,4.0,4.0,0.0
+2018-05-19,121392,5.0,4.0,0.0
+2018-05-20,126981,6.0,4.0,0.0
+2018-05-21,189291,0.0,4.0,0.0
+2018-05-22,203038,1.0,4.0,0.0
+2018-05-23,205330,2.0,4.0,0.0
+2018-05-24,199208,3.0,4.0,0.0
+2018-05-25,187768,4.0,4.0,0.0
+2018-05-26,117635,5.0,4.0,0.0
+2018-05-27,124352,6.0,4.0,0.0
+2018-05-28,180398,0.0,4.0,1.0
+2018-05-29,194170,1.0,4.0,0.0
+2018-05-30,200281,2.0,4.0,0.0
+2018-05-31,197244,3.0,4.0,0.0
+2018-06-01,184037,4.0,5.0,0.0
+2018-06-02,121135,5.0,5.0,0.0
+2018-06-03,129389,6.0,5.0,0.0
+2018-06-04,200331,0.0,5.0,0.0
+2018-06-05,207735,1.0,5.0,0.0
+2018-06-06,203354,2.0,5.0,0.0
+2018-06-07,200520,3.0,5.0,0.0
+2018-06-08,182038,4.0,5.0,0.0
+2018-06-09,120164,5.0,5.0,0.0
+2018-06-10,125256,6.0,5.0,0.0
+2018-06-11,194786,0.0,5.0,0.0
+2018-06-12,200815,1.0,5.0,0.0
+2018-06-13,197740,2.0,5.0,0.0
+2018-06-14,192294,3.0,5.0,0.0
+2018-06-15,173587,4.0,5.0,0.0
+2018-06-16,105955,5.0,5.0,0.0
+2018-06-17,110780,6.0,5.0,0.0
+2018-06-18,174582,0.0,5.0,0.0
+2018-06-19,193310,1.0,5.0,0.0
+2018-06-20,193062,2.0,5.0,0.0
+2018-06-21,187986,3.0,5.0,0.0
+2018-06-22,173606,4.0,5.0,0.0
+2018-06-23,111795,5.0,5.0,0.0
+2018-06-24,116134,6.0,5.0,0.0
+2018-06-25,185919,0.0,5.0,0.0
+2018-06-26,193142,1.0,5.0,0.0
+2018-06-27,188114,2.0,5.0,0.0
+2018-06-28,183737,3.0,5.0,0.0
+2018-06-29,171496,4.0,5.0,0.0
+2018-06-30,107210,5.0,5.0,0.0
+2018-07-01,111053,6.0,6.0,0.0
+2018-07-02,176198,0.0,6.0,0.0
+2018-07-03,184040,1.0,6.0,0.0
+2018-07-04,169783,2.0,6.0,1.0
+2018-07-05,177996,3.0,6.0,0.0
+2018-07-06,167378,4.0,6.0,0.0
+2018-07-07,106401,5.0,6.0,0.0
+2018-07-08,112327,6.0,6.0,0.0
+2018-07-09,182835,0.0,6.0,0.0
+2018-07-10,187694,1.0,6.0,0.0
+2018-07-11,185762,2.0,6.0,0.0
+2018-07-12,184099,3.0,6.0,0.0
+2018-07-13,170860,4.0,6.0,0.0
+2018-07-14,106799,5.0,6.0,0.0
+2018-07-15,108475,6.0,6.0,0.0
+2018-07-16,175704,0.0,6.0,0.0
+2018-07-17,183596,1.0,6.0,0.0
+2018-07-18,179897,2.0,6.0,0.0
+2018-07-19,183373,3.0,6.0,0.0
+2018-07-20,169626,4.0,6.0,0.0
+2018-07-21,106785,5.0,6.0,0.0
+2018-07-22,112387,6.0,6.0,0.0
+2018-07-23,180572,0.0,6.0,0.0
+2018-07-24,186943,1.0,6.0,0.0
+2018-07-25,185744,2.0,6.0,0.0
+2018-07-26,183117,3.0,6.0,0.0
+2018-07-27,168526,4.0,6.0,0.0
+2018-07-28,105936,5.0,6.0,0.0
+2018-07-29,111708,6.0,6.0,0.0
+2018-07-30,179950,0.0,6.0,0.0
+2018-07-31,185930,1.0,6.0,0.0
+2018-08-01,183366,2.0,7.0,0.0
+2018-08-02,182412,3.0,7.0,0.0
+2018-08-03,173429,4.0,7.0,0.0
+2018-08-04,106108,5.0,7.0,0.0
+2018-08-05,110059,6.0,7.0,0.0
+2018-08-06,178355,0.0,7.0,0.0
+2018-08-07,185518,1.0,7.0,0.0
+2018-08-08,183204,2.0,7.0,0.0
+2018-08-09,181276,3.0,7.0,0.0
+2018-08-10,168297,4.0,7.0,0.0
+2018-08-11,106488,5.0,7.0,0.0
+2018-08-12,111786,6.0,7.0,0.0
+2018-08-13,178620,0.0,7.0,0.0
+2018-08-14,181922,1.0,7.0,0.0
+2018-08-15,172198,2.0,7.0,0.0
+2018-08-16,177367,3.0,7.0,0.0
+2018-08-17,166550,4.0,7.0,0.0
+2018-08-18,107011,5.0,7.0,0.0
+2018-08-19,112299,6.0,7.0,0.0
+2018-08-20,176718,0.0,7.0,0.0
+2018-08-21,182562,1.0,7.0,0.0
+2018-08-22,181484,2.0,7.0,0.0
+2018-08-23,180317,3.0,7.0,0.0
+2018-08-24,170197,4.0,7.0,0.0
+2018-08-25,109383,5.0,7.0,0.0
+2018-08-26,113373,6.0,7.0,0.0
+2018-08-27,180142,0.0,7.0,0.0
+2018-08-28,191628,1.0,7.0,0.0
+2018-08-29,191149,2.0,7.0,0.0
+2018-08-30,187503,3.0,7.0,0.0
+2018-08-31,172280,4.0,7.0,0.0
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/github_dau_2011-2018_train.csv b/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/github_dau_2011-2018_train.csv
new file mode 100644
index 000000000..5a409ad26
--- /dev/null
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/github_dau_2011-2018_train.csv
@@ -0,0 +1,2286 @@
+date,count,day_of_week,month_of_year,holiday
+2011-03-01,8583,1.0,2.0,0.0
+2011-03-02,8561,2.0,2.0,0.0
+2011-03-03,8406,3.0,2.0,0.0
+2011-03-04,7921,4.0,2.0,0.0
+2011-03-05,5597,5.0,2.0,0.0
+2011-03-06,6400,6.0,2.0,0.0
+2011-03-07,8043,0.0,2.0,0.0
+2011-03-08,8666,1.0,2.0,0.0
+2011-03-09,8344,2.0,2.0,0.0
+2011-03-10,8344,3.0,2.0,0.0
+2011-03-11,8017,4.0,2.0,0.0
+2011-03-12,5756,5.0,2.0,0.0
+2011-03-13,6294,6.0,2.0,0.0
+2011-03-14,8210,0.0,2.0,0.0
+2011-03-15,8882,1.0,2.0,0.0
+2011-03-16,8849,2.0,2.0,0.0
+2011-03-17,8611,3.0,2.0,0.0
+2011-03-18,8160,4.0,2.0,0.0
+2011-03-19,6068,5.0,2.0,0.0
+2011-03-20,6485,6.0,2.0,0.0
+2011-03-21,8596,0.0,2.0,0.0
+2011-03-22,9240,1.0,2.0,0.0
+2011-03-23,9005,2.0,2.0,0.0
+2011-03-24,8653,3.0,2.0,0.0
+2011-03-25,8288,4.0,2.0,0.0
+2011-03-26,6317,5.0,2.0,0.0
+2011-03-27,6793,6.0,2.0,0.0
+2011-03-28,9369,0.0,2.0,0.0
+2011-03-29,8589,1.0,2.0,0.0
+2011-03-30,9100,2.0,2.0,0.0
+2011-03-31,9013,3.0,2.0,0.0
+2011-04-01,8439,4.0,3.0,0.0
+2011-04-02,6142,5.0,3.0,0.0
+2011-04-03,6703,6.0,3.0,0.0
+2011-04-04,9516,0.0,3.0,0.0
+2011-04-05,9736,1.0,3.0,0.0
+2011-04-06,9370,2.0,3.0,0.0
+2011-04-07,9178,3.0,3.0,0.0
+2011-04-08,8862,4.0,3.0,0.0
+2011-04-09,6183,5.0,3.0,0.0
+2011-04-10,6798,6.0,3.0,0.0
+2011-04-11,9661,0.0,3.0,0.0
+2011-04-12,9498,1.0,3.0,0.0
+2011-04-13,9668,2.0,3.0,0.0
+2011-04-14,9651,3.0,3.0,0.0
+2011-04-15,9052,4.0,3.0,0.0
+2011-04-16,6559,5.0,3.0,0.0
+2011-04-17,6826,6.0,3.0,0.0
+2011-04-18,9243,0.0,3.0,0.0
+2011-04-19,9787,1.0,3.0,0.0
+2011-04-20,9259,2.0,3.0,0.0
+2011-04-21,9090,3.0,3.0,0.0
+2011-04-22,7812,4.0,3.0,0.0
+2011-04-23,6081,5.0,3.0,0.0
+2011-04-24,6106,6.0,3.0,0.0
+2011-04-25,7975,0.0,3.0,0.0
+2011-04-26,9656,1.0,3.0,0.0
+2011-04-27,9090,2.0,3.0,0.0
+2011-04-28,8600,3.0,3.0,0.0
+2011-04-29,9050,4.0,3.0,0.0
+2011-04-30,6073,5.0,3.0,0.0
+2011-05-01,6554,6.0,4.0,0.0
+2011-05-02,8287,0.0,4.0,0.0
+2011-05-03,9763,1.0,4.0,0.0
+2011-05-04,10105,2.0,4.0,0.0
+2011-05-05,10113,3.0,4.0,0.0
+2011-05-06,9085,4.0,4.0,0.0
+2011-05-07,6286,5.0,4.0,0.0
+2011-05-08,6674,6.0,4.0,0.0
+2011-05-09,9810,0.0,4.0,0.0
+2011-05-10,9390,1.0,4.0,0.0
+2011-05-11,10237,2.0,4.0,0.0
+2011-05-12,9630,3.0,4.0,0.0
+2011-05-13,9248,4.0,4.0,0.0
+2011-05-14,6785,5.0,4.0,0.0
+2011-05-15,7197,6.0,4.0,0.0
+2011-05-16,9794,0.0,4.0,0.0
+2011-05-17,10042,1.0,4.0,0.0
+2011-05-18,9978,2.0,4.0,0.0
+2011-05-19,10032,3.0,4.0,0.0
+2011-05-20,8662,4.0,4.0,0.0
+2011-05-21,6172,5.0,4.0,0.0
+2011-05-22,6423,6.0,4.0,0.0
+2011-05-23,10039,0.0,4.0,0.0
+2011-05-24,10487,1.0,4.0,0.0
+2011-05-25,10291,2.0,4.0,0.0
+2011-05-26,10188,3.0,4.0,0.0
+2011-05-27,8773,4.0,4.0,0.0
+2011-05-28,6323,5.0,4.0,0.0
+2011-05-29,6728,6.0,4.0,0.0
+2011-05-30,8663,0.0,4.0,1.0
+2011-05-31,10047,1.0,4.0,0.0
+2011-06-01,10183,2.0,5.0,0.0
+2011-06-02,9305,3.0,5.0,0.0
+2011-06-03,9493,4.0,5.0,0.0
+2011-06-04,6682,5.0,5.0,0.0
+2011-06-05,7043,6.0,5.0,0.0
+2011-06-06,9619,0.0,5.0,0.0
+2011-06-07,10108,1.0,5.0,0.0
+2011-06-08,10330,2.0,5.0,0.0
+2011-06-09,9792,3.0,5.0,0.0
+2011-06-10,9287,4.0,5.0,0.0
+2011-06-11,6432,5.0,5.0,0.0
+2011-06-12,6278,6.0,5.0,0.0
+2011-06-13,9515,0.0,5.0,0.0
+2011-06-14,10155,1.0,5.0,0.0
+2011-06-15,9979,2.0,5.0,0.0
+2011-06-16,9880,3.0,5.0,0.0
+2011-06-17,9855,4.0,5.0,0.0
+2011-06-18,6356,5.0,5.0,0.0
+2011-06-19,7028,6.0,5.0,0.0
+2011-06-20,10335,0.0,5.0,0.0
+2011-06-21,10383,1.0,5.0,0.0
+2011-06-22,10391,2.0,5.0,0.0
+2011-06-23,7190,3.0,5.0,0.0
+2011-06-24,9613,4.0,5.0,0.0
+2011-06-25,5890,5.0,5.0,0.0
+2011-06-26,6256,6.0,5.0,0.0
+2011-06-27,8825,0.0,5.0,0.0
+2011-06-28,10263,1.0,5.0,0.0
+2011-06-29,10628,2.0,5.0,0.0
+2011-06-30,10043,3.0,5.0,0.0
+2011-07-01,9403,4.0,6.0,0.0
+2011-07-02,6294,5.0,6.0,0.0
+2011-07-03,6485,6.0,6.0,0.0
+2011-07-04,8954,0.0,6.0,1.0
+2011-07-05,9672,1.0,6.0,0.0
+2011-07-06,10488,2.0,6.0,0.0
+2011-07-07,10199,3.0,6.0,0.0
+2011-07-08,9300,4.0,6.0,0.0
+2011-07-09,6544,5.0,6.0,0.0
+2011-07-10,6898,6.0,6.0,0.0
+2011-07-11,10087,0.0,6.0,0.0
+2011-07-12,10623,1.0,6.0,0.0
+2011-07-13,10201,2.0,6.0,0.0
+2011-07-14,9771,3.0,6.0,0.0
+2011-07-15,9339,4.0,6.0,0.0
+2011-07-16,6690,5.0,6.0,0.0
+2011-07-17,7059,6.0,6.0,0.0
+2011-07-18,10367,0.0,6.0,0.0
+2011-07-19,10123,1.0,6.0,0.0
+2011-07-20,10370,2.0,6.0,0.0
+2011-07-21,10296,3.0,6.0,0.0
+2011-07-22,9479,4.0,6.0,0.0
+2011-07-23,6667,5.0,6.0,0.0
+2011-07-24,6929,6.0,6.0,0.0
+2011-07-25,9924,0.0,6.0,0.0
+2011-07-26,10840,1.0,6.0,0.0
+2011-07-27,10588,2.0,6.0,0.0
+2011-07-28,10195,3.0,6.0,0.0
+2011-07-29,9688,4.0,6.0,0.0
+2011-07-30,6070,5.0,6.0,0.0
+2011-07-31,6858,6.0,6.0,0.0
+2011-08-01,9822,0.0,7.0,0.0
+2011-08-02,10529,1.0,7.0,0.0
+2011-08-03,10392,2.0,7.0,0.0
+2011-08-04,10498,3.0,7.0,0.0
+2011-08-05,9775,4.0,7.0,0.0
+2011-08-06,6653,5.0,7.0,0.0
+2011-08-07,6361,6.0,7.0,0.0
+2011-08-08,10287,0.0,7.0,0.0
+2011-08-09,10742,1.0,7.0,0.0
+2011-08-10,10086,2.0,7.0,0.0
+2011-08-11,10391,3.0,7.0,0.0
+2011-08-12,9614,4.0,7.0,0.0
+2011-08-13,6835,5.0,7.0,0.0
+2011-08-14,6912,6.0,7.0,0.0
+2011-08-15,10075,0.0,7.0,0.0
+2011-08-16,10949,1.0,7.0,0.0
+2011-08-17,11041,2.0,7.0,0.0
+2011-08-18,10742,3.0,7.0,0.0
+2011-08-19,10146,4.0,7.0,0.0
+2011-08-20,6424,5.0,7.0,0.0
+2011-08-21,7248,6.0,7.0,0.0
+2011-08-22,10650,0.0,7.0,0.0
+2011-08-23,11171,1.0,7.0,0.0
+2011-08-24,11385,2.0,7.0,0.0
+2011-08-25,10968,3.0,7.0,0.0
+2011-08-26,10179,4.0,7.0,0.0
+2011-08-27,7129,5.0,7.0,0.0
+2011-08-28,7341,6.0,7.0,0.0
+2011-08-29,10953,0.0,7.0,0.0
+2011-08-30,11251,1.0,7.0,0.0
+2011-08-31,11103,2.0,7.0,0.0
+2011-09-01,11120,3.0,8.0,0.0
+2011-09-02,10610,4.0,8.0,0.0
+2011-09-03,7280,5.0,8.0,0.0
+2011-09-04,7798,6.0,8.0,0.0
+2011-09-05,10391,0.0,8.0,1.0
+2011-09-06,11625,1.0,8.0,0.0
+2011-09-07,11869,2.0,8.0,0.0
+2011-09-08,11653,3.0,8.0,0.0
+2011-09-09,10962,4.0,8.0,0.0
+2011-09-10,7616,5.0,8.0,0.0
+2011-09-11,8209,6.0,8.0,0.0
+2011-09-12,11410,0.0,8.0,0.0
+2011-09-13,12278,1.0,8.0,0.0
+2011-09-14,12162,2.0,8.0,0.0
+2011-09-15,11739,3.0,8.0,0.0
+2011-09-16,11476,4.0,8.0,0.0
+2011-09-17,7297,5.0,8.0,0.0
+2011-09-18,8467,6.0,8.0,0.0
+2011-09-19,11276,0.0,8.0,0.0
+2011-09-20,11934,1.0,8.0,0.0
+2011-09-21,12059,2.0,8.0,0.0
+2011-09-22,12279,3.0,8.0,0.0
+2011-09-23,11209,4.0,8.0,0.0
+2011-09-24,7928,5.0,8.0,0.0
+2011-09-25,8584,6.0,8.0,0.0
+2011-09-26,12586,0.0,8.0,0.0
+2011-09-27,13016,1.0,8.0,0.0
+2011-09-28,12805,2.0,8.0,0.0
+2011-09-29,12525,3.0,8.0,0.0
+2011-09-30,11612,4.0,8.0,0.0
+2011-10-01,7829,5.0,9.0,0.0
+2011-10-02,8493,6.0,9.0,0.0
+2011-10-03,11934,0.0,9.0,0.0
+2011-10-04,12469,1.0,9.0,0.0
+2011-10-05,12576,2.0,9.0,0.0
+2011-10-06,12347,3.0,9.0,0.0
+2011-10-07,11916,4.0,9.0,0.0
+2011-10-08,8281,5.0,9.0,0.0
+2011-10-09,8830,6.0,9.0,0.0
+2011-10-10,12618,0.0,9.0,1.0
+2011-10-11,13105,1.0,9.0,0.0
+2011-10-12,12897,2.0,9.0,0.0
+2011-10-13,12674,3.0,9.0,0.0
+2011-10-14,11783,4.0,9.0,0.0
+2011-10-15,8104,5.0,9.0,0.0
+2011-10-16,8805,6.0,9.0,0.0
+2011-10-17,12899,0.0,9.0,0.0
+2011-10-18,13196,1.0,9.0,0.0
+2011-10-19,13200,2.0,9.0,0.0
+2011-10-20,13142,3.0,9.0,0.0
+2011-10-21,12269,4.0,9.0,0.0
+2011-10-22,8506,5.0,9.0,0.0
+2011-10-23,9133,6.0,9.0,0.0
+2011-10-24,13230,0.0,9.0,0.0
+2011-10-25,13364,1.0,9.0,0.0
+2011-10-26,13443,2.0,9.0,0.0
+2011-10-27,11080,3.0,9.0,0.0
+2011-10-28,10718,4.0,9.0,0.0
+2011-10-29,7997,5.0,9.0,0.0
+2011-10-30,8613,6.0,9.0,0.0
+2011-10-31,12319,0.0,9.0,0.0
+2011-11-01,12598,1.0,10.0,0.0
+2011-11-02,13218,2.0,10.0,0.0
+2011-11-03,12805,3.0,10.0,0.0
+2011-11-04,12883,4.0,10.0,0.0
+2011-11-05,8569,5.0,10.0,0.0
+2011-11-06,9090,6.0,10.0,0.0
+2011-11-07,11174,0.0,10.0,0.0
+2011-11-08,14122,1.0,10.0,0.0
+2011-11-09,12036,2.0,10.0,0.0
+2011-11-10,12966,3.0,10.0,0.0
+2011-11-11,12005,4.0,10.0,1.0
+2011-11-12,8419,5.0,10.0,0.0
+2011-11-13,9036,6.0,10.0,0.0
+2011-11-14,12804,0.0,10.0,0.0
+2011-11-15,13378,1.0,10.0,0.0
+2011-11-16,12693,2.0,10.0,0.0
+2011-11-17,13360,3.0,10.0,0.0
+2011-11-18,11744,4.0,10.0,0.0
+2011-11-19,8190,5.0,10.0,0.0
+2011-11-20,9690,6.0,10.0,0.0
+2011-11-21,12145,0.0,10.0,0.0
+2011-11-22,13212,1.0,10.0,0.0
+2011-11-23,13477,2.0,10.0,0.0
+2011-11-24,12085,3.0,10.0,1.0
+2011-11-25,10505,4.0,10.0,0.0
+2011-11-26,8705,5.0,10.0,0.0
+2011-11-27,9648,6.0,10.0,0.0
+2011-11-28,13613,0.0,10.0,0.0
+2011-11-29,14272,1.0,10.0,0.0
+2011-11-30,13957,2.0,10.0,0.0
+2011-12-01,14827,3.0,11.0,0.0
+2011-12-02,13591,4.0,11.0,0.0
+2011-12-03,9827,5.0,11.0,0.0
+2011-12-04,10540,6.0,11.0,0.0
+2011-12-05,14286,0.0,11.0,0.0
+2011-12-06,14420,1.0,11.0,0.0
+2011-12-07,13800,2.0,11.0,0.0
+2011-12-08,13077,3.0,11.0,0.0
+2011-12-09,13409,4.0,11.0,0.0
+2011-12-10,9537,5.0,11.0,0.0
+2011-12-11,9686,6.0,11.0,0.0
+2011-12-12,14003,0.0,11.0,0.0
+2011-12-13,13616,1.0,11.0,0.0
+2011-12-14,13695,2.0,11.0,0.0
+2011-12-15,13702,3.0,11.0,0.0
+2011-12-16,13328,4.0,11.0,0.0
+2011-12-17,8779,5.0,11.0,0.0
+2011-12-18,9541,6.0,11.0,0.0
+2011-12-19,13250,0.0,11.0,0.0
+2011-12-20,12924,1.0,11.0,0.0
+2011-12-21,12238,2.0,11.0,0.0
+2011-12-22,11812,3.0,11.0,0.0
+2011-12-23,10407,4.0,11.0,0.0
+2011-12-24,6600,5.0,11.0,0.0
+2011-12-25,5670,6.0,11.0,0.0
+2011-12-26,7446,0.0,11.0,1.0
+2011-12-27,9742,1.0,11.0,0.0
+2011-12-28,10019,2.0,11.0,0.0
+2011-12-29,10927,3.0,11.0,0.0
+2011-12-30,10146,4.0,11.0,0.0
+2012-01-01,6587,6.0,0.0,0.0
+2012-01-02,10254,0.0,0.0,1.0
+2012-01-03,12412,1.0,0.0,0.0
+2012-01-04,11806,2.0,0.0,0.0
+2012-01-05,13030,3.0,0.0,0.0
+2012-01-06,13081,4.0,0.0,0.0
+2012-01-07,9688,5.0,0.0,0.0
+2012-01-08,9682,6.0,0.0,0.0
+2012-01-09,12389,0.0,0.0,0.0
+2012-01-10,12888,1.0,0.0,0.0
+2012-01-11,14916,2.0,0.0,0.0
+2012-01-12,13966,3.0,0.0,0.0
+2012-01-13,13629,4.0,0.0,0.0
+2012-01-14,9862,5.0,0.0,0.0
+2012-01-15,10764,6.0,0.0,0.0
+2012-01-16,14066,0.0,0.0,1.0
+2012-01-17,14636,1.0,0.0,0.0
+2012-01-18,14308,2.0,0.0,0.0
+2012-01-19,14301,3.0,0.0,0.0
+2012-01-20,13525,4.0,0.0,0.0
+2012-01-21,10410,5.0,0.0,0.0
+2012-01-22,10384,6.0,0.0,0.0
+2012-01-23,14114,0.0,0.0,0.0
+2012-01-24,14996,1.0,0.0,0.0
+2012-01-25,14904,2.0,0.0,0.0
+2012-01-26,14957,3.0,0.0,0.0
+2012-01-27,15145,4.0,0.0,0.0
+2012-01-28,11182,5.0,0.0,0.0
+2012-01-29,11845,6.0,0.0,0.0
+2012-01-30,15747,0.0,0.0,0.0
+2012-01-31,16974,1.0,0.0,0.0
+2012-02-01,16410,2.0,1.0,0.0
+2012-02-02,15344,3.0,1.0,0.0
+2012-02-03,15275,4.0,1.0,0.0
+2012-02-04,10634,5.0,1.0,0.0
+2012-02-05,11996,6.0,1.0,0.0
+2012-02-06,13976,0.0,1.0,0.0
+2012-02-07,14838,1.0,1.0,0.0
+2012-02-08,15306,2.0,1.0,0.0
+2012-02-09,15598,3.0,1.0,0.0
+2012-02-10,14349,4.0,1.0,0.0
+2012-02-11,11061,5.0,1.0,0.0
+2012-02-12,12209,6.0,1.0,0.0
+2012-02-13,13869,0.0,1.0,0.0
+2012-02-14,15581,1.0,1.0,0.0
+2012-02-15,13850,2.0,1.0,0.0
+2012-02-16,15864,3.0,1.0,0.0
+2012-02-17,15855,4.0,1.0,0.0
+2012-02-18,11506,5.0,1.0,0.0
+2012-02-19,12713,6.0,1.0,0.0
+2012-02-20,15871,0.0,1.0,1.0
+2012-02-21,18141,1.0,1.0,0.0
+2012-02-22,18658,2.0,1.0,0.0
+2012-02-23,18336,3.0,1.0,0.0
+2012-02-24,17493,4.0,1.0,0.0
+2012-02-25,13047,5.0,1.0,0.0
+2012-02-26,13470,6.0,1.0,0.0
+2012-02-27,18588,0.0,1.0,0.0
+2012-02-28,19337,1.0,1.0,0.0
+2012-02-29,18919,2.0,1.0,0.0
+2012-03-01,16831,3.0,2.0,0.0
+2012-03-02,16858,4.0,2.0,0.0
+2012-03-03,12768,5.0,2.0,0.0
+2012-03-04,11378,6.0,2.0,0.0
+2012-03-05,17247,0.0,2.0,0.0
+2012-03-06,19299,1.0,2.0,0.0
+2012-03-07,19070,2.0,2.0,0.0
+2012-03-08,18345,3.0,2.0,0.0
+2012-03-09,17563,4.0,2.0,0.0
+2012-03-10,4558,5.0,2.0,0.0
+2012-03-11,11403,6.0,2.0,0.0
+2012-03-12,19012,0.0,2.0,0.0
+2012-03-13,19453,1.0,2.0,0.0
+2012-03-14,18612,2.0,2.0,0.0
+2012-03-15,18516,3.0,2.0,0.0
+2012-03-16,17712,4.0,2.0,0.0
+2012-03-17,12388,5.0,2.0,0.0
+2012-03-18,13136,6.0,2.0,0.0
+2012-03-19,19017,0.0,2.0,0.0
+2012-03-20,19748,1.0,2.0,0.0
+2012-03-21,19332,2.0,2.0,0.0
+2012-03-22,19193,3.0,2.0,0.0
+2012-03-23,17920,4.0,2.0,0.0
+2012-03-24,12753,5.0,2.0,0.0
+2012-03-25,13249,6.0,2.0,0.0
+2012-03-26,19124,0.0,2.0,0.0
+2012-03-27,19509,1.0,2.0,0.0
+2012-03-28,19821,2.0,2.0,0.0
+2012-03-29,19472,3.0,2.0,0.0
+2012-03-30,18427,4.0,2.0,0.0
+2012-03-31,13115,5.0,2.0,0.0
+2012-04-01,13515,6.0,3.0,0.0
+2012-04-02,18399,0.0,3.0,0.0
+2012-04-03,19605,1.0,3.0,0.0
+2012-04-04,19252,2.0,3.0,0.0
+2012-04-05,18543,3.0,3.0,0.0
+2012-04-06,16503,4.0,3.0,0.0
+2012-04-07,12460,5.0,3.0,0.0
+2012-04-08,12448,6.0,3.0,0.0
+2012-04-09,17445,0.0,3.0,0.0
+2012-04-10,19932,1.0,3.0,0.0
+2012-04-11,20228,2.0,3.0,0.0
+2012-04-12,19756,3.0,3.0,0.0
+2012-04-13,18782,4.0,3.0,0.0
+2012-04-14,13467,5.0,3.0,0.0
+2012-04-15,14327,6.0,3.0,0.0
+2012-04-16,20054,0.0,3.0,0.0
+2012-04-17,20519,1.0,3.0,0.0
+2012-04-18,20550,2.0,3.0,0.0
+2012-04-19,20701,3.0,3.0,0.0
+2012-04-20,19581,4.0,3.0,0.0
+2012-04-21,13836,5.0,3.0,0.0
+2012-04-22,15203,6.0,3.0,0.0
+2012-04-23,21022,0.0,3.0,0.0
+2012-04-24,21531,1.0,3.0,0.0
+2012-04-25,20843,2.0,3.0,0.0
+2012-04-26,20502,3.0,3.0,0.0
+2012-04-27,19350,4.0,3.0,0.0
+2012-04-28,13435,5.0,3.0,0.0
+2012-04-29,13740,6.0,3.0,0.0
+2012-04-30,18399,0.0,3.0,0.0
+2012-05-01,18568,1.0,4.0,0.0
+2012-05-02,20450,2.0,4.0,0.0
+2012-05-03,20346,3.0,4.0,0.0
+2012-05-04,19046,4.0,4.0,0.0
+2012-05-05,13624,5.0,4.0,0.0
+2012-05-06,14067,6.0,4.0,0.0
+2012-05-07,19843,0.0,4.0,0.0
+2012-05-08,20642,1.0,4.0,0.0
+2012-05-09,20494,2.0,4.0,0.0
+2012-05-10,20582,3.0,4.0,0.0
+2012-05-11,19082,4.0,4.0,0.0
+2012-05-12,12969,5.0,4.0,0.0
+2012-05-13,13213,6.0,4.0,0.0
+2012-05-14,19891,0.0,4.0,0.0
+2012-05-15,20429,1.0,4.0,0.0
+2012-05-16,19803,2.0,4.0,0.0
+2012-05-17,18502,3.0,4.0,0.0
+2012-05-18,17863,4.0,4.0,0.0
+2012-05-19,11967,5.0,4.0,0.0
+2012-05-20,12955,6.0,4.0,0.0
+2012-05-21,19504,0.0,4.0,0.0
+2012-05-22,21177,1.0,4.0,0.0
+2012-05-23,20755,2.0,4.0,0.0
+2012-05-24,20334,3.0,4.0,0.0
+2012-05-25,18596,4.0,4.0,0.0
+2012-05-26,11896,5.0,4.0,0.0
+2012-05-27,12267,6.0,4.0,0.0
+2012-05-28,16877,0.0,4.0,1.0
+2012-05-29,20475,1.0,4.0,0.0
+2012-05-30,20843,2.0,4.0,0.0
+2012-05-31,19725,3.0,4.0,0.0
+2012-06-01,18977,4.0,5.0,0.0
+2012-06-02,12762,5.0,5.0,0.0
+2012-06-03,13811,6.0,5.0,0.0
+2012-06-04,19603,0.0,5.0,0.0
+2012-06-05,20407,1.0,5.0,0.0
+2012-06-06,20109,2.0,5.0,0.0
+2012-06-07,20065,3.0,5.0,0.0
+2012-06-08,18897,4.0,5.0,0.0
+2012-06-09,12974,5.0,5.0,0.0
+2012-06-10,13579,6.0,5.0,0.0
+2012-06-11,19795,0.0,5.0,0.0
+2012-06-12,20766,1.0,5.0,0.0
+2012-06-13,20493,2.0,5.0,0.0
+2012-06-14,20337,3.0,5.0,0.0
+2012-06-15,18872,4.0,5.0,0.0
+2012-06-16,12563,5.0,5.0,0.0
+2012-06-17,12595,6.0,5.0,0.0
+2012-06-18,19942,0.0,5.0,0.0
+2012-06-19,20901,1.0,5.0,0.0
+2012-06-20,20460,2.0,5.0,0.0
+2012-06-21,20208,3.0,5.0,0.0
+2012-06-22,18334,4.0,5.0,0.0
+2012-06-23,12188,5.0,5.0,0.0
+2012-06-24,12974,6.0,5.0,0.0
+2012-06-25,19997,0.0,5.0,0.0
+2012-06-26,21259,1.0,5.0,0.0
+2012-06-27,20474,2.0,5.0,0.0
+2012-06-28,19885,3.0,5.0,0.0
+2012-06-29,18686,4.0,5.0,0.0
+2012-06-30,12240,5.0,5.0,0.0
+2012-07-01,12825,6.0,6.0,0.0
+2012-07-02,19514,0.0,6.0,0.0
+2012-07-03,20326,1.0,6.0,0.0
+2012-07-04,18182,2.0,6.0,1.0
+2012-07-05,19268,3.0,6.0,0.0
+2012-07-06,19182,4.0,6.0,0.0
+2012-07-07,12835,5.0,6.0,0.0
+2012-07-08,13365,6.0,6.0,0.0
+2012-07-09,20486,0.0,6.0,0.0
+2012-07-10,21706,1.0,6.0,0.0
+2012-07-11,21626,2.0,6.0,0.0
+2012-07-12,21252,3.0,6.0,0.0
+2012-07-13,20151,4.0,6.0,0.0
+2012-07-14,12797,5.0,6.0,0.0
+2012-07-15,13483,6.0,6.0,0.0
+2012-07-16,20626,0.0,6.0,0.0
+2012-07-17,21534,1.0,6.0,0.0
+2012-07-18,21272,2.0,6.0,0.0
+2012-07-19,20996,3.0,6.0,0.0
+2012-07-20,19689,4.0,6.0,0.0
+2012-07-21,12728,5.0,6.0,0.0
+2012-07-22,13196,6.0,6.0,0.0
+2012-07-23,20682,0.0,6.0,0.0
+2012-07-24,21436,1.0,6.0,0.0
+2012-07-25,20928,2.0,6.0,0.0
+2012-07-26,20682,3.0,6.0,0.0
+2012-07-27,19471,4.0,6.0,0.0
+2012-07-28,12348,5.0,6.0,0.0
+2012-07-29,13181,6.0,6.0,0.0
+2012-07-30,20472,0.0,6.0,0.0
+2012-07-31,20755,1.0,6.0,0.0
+2012-08-01,20981,2.0,7.0,0.0
+2012-08-02,20754,3.0,7.0,0.0
+2012-08-03,19474,4.0,7.0,0.0
+2012-08-04,12608,5.0,7.0,0.0
+2012-08-05,13300,6.0,7.0,0.0
+2012-08-06,20171,0.0,7.0,0.0
+2012-08-07,21381,1.0,7.0,0.0
+2012-08-08,21414,2.0,7.0,0.0
+2012-08-09,21189,3.0,7.0,0.0
+2012-08-10,20258,4.0,7.0,0.0
+2012-08-11,13126,5.0,7.0,0.0
+2012-08-12,13542,6.0,7.0,0.0
+2012-08-13,21095,0.0,7.0,0.0
+2012-08-14,21820,1.0,7.0,0.0
+2012-08-15,20412,2.0,7.0,0.0
+2012-08-16,20654,3.0,7.0,0.0
+2012-08-17,19865,4.0,7.0,0.0
+2012-08-18,13124,5.0,7.0,0.0
+2012-08-19,13500,6.0,7.0,0.0
+2012-08-20,21156,0.0,7.0,0.0
+2012-08-21,22188,1.0,7.0,0.0
+2012-08-22,22133,2.0,7.0,0.0
+2012-08-23,21972,3.0,7.0,0.0
+2012-08-24,20575,4.0,7.0,0.0
+2012-08-25,13606,5.0,7.0,0.0
+2012-08-26,14147,6.0,7.0,0.0
+2012-08-27,21513,0.0,7.0,0.0
+2012-08-28,22396,1.0,7.0,0.0
+2012-08-29,22023,2.0,7.0,0.0
+2012-08-30,22032,3.0,7.0,0.0
+2012-08-31,20667,4.0,7.0,0.0
+2012-09-01,13193,5.0,8.0,0.0
+2012-09-02,14236,6.0,8.0,0.0
+2012-09-03,19533,0.0,8.0,1.0
+2012-09-04,22529,1.0,8.0,0.0
+2012-09-05,23006,2.0,8.0,0.0
+2012-09-06,22463,3.0,8.0,0.0
+2012-09-07,21547,4.0,8.0,0.0
+2012-09-08,14061,5.0,8.0,0.0
+2012-09-09,15149,6.0,8.0,0.0
+2012-09-10,22730,0.0,8.0,0.0
+2012-09-11,23336,1.0,8.0,0.0
+2012-09-12,23521,2.0,8.0,0.0
+2012-09-13,23435,3.0,8.0,0.0
+2012-09-14,21632,4.0,8.0,0.0
+2012-09-15,14370,5.0,8.0,0.0
+2012-09-16,15122,6.0,8.0,0.0
+2012-09-17,23351,0.0,8.0,0.0
+2012-09-18,24066,1.0,8.0,0.0
+2012-09-19,23742,2.0,8.0,0.0
+2012-09-20,23585,3.0,8.0,0.0
+2012-09-21,22157,4.0,8.0,0.0
+2012-09-22,14539,5.0,8.0,0.0
+2012-09-23,15735,6.0,8.0,0.0
+2012-09-24,23613,0.0,8.0,0.0
+2012-09-25,24315,1.0,8.0,0.0
+2012-09-26,24513,2.0,8.0,0.0
+2012-09-27,23950,3.0,8.0,0.0
+2012-09-28,22489,4.0,8.0,0.0
+2012-09-29,15130,5.0,8.0,0.0
+2012-09-30,15516,6.0,8.0,0.0
+2012-10-01,22938,0.0,9.0,0.0
+2012-10-02,23758,1.0,9.0,0.0
+2012-10-03,24048,2.0,9.0,0.0
+2012-10-04,23651,3.0,9.0,0.0
+2012-10-05,22488,4.0,9.0,0.0
+2012-10-06,15261,5.0,9.0,0.0
+2012-10-07,16074,6.0,9.0,0.0
+2012-10-08,24300,0.0,9.0,1.0
+2012-10-09,26112,1.0,9.0,0.0
+2012-10-10,26118,2.0,9.0,0.0
+2012-10-11,25481,3.0,9.0,0.0
+2012-10-12,23749,4.0,9.0,0.0
+2012-10-13,16161,5.0,9.0,0.0
+2012-10-14,17196,6.0,9.0,0.0
+2012-10-15,25711,0.0,9.0,0.0
+2012-10-16,26368,1.0,9.0,0.0
+2012-10-17,26436,2.0,9.0,0.0
+2012-10-18,25588,3.0,9.0,0.0
+2012-10-19,24120,4.0,9.0,0.0
+2012-10-20,16546,5.0,9.0,0.0
+2012-10-21,17939,6.0,9.0,0.0
+2012-10-22,26790,0.0,9.0,0.0
+2012-10-23,26904,1.0,9.0,0.0
+2012-10-24,27135,2.0,9.0,0.0
+2012-10-25,26631,3.0,9.0,0.0
+2012-10-26,24735,4.0,9.0,0.0
+2012-10-27,16414,5.0,9.0,0.0
+2012-10-28,17832,6.0,9.0,0.0
+2012-10-29,26382,0.0,9.0,0.0
+2012-10-30,27051,1.0,9.0,0.0
+2012-10-31,26630,2.0,9.0,0.0
+2012-11-01,25001,3.0,10.0,0.0
+2012-11-02,24505,4.0,10.0,0.0
+2012-11-03,17411,5.0,10.0,0.0
+2012-11-04,18421,6.0,10.0,0.0
+2012-11-05,27468,0.0,10.0,0.0
+2012-11-06,28425,1.0,10.0,0.0
+2012-11-07,27405,2.0,10.0,0.0
+2012-11-08,28017,3.0,10.0,0.0
+2012-11-09,26332,4.0,10.0,0.0
+2012-11-10,18246,5.0,10.0,0.0
+2012-11-11,19133,6.0,10.0,0.0
+2012-11-12,27814,0.0,10.0,1.0
+2012-11-13,28922,1.0,10.0,0.0
+2012-11-14,28695,2.0,10.0,0.0
+2012-11-15,28078,3.0,10.0,0.0
+2012-11-16,26404,4.0,10.0,0.0
+2012-11-17,18254,5.0,10.0,0.0
+2012-11-18,19573,6.0,10.0,0.0
+2012-11-19,28486,0.0,10.0,0.0
+2012-11-20,28976,1.0,10.0,0.0
+2012-11-21,28161,2.0,10.0,0.0
+2012-11-22,24228,3.0,10.0,1.0
+2012-11-23,22550,4.0,10.0,0.0
+2012-11-24,17484,5.0,10.0,0.0
+2012-11-25,19188,6.0,10.0,0.0
+2012-11-26,28974,0.0,10.0,0.0
+2012-11-27,29963,1.0,10.0,0.0
+2012-11-28,30244,2.0,10.0,0.0
+2012-11-29,29538,3.0,10.0,0.0
+2012-11-30,26786,4.0,10.0,0.0
+2012-12-01,19253,5.0,11.0,0.0
+2012-12-02,20778,6.0,11.0,0.0
+2012-12-03,30026,0.0,11.0,0.0
+2012-12-04,30295,1.0,11.0,0.0
+2012-12-05,30105,2.0,11.0,0.0
+2012-12-06,29559,3.0,11.0,0.0
+2012-12-07,26613,4.0,11.0,0.0
+2012-12-08,18467,5.0,11.0,0.0
+2012-12-09,20055,6.0,11.0,0.0
+2012-12-10,28579,0.0,11.0,0.0
+2012-12-11,29642,1.0,11.0,0.0
+2012-12-12,29168,2.0,11.0,0.0
+2012-12-13,28652,3.0,11.0,0.0
+2012-12-14,26568,4.0,11.0,0.0
+2012-12-15,17788,5.0,11.0,0.0
+2012-12-16,18785,6.0,11.0,0.0
+2012-12-17,27496,0.0,11.0,0.0
+2012-12-18,27723,1.0,11.0,0.0
+2012-12-19,27055,2.0,11.0,0.0
+2012-12-20,26013,3.0,11.0,0.0
+2012-12-21,23140,4.0,11.0,0.0
+2012-12-22,15245,5.0,11.0,0.0
+2012-12-23,14097,6.0,11.0,0.0
+2012-12-24,16373,0.0,11.0,0.0
+2012-12-25,13596,1.0,11.0,1.0
+2012-12-26,17465,2.0,11.0,0.0
+2012-12-27,20445,3.0,11.0,0.0
+2012-12-28,20120,4.0,11.0,0.0
+2012-12-29,16407,5.0,11.0,0.0
+2012-12-30,15777,6.0,11.0,0.0
+2012-12-31,6200,0.0,11.0,0.0
+2013-01-01,11208,1.0,0.0,1.0
+2013-01-02,22522,2.0,0.0,0.0
+2013-01-03,24859,3.0,0.0,0.0
+2013-01-04,25302,4.0,0.0,0.0
+2013-01-05,19114,5.0,0.0,0.0
+2013-01-06,19650,6.0,0.0,0.0
+2013-01-07,27504,0.0,0.0,0.0
+2013-01-08,29375,1.0,0.0,0.0
+2013-01-09,29679,2.0,0.0,0.0
+2013-01-10,29661,3.0,0.0,0.0
+2013-01-11,28997,4.0,0.0,0.0
+2013-01-12,19920,5.0,0.0,0.0
+2013-01-13,21301,6.0,0.0,0.0
+2013-01-14,30089,0.0,0.0,0.0
+2013-01-15,30936,1.0,0.0,0.0
+2013-01-16,31416,2.0,0.0,0.0
+2013-01-17,30992,3.0,0.0,0.0
+2013-01-18,29420,4.0,0.0,0.0
+2013-01-19,20790,5.0,0.0,0.0
+2013-01-20,21897,6.0,0.0,0.0
+2013-01-21,29606,0.0,0.0,1.0
+2013-01-22,31573,1.0,0.0,0.0
+2013-01-23,32344,2.0,0.0,0.0
+2013-01-24,32485,3.0,0.0,0.0
+2013-01-25,30793,4.0,0.0,0.0
+2013-01-26,21917,5.0,0.0,0.0
+2013-01-27,23032,6.0,0.0,0.0
+2013-01-28,31946,0.0,0.0,0.0
+2013-01-29,33487,1.0,0.0,0.0
+2013-01-30,33192,2.0,0.0,0.0
+2013-01-31,32722,3.0,0.0,0.0
+2013-02-01,30716,4.0,1.0,0.0
+2013-02-02,21484,5.0,1.0,0.0
+2013-02-03,22962,6.0,1.0,0.0
+2013-02-04,31284,0.0,1.0,0.0
+2013-02-05,33106,1.0,1.0,0.0
+2013-02-06,32976,2.0,1.0,0.0
+2013-02-07,32429,3.0,1.0,0.0
+2013-02-08,30524,4.0,1.0,0.0
+2013-02-09,21085,5.0,1.0,0.0
+2013-02-10,22281,6.0,1.0,0.0
+2013-02-11,30989,0.0,1.0,0.0
+2013-02-12,32543,1.0,1.0,0.0
+2013-02-13,31854,2.0,1.0,0.0
+2013-02-14,30875,3.0,1.0,0.0
+2013-02-15,29531,4.0,1.0,0.0
+2013-02-16,22299,5.0,1.0,0.0
+2013-02-17,23941,6.0,1.0,0.0
+2013-02-18,33106,0.0,1.0,1.0
+2013-02-19,35274,1.0,1.0,0.0
+2013-02-20,35265,2.0,1.0,0.0
+2013-02-21,34535,3.0,1.0,0.0
+2013-02-22,33009,4.0,1.0,0.0
+2013-02-23,23466,5.0,1.0,0.0
+2013-02-24,24903,6.0,1.0,0.0
+2013-02-25,35081,0.0,1.0,0.0
+2013-02-26,36143,1.0,1.0,0.0
+2013-02-27,35992,2.0,1.0,0.0
+2013-02-28,35284,3.0,1.0,0.0
+2013-03-01,33063,4.0,2.0,0.0
+2013-03-02,23944,5.0,2.0,0.0
+2013-03-03,25119,6.0,2.0,0.0
+2013-03-04,35777,0.0,2.0,0.0
+2013-03-05,36559,1.0,2.0,0.0
+2013-03-06,35998,2.0,2.0,0.0
+2013-03-07,35682,3.0,2.0,0.0
+2013-03-08,33619,4.0,2.0,0.0
+2013-03-09,23860,5.0,2.0,0.0
+2013-03-10,25293,6.0,2.0,0.0
+2013-03-11,36253,0.0,2.0,0.0
+2013-03-12,37391,1.0,2.0,0.0
+2013-03-13,37132,2.0,2.0,0.0
+2013-03-14,36044,3.0,2.0,0.0
+2013-03-15,34297,4.0,2.0,0.0
+2013-03-16,24005,5.0,2.0,0.0
+2013-03-17,25836,6.0,2.0,0.0
+2013-03-18,36614,0.0,2.0,0.0
+2013-03-19,38229,1.0,2.0,0.0
+2013-03-20,38085,2.0,2.0,0.0
+2013-03-21,37290,3.0,2.0,0.0
+2013-03-22,35173,4.0,2.0,0.0
+2013-03-23,23732,5.0,2.0,0.0
+2013-03-24,26573,6.0,2.0,0.0
+2013-03-25,38095,0.0,2.0,0.0
+2013-03-26,38959,1.0,2.0,0.0
+2013-03-27,36841,2.0,2.0,0.0
+2013-03-28,35861,3.0,2.0,0.0
+2013-03-29,31458,4.0,2.0,0.0
+2013-03-30,23375,5.0,2.0,0.0
+2013-03-31,23229,6.0,2.0,0.0
+2013-04-01,32188,0.0,3.0,0.0
+2013-04-02,37574,1.0,3.0,0.0
+2013-04-03,37688,2.0,3.0,0.0
+2013-04-04,36662,3.0,3.0,0.0
+2013-04-05,35247,4.0,3.0,0.0
+2013-04-06,25579,5.0,3.0,0.0
+2013-04-07,28152,6.0,3.0,0.0
+2013-04-08,38770,0.0,3.0,0.0
+2013-04-09,39537,1.0,3.0,0.0
+2013-04-10,39099,2.0,3.0,0.0
+2013-04-11,38970,3.0,3.0,0.0
+2013-04-12,37006,4.0,3.0,0.0
+2013-04-13,25241,5.0,3.0,0.0
+2013-04-14,26604,6.0,3.0,0.0
+2013-04-15,38046,0.0,3.0,0.0
+2013-04-16,39572,1.0,3.0,0.0
+2013-04-17,39873,2.0,3.0,0.0
+2013-04-18,39338,3.0,3.0,0.0
+2013-04-19,36343,4.0,3.0,0.0
+2013-04-20,25210,5.0,3.0,0.0
+2013-04-21,26877,6.0,3.0,0.0
+2013-04-22,39663,0.0,3.0,0.0
+2013-04-23,40706,1.0,3.0,0.0
+2013-04-24,39844,2.0,3.0,0.0
+2013-04-25,38703,3.0,3.0,0.0
+2013-04-26,35427,4.0,3.0,0.0
+2013-04-27,26071,5.0,3.0,0.0
+2013-04-28,27388,6.0,3.0,0.0
+2013-04-29,37487,0.0,3.0,0.0
+2013-04-30,36940,1.0,3.0,0.0
+2013-05-01,33606,2.0,4.0,0.0
+2013-05-02,37390,3.0,4.0,0.0
+2013-05-03,35633,4.0,4.0,0.0
+2013-05-04,24228,5.0,4.0,0.0
+2013-05-05,24997,6.0,4.0,0.0
+2013-05-06,36749,0.0,4.0,0.0
+2013-05-07,37704,1.0,4.0,0.0
+2013-05-08,37857,2.0,4.0,0.0
+2013-05-09,35833,3.0,4.0,0.0
+2013-05-10,34646,4.0,4.0,0.0
+2013-05-11,24376,5.0,4.0,0.0
+2013-05-12,25378,6.0,4.0,0.0
+2013-05-13,38290,0.0,4.0,0.0
+2013-05-14,39639,1.0,4.0,0.0
+2013-05-15,38600,2.0,4.0,0.0
+2013-05-16,38360,3.0,4.0,0.0
+2013-05-17,35699,4.0,4.0,0.0
+2013-05-18,23617,5.0,4.0,0.0
+2013-05-19,24777,6.0,4.0,0.0
+2013-05-20,36164,0.0,4.0,0.0
+2013-05-21,38868,1.0,4.0,0.0
+2013-05-22,39343,2.0,4.0,0.0
+2013-05-23,38808,3.0,4.0,0.0
+2013-05-24,35952,4.0,4.0,0.0
+2013-05-25,23631,5.0,4.0,0.0
+2013-05-26,24617,6.0,4.0,0.0
+2013-05-27,33553,0.0,4.0,1.0
+2013-05-28,38933,1.0,4.0,0.0
+2013-05-29,39393,2.0,4.0,0.0
+2013-05-30,37654,3.0,4.0,0.0
+2013-05-31,36341,4.0,4.0,0.0
+2013-06-01,23781,5.0,5.0,0.0
+2013-06-02,25611,6.0,5.0,0.0
+2013-06-03,38377,0.0,5.0,0.0
+2013-06-04,39508,1.0,5.0,0.0
+2013-06-05,38949,2.0,5.0,0.0
+2013-06-06,38397,3.0,5.0,0.0
+2013-06-07,36512,4.0,5.0,0.0
+2013-06-08,24453,5.0,5.0,0.0
+2013-06-09,25513,6.0,5.0,0.0
+2013-06-10,35931,0.0,5.0,0.0
+2013-06-11,36456,1.0,5.0,0.0
+2013-06-12,36649,2.0,5.0,0.0
+2013-06-13,37838,3.0,5.0,0.0
+2013-06-14,35372,4.0,5.0,0.0
+2013-06-15,22633,5.0,5.0,0.0
+2013-06-16,23632,6.0,5.0,0.0
+2013-06-17,36996,0.0,5.0,0.0
+2013-06-18,38905,1.0,5.0,0.0
+2013-06-19,38128,2.0,5.0,0.0
+2013-06-20,37205,3.0,5.0,0.0
+2013-06-21,34488,4.0,5.0,0.0
+2013-06-22,22328,5.0,5.0,0.0
+2013-06-23,24116,6.0,5.0,0.0
+2013-06-24,37051,0.0,5.0,0.0
+2013-06-25,38924,1.0,5.0,0.0
+2013-06-26,38481,2.0,5.0,0.0
+2013-06-27,37527,3.0,5.0,0.0
+2013-06-28,35081,4.0,5.0,0.0
+2013-06-29,22609,5.0,5.0,0.0
+2013-06-30,23535,6.0,5.0,0.0
+2013-07-01,35825,0.0,6.0,0.0
+2013-07-02,37818,1.0,6.0,0.0
+2013-07-03,37797,2.0,6.0,0.0
+2013-07-04,33322,3.0,6.0,1.0
+2013-07-05,32777,4.0,6.0,0.0
+2013-07-06,22675,5.0,6.0,0.0
+2013-07-07,24558,6.0,6.0,0.0
+2013-07-08,38713,0.0,6.0,0.0
+2013-07-09,40620,1.0,6.0,0.0
+2013-07-10,42070,2.0,6.0,0.0
+2013-07-11,41020,3.0,6.0,0.0
+2013-07-12,37346,4.0,6.0,0.0
+2013-07-13,23190,5.0,6.0,0.0
+2013-07-14,24518,6.0,6.0,0.0
+2013-07-15,38390,0.0,6.0,0.0
+2013-07-16,40149,1.0,6.0,0.0
+2013-07-17,40568,2.0,6.0,0.0
+2013-07-18,40213,3.0,6.0,0.0
+2013-07-19,38293,4.0,6.0,0.0
+2013-07-20,24090,5.0,6.0,0.0
+2013-07-21,24762,6.0,6.0,0.0
+2013-07-22,39038,0.0,6.0,0.0
+2013-07-23,40878,1.0,6.0,0.0
+2013-07-24,39600,2.0,6.0,0.0
+2013-07-25,38883,3.0,6.0,0.0
+2013-07-26,36596,4.0,6.0,0.0
+2013-07-27,23424,5.0,6.0,0.0
+2013-07-28,24364,6.0,6.0,0.0
+2013-07-29,37997,0.0,6.0,0.0
+2013-07-30,39569,1.0,6.0,0.0
+2013-07-31,39220,2.0,6.0,0.0
+2013-08-01,38151,3.0,7.0,0.0
+2013-08-02,35991,4.0,7.0,0.0
+2013-08-03,23359,5.0,7.0,0.0
+2013-08-04,24392,6.0,7.0,0.0
+2013-08-05,37880,0.0,7.0,0.0
+2013-08-06,39787,1.0,7.0,0.0
+2013-08-07,40562,2.0,7.0,0.0
+2013-08-08,39204,3.0,7.0,0.0
+2013-08-09,36126,4.0,7.0,0.0
+2013-08-10,23322,5.0,7.0,0.0
+2013-08-11,24528,6.0,7.0,0.0
+2013-08-12,37294,0.0,7.0,0.0
+2013-08-13,38848,1.0,7.0,0.0
+2013-08-14,38772,2.0,7.0,0.0
+2013-08-15,34626,3.0,7.0,0.0
+2013-08-16,34857,4.0,7.0,0.0
+2013-08-17,23932,5.0,7.0,0.0
+2013-08-18,24779,6.0,7.0,0.0
+2013-08-19,37843,0.0,7.0,0.0
+2013-08-20,38890,1.0,7.0,0.0
+2013-08-21,39298,2.0,7.0,0.0
+2013-08-22,38649,3.0,7.0,0.0
+2013-08-23,36410,4.0,7.0,0.0
+2013-08-24,23893,5.0,7.0,0.0
+2013-08-25,25183,6.0,7.0,0.0
+2013-08-26,37745,0.0,7.0,0.0
+2013-08-27,40279,1.0,7.0,0.0
+2013-08-28,40041,2.0,7.0,0.0
+2013-08-29,39814,3.0,7.0,0.0
+2013-08-30,36737,4.0,7.0,0.0
+2013-08-31,23496,5.0,7.0,0.0
+2013-09-01,24887,6.0,8.0,0.0
+2013-09-02,34734,0.0,8.0,1.0
+2013-09-03,40062,1.0,8.0,0.0
+2013-09-04,40547,2.0,8.0,0.0
+2013-09-05,39817,3.0,8.0,0.0
+2013-09-06,36795,4.0,8.0,0.0
+2013-09-07,25041,5.0,8.0,0.0
+2013-09-08,26867,6.0,8.0,0.0
+2013-09-09,40162,0.0,8.0,0.0
+2013-09-10,41282,1.0,8.0,0.0
+2013-09-11,41776,2.0,8.0,0.0
+2013-09-12,40797,3.0,8.0,0.0
+2013-09-13,39038,4.0,8.0,0.0
+2013-09-14,25547,5.0,8.0,0.0
+2013-09-15,27248,6.0,8.0,0.0
+2013-09-16,41174,0.0,8.0,0.0
+2013-09-17,41800,1.0,8.0,0.0
+2013-09-18,40673,2.0,8.0,0.0
+2013-09-19,35777,3.0,8.0,0.0
+2013-09-20,37267,4.0,8.0,0.0
+2013-09-21,25963,5.0,8.0,0.0
+2013-09-22,28105,6.0,8.0,0.0
+2013-09-23,40921,0.0,8.0,0.0
+2013-09-24,42979,1.0,8.0,0.0
+2013-09-25,42683,2.0,8.0,0.0
+2013-09-26,42336,3.0,8.0,0.0
+2013-09-27,39720,4.0,8.0,0.0
+2013-09-28,26060,5.0,8.0,0.0
+2013-09-29,29404,6.0,8.0,0.0
+2013-09-30,41805,0.0,8.0,0.0
+2013-10-01,41029,1.0,9.0,0.0
+2013-10-02,41378,2.0,9.0,0.0
+2013-10-03,40288,3.0,9.0,0.0
+2013-10-04,38966,4.0,9.0,0.0
+2013-10-05,26606,5.0,9.0,0.0
+2013-10-06,28694,6.0,9.0,0.0
+2013-10-07,42983,0.0,9.0,0.0
+2013-10-08,45969,1.0,9.0,0.0
+2013-10-09,45673,2.0,9.0,0.0
+2013-10-10,44823,3.0,9.0,0.0
+2013-10-11,42240,4.0,9.0,0.0
+2013-10-12,28719,5.0,9.0,0.0
+2013-10-13,29129,6.0,9.0,0.0
+2013-10-14,42706,0.0,9.0,1.0
+2013-10-15,45380,1.0,9.0,0.0
+2013-10-16,46301,2.0,9.0,0.0
+2013-10-17,45649,3.0,9.0,0.0
+2013-10-18,42778,4.0,9.0,0.0
+2013-10-19,28774,5.0,9.0,0.0
+2013-10-20,31296,6.0,9.0,0.0
+2013-10-21,45838,0.0,9.0,0.0
+2013-10-22,46948,1.0,9.0,0.0
+2013-10-23,46510,2.0,9.0,0.0
+2013-10-24,44514,3.0,9.0,0.0
+2013-10-25,44395,4.0,9.0,0.0
+2013-10-26,29485,5.0,9.0,0.0
+2013-10-27,31661,6.0,9.0,0.0
+2013-10-28,46946,0.0,9.0,0.0
+2013-10-29,48500,1.0,9.0,0.0
+2013-10-30,48321,2.0,9.0,0.0
+2013-10-31,46159,3.0,9.0,0.0
+2013-11-01,41112,4.0,10.0,0.0
+2013-11-02,29827,5.0,10.0,0.0
+2013-11-03,31521,6.0,10.0,0.0
+2013-11-04,47735,0.0,10.0,0.0
+2013-11-05,49358,1.0,10.0,0.0
+2013-11-06,49622,2.0,10.0,0.0
+2013-11-07,48864,3.0,10.0,0.0
+2013-11-08,46153,4.0,10.0,0.0
+2013-11-09,31598,5.0,10.0,0.0
+2013-11-10,33505,6.0,10.0,0.0
+2013-11-11,47101,0.0,10.0,1.0
+2013-11-12,50609,1.0,10.0,0.0
+2013-11-13,48306,2.0,10.0,0.0
+2013-11-14,49673,3.0,10.0,0.0
+2013-11-15,46797,4.0,10.0,0.0
+2013-11-16,32098,5.0,10.0,0.0
+2013-11-17,34542,6.0,10.0,0.0
+2013-11-18,50981,0.0,10.0,0.0
+2013-11-19,51901,1.0,10.0,0.0
+2013-11-20,51862,2.0,10.0,0.0
+2013-11-21,51330,3.0,10.0,0.0
+2013-11-22,48100,4.0,10.0,0.0
+2013-11-23,32590,5.0,10.0,0.0
+2013-11-24,34863,6.0,10.0,0.0
+2013-11-25,49346,0.0,10.0,0.0
+2013-11-26,51549,1.0,10.0,0.0
+2013-11-27,49231,2.0,10.0,0.0
+2013-11-28,42985,3.0,10.0,1.0
+2013-11-29,39014,4.0,10.0,0.0
+2013-11-30,29927,5.0,10.0,0.0
+2013-12-01,32875,6.0,11.0,0.0
+2013-12-02,50342,0.0,11.0,0.0
+2013-12-03,52500,1.0,11.0,0.0
+2013-12-04,52398,2.0,11.0,0.0
+2013-12-05,51352,3.0,11.0,0.0
+2013-12-06,47337,4.0,11.0,0.0
+2013-12-07,32551,5.0,11.0,0.0
+2013-12-08,34756,6.0,11.0,0.0
+2013-12-09,50839,0.0,11.0,0.0
+2013-12-10,51506,1.0,11.0,0.0
+2013-12-11,50204,2.0,11.0,0.0
+2013-12-12,48640,3.0,11.0,0.0
+2013-12-13,45504,4.0,11.0,0.0
+2013-12-14,30350,5.0,11.0,0.0
+2013-12-15,32192,6.0,11.0,0.0
+2013-12-16,47571,0.0,11.0,0.0
+2013-12-17,48189,1.0,11.0,0.0
+2013-12-18,46983,2.0,11.0,0.0
+2013-12-19,44986,3.0,11.0,0.0
+2013-12-20,41717,4.0,11.0,0.0
+2013-12-21,26649,5.0,11.0,0.0
+2013-12-22,26917,6.0,11.0,0.0
+2013-12-23,36144,0.0,11.0,0.0
+2013-12-24,30015,1.0,11.0,0.0
+2013-12-25,23280,2.0,11.0,1.0
+2013-12-26,29732,3.0,11.0,0.0
+2013-12-27,32334,4.0,11.0,0.0
+2013-12-28,26369,5.0,11.0,0.0
+2013-12-29,27110,6.0,11.0,0.0
+2013-12-30,35237,0.0,11.0,0.0
+2013-12-31,12471,1.0,11.0,0.0
+2014-01-01,19103,2.0,0.0,1.0
+2014-01-02,38454,3.0,0.0,0.0
+2014-01-03,38788,4.0,0.0,0.0
+2014-01-04,31132,5.0,0.0,0.0
+2014-01-05,32334,6.0,0.0,0.0
+2014-01-06,44539,0.0,0.0,0.0
+2014-01-07,47256,1.0,0.0,0.0
+2014-01-08,47472,2.0,0.0,0.0
+2014-01-09,48662,3.0,0.0,0.0
+2014-01-10,46462,4.0,0.0,0.0
+2014-01-11,32376,5.0,0.0,0.0
+2014-01-12,34043,6.0,0.0,0.0
+2014-01-13,49000,0.0,0.0,0.0
+2014-01-14,50766,1.0,0.0,0.0
+2014-01-15,51247,2.0,0.0,0.0
+2014-01-16,51321,3.0,0.0,0.0
+2014-01-17,48280,4.0,0.0,0.0
+2014-01-18,33741,5.0,0.0,0.0
+2014-01-19,35398,6.0,0.0,0.0
+2014-01-20,48750,0.0,0.0,1.0
+2014-01-21,52079,1.0,0.0,0.0
+2014-01-22,52542,2.0,0.0,0.0
+2014-01-23,52376,3.0,0.0,0.0
+2014-01-24,48155,4.0,0.0,0.0
+2014-01-25,36337,5.0,0.0,0.0
+2014-01-26,38223,6.0,0.0,0.0
+2014-01-27,51032,0.0,0.0,0.0
+2014-01-28,52414,1.0,0.0,0.0
+2014-01-29,51673,2.0,0.0,0.0
+2014-01-30,50439,3.0,0.0,0.0
+2014-01-31,47161,4.0,0.0,0.0
+2014-02-01,33166,5.0,1.0,0.0
+2014-02-02,34890,6.0,1.0,0.0
+2014-02-03,47975,0.0,1.0,0.0
+2014-02-04,51265,1.0,1.0,0.0
+2014-02-05,51264,2.0,1.0,0.0
+2014-02-06,52288,3.0,1.0,0.0
+2014-02-07,50247,4.0,1.0,0.0
+2014-02-08,36698,5.0,1.0,0.0
+2014-02-09,38503,6.0,1.0,0.0
+2014-02-10,54226,0.0,1.0,0.0
+2014-02-11,56115,1.0,1.0,0.0
+2014-02-12,56224,2.0,1.0,0.0
+2014-02-13,55362,3.0,1.0,0.0
+2014-02-14,50776,4.0,1.0,0.0
+2014-02-15,35096,5.0,1.0,0.0
+2014-02-16,38108,6.0,1.0,0.0
+2014-02-17,53408,0.0,1.0,1.0
+2014-02-18,57332,1.0,1.0,0.0
+2014-02-19,56375,2.0,1.0,0.0
+2014-02-20,53624,3.0,1.0,0.0
+2014-02-21,53840,4.0,1.0,0.0
+2014-02-22,37965,5.0,1.0,0.0
+2014-02-23,38901,6.0,1.0,0.0
+2014-02-24,57056,0.0,1.0,0.0
+2014-02-25,58723,1.0,1.0,0.0
+2014-02-26,58317,2.0,1.0,0.0
+2014-02-27,58104,3.0,1.0,0.0
+2014-02-28,54417,4.0,1.0,0.0
+2014-03-01,37253,5.0,2.0,0.0
+2014-03-02,39545,6.0,2.0,0.0
+2014-03-03,56281,0.0,2.0,0.0
+2014-03-04,58275,1.0,2.0,0.0
+2014-03-05,58531,2.0,2.0,0.0
+2014-03-06,58230,3.0,2.0,0.0
+2014-03-07,54381,4.0,2.0,0.0
+2014-03-08,36908,5.0,2.0,0.0
+2014-03-09,38903,6.0,2.0,0.0
+2014-03-10,57466,0.0,2.0,0.0
+2014-03-11,58201,1.0,2.0,0.0
+2014-03-12,59508,2.0,2.0,0.0
+2014-03-13,58819,3.0,2.0,0.0
+2014-03-14,54631,4.0,2.0,0.0
+2014-03-15,37045,5.0,2.0,0.0
+2014-03-16,40071,6.0,2.0,0.0
+2014-03-17,58119,0.0,2.0,0.0
+2014-03-18,60296,1.0,2.0,0.0
+2014-03-19,60348,2.0,2.0,0.0
+2014-03-20,59653,3.0,2.0,0.0
+2014-03-21,54723,4.0,2.0,0.0
+2014-03-22,38438,5.0,2.0,0.0
+2014-03-23,41116,6.0,2.0,0.0
+2014-03-24,59413,0.0,2.0,0.0
+2014-03-25,58491,1.0,2.0,0.0
+2014-03-26,57706,2.0,2.0,0.0
+2014-03-27,59629,3.0,2.0,0.0
+2014-03-28,55961,4.0,2.0,0.0
+2014-03-29,37785,5.0,2.0,0.0
+2014-03-30,40405,6.0,2.0,0.0
+2014-03-31,59279,0.0,2.0,0.0
+2014-04-01,59904,1.0,3.0,0.0
+2014-04-02,61078,2.0,3.0,0.0
+2014-04-03,60665,3.0,3.0,0.0
+2014-04-04,56880,4.0,3.0,0.0
+2014-04-05,38088,5.0,3.0,0.0
+2014-04-06,40745,6.0,3.0,0.0
+2014-04-07,59201,0.0,3.0,0.0
+2014-04-08,62373,1.0,3.0,0.0
+2014-04-09,61447,2.0,3.0,0.0
+2014-04-10,60721,3.0,3.0,0.0
+2014-04-11,57113,4.0,3.0,0.0
+2014-04-12,38778,5.0,3.0,0.0
+2014-04-13,41754,6.0,3.0,0.0
+2014-04-14,60584,0.0,3.0,0.0
+2014-04-15,62573,1.0,3.0,0.0
+2014-04-16,61692,2.0,3.0,0.0
+2014-04-17,58954,3.0,3.0,0.0
+2014-04-18,50828,4.0,3.0,0.0
+2014-04-19,37908,5.0,3.0,0.0
+2014-04-20,37161,6.0,3.0,0.0
+2014-04-21,53971,0.0,3.0,0.0
+2014-04-22,63154,1.0,3.0,0.0
+2014-04-23,64034,2.0,3.0,0.0
+2014-04-24,63013,3.0,3.0,0.0
+2014-04-25,58866,4.0,3.0,0.0
+2014-04-26,41588,5.0,3.0,0.0
+2014-04-27,46281,6.0,3.0,0.0
+2014-04-28,62917,0.0,3.0,0.0
+2014-04-29,58880,1.0,3.0,0.0
+2014-04-30,59201,2.0,3.0,0.0
+2014-05-01,51873,3.0,4.0,0.0
+2014-05-02,53187,4.0,4.0,0.0
+2014-05-03,38524,5.0,4.0,0.0
+2014-05-04,42442,6.0,4.0,0.0
+2014-05-05,59938,0.0,4.0,0.0
+2014-05-06,63226,1.0,4.0,0.0
+2014-05-07,64056,2.0,4.0,0.0
+2014-05-08,62352,3.0,4.0,0.0
+2014-05-09,58471,4.0,4.0,0.0
+2014-05-10,40697,5.0,4.0,0.0
+2014-05-11,42929,6.0,4.0,0.0
+2014-05-12,62494,0.0,4.0,0.0
+2014-05-13,63889,1.0,4.0,0.0
+2014-05-14,63489,2.0,4.0,0.0
+2014-05-15,62615,3.0,4.0,0.0
+2014-05-16,57477,4.0,4.0,0.0
+2014-05-17,38612,5.0,4.0,0.0
+2014-05-18,41834,6.0,4.0,0.0
+2014-05-19,61093,0.0,4.0,0.0
+2014-05-20,63539,1.0,4.0,0.0
+2014-05-21,63520,2.0,4.0,0.0
+2014-05-22,62947,3.0,4.0,0.0
+2014-05-23,58949,4.0,4.0,0.0
+2014-05-24,38860,5.0,4.0,0.0
+2014-05-25,41500,6.0,4.0,0.0
+2014-05-26,54191,0.0,4.0,1.0
+2014-05-27,62110,1.0,4.0,0.0
+2014-05-28,62119,2.0,4.0,0.0
+2014-05-29,57778,3.0,4.0,0.0
+2014-05-30,55360,4.0,4.0,0.0
+2014-05-31,36956,5.0,4.0,0.0
+2014-06-01,38803,6.0,5.0,0.0
+2014-06-02,57279,0.0,5.0,0.0
+2014-06-03,61545,1.0,5.0,0.0
+2014-06-04,62143,2.0,5.0,0.0
+2014-06-05,61565,3.0,5.0,0.0
+2014-06-06,56682,4.0,5.0,0.0
+2014-06-07,37230,5.0,5.0,0.0
+2014-06-08,39439,6.0,5.0,0.0
+2014-06-09,56406,0.0,5.0,0.0
+2014-06-10,60934,1.0,5.0,0.0
+2014-06-11,61030,2.0,5.0,0.0
+2014-06-12,58531,3.0,5.0,0.0
+2014-06-13,54801,4.0,5.0,0.0
+2014-06-14,36688,5.0,5.0,0.0
+2014-06-15,38911,6.0,5.0,0.0
+2014-06-16,57628,0.0,5.0,0.0
+2014-06-17,60437,1.0,5.0,0.0
+2014-06-18,59666,2.0,5.0,0.0
+2014-06-19,58550,3.0,5.0,0.0
+2014-06-20,54734,4.0,5.0,0.0
+2014-06-21,36936,5.0,5.0,0.0
+2014-06-22,40998,6.0,5.0,0.0
+2014-06-23,57817,0.0,5.0,0.0
+2014-06-24,59898,1.0,5.0,0.0
+2014-06-25,59275,2.0,5.0,0.0
+2014-06-26,58194,3.0,5.0,0.0
+2014-06-27,54687,4.0,5.0,0.0
+2014-06-28,34376,5.0,5.0,0.0
+2014-06-29,36039,6.0,5.0,0.0
+2014-06-30,56288,0.0,5.0,0.0
+2014-07-01,57564,1.0,6.0,0.0
+2014-07-02,58226,2.0,6.0,0.0
+2014-07-03,57447,3.0,6.0,0.0
+2014-07-04,46868,4.0,6.0,1.0
+2014-07-05,31976,5.0,6.0,0.0
+2014-07-06,35625,6.0,6.0,0.0
+2014-07-07,57648,0.0,6.0,0.0
+2014-07-08,59817,1.0,6.0,0.0
+2014-07-09,58684,2.0,6.0,0.0
+2014-07-10,59610,3.0,6.0,0.0
+2014-07-11,56361,4.0,6.0,0.0
+2014-07-12,36405,5.0,6.0,0.0
+2014-07-13,37367,6.0,6.0,0.0
+2014-07-14,57220,0.0,6.0,0.0
+2014-07-15,60954,1.0,6.0,0.0
+2014-07-16,60772,2.0,6.0,0.0
+2014-07-17,58139,3.0,6.0,0.0
+2014-07-18,55605,4.0,6.0,0.0
+2014-07-19,35444,5.0,6.0,0.0
+2014-07-20,37516,6.0,6.0,0.0
+2014-07-21,58789,0.0,6.0,0.0
+2014-07-22,61115,1.0,6.0,0.0
+2014-07-23,61183,2.0,6.0,0.0
+2014-07-24,60482,3.0,6.0,0.0
+2014-07-25,56642,4.0,6.0,0.0
+2014-07-26,37052,5.0,6.0,0.0
+2014-07-27,40482,6.0,6.0,0.0
+2014-07-28,58625,0.0,6.0,0.0
+2014-07-29,60214,1.0,6.0,0.0
+2014-07-30,60244,2.0,6.0,0.0
+2014-07-31,59555,3.0,6.0,0.0
+2014-08-01,54851,4.0,7.0,0.0
+2014-08-02,34918,5.0,7.0,0.0
+2014-08-03,36852,6.0,7.0,0.0
+2014-08-04,57355,0.0,7.0,0.0
+2014-08-05,60536,1.0,7.0,0.0
+2014-08-06,60691,2.0,7.0,0.0
+2014-08-07,59387,3.0,7.0,0.0
+2014-08-08,55824,4.0,7.0,0.0
+2014-08-09,35770,5.0,7.0,0.0
+2014-08-10,38102,6.0,7.0,0.0
+2014-08-11,59054,0.0,7.0,0.0
+2014-08-12,60590,1.0,7.0,0.0
+2014-08-13,60448,2.0,7.0,0.0
+2014-08-14,58944,3.0,7.0,0.0
+2014-08-15,53160,4.0,7.0,0.0
+2014-08-16,35988,5.0,7.0,0.0
+2014-08-17,39009,6.0,7.0,0.0
+2014-08-18,59031,0.0,7.0,0.0
+2014-08-19,61664,1.0,7.0,0.0
+2014-08-20,61490,2.0,7.0,0.0
+2014-08-21,61343,3.0,7.0,0.0
+2014-08-22,58054,4.0,7.0,0.0
+2014-08-23,38573,5.0,7.0,0.0
+2014-08-24,41813,6.0,7.0,0.0
+2014-08-25,58804,0.0,7.0,0.0
+2014-08-26,61870,1.0,7.0,0.0
+2014-08-27,61716,2.0,7.0,0.0
+2014-08-28,60539,3.0,7.0,0.0
+2014-08-29,56147,4.0,7.0,0.0
+2014-08-30,36483,5.0,7.0,0.0
+2014-08-31,38402,6.0,7.0,0.0
+2014-09-01,53643,0.0,8.0,1.0
+2014-09-02,62318,1.0,8.0,0.0
+2014-09-03,63877,2.0,8.0,0.0
+2014-09-04,63233,3.0,8.0,0.0
+2014-09-05,59368,4.0,8.0,0.0
+2014-09-06,39023,5.0,8.0,0.0
+2014-09-07,40969,6.0,8.0,0.0
+2014-09-08,59558,0.0,8.0,0.0
+2014-09-09,63536,1.0,8.0,0.0
+2014-09-10,64457,2.0,8.0,0.0
+2014-09-11,64373,3.0,8.0,0.0
+2014-09-12,60704,4.0,8.0,0.0
+2014-09-13,40285,5.0,8.0,0.0
+2014-09-14,42980,6.0,8.0,0.0
+2014-09-15,63854,0.0,8.0,0.0
+2014-09-16,66603,1.0,8.0,0.0
+2014-09-17,66943,2.0,8.0,0.0
+2014-09-18,65374,3.0,8.0,0.0
+2014-09-19,61976,4.0,8.0,0.0
+2014-09-20,41540,5.0,8.0,0.0
+2014-09-21,45895,6.0,8.0,0.0
+2014-09-22,65680,0.0,8.0,0.0
+2014-09-23,65894,1.0,8.0,0.0
+2014-09-24,67516,2.0,8.0,0.0
+2014-09-25,66172,3.0,8.0,0.0
+2014-09-26,62052,4.0,8.0,0.0
+2014-09-27,40681,5.0,8.0,0.0
+2014-09-28,44507,6.0,8.0,0.0
+2014-09-29,66009,0.0,8.0,0.0
+2014-09-30,65377,1.0,8.0,0.0
+2014-10-01,64361,2.0,9.0,0.0
+2014-10-02,63192,3.0,9.0,0.0
+2014-10-03,58623,4.0,9.0,0.0
+2014-10-04,40046,5.0,9.0,0.0
+2014-10-05,42635,6.0,9.0,0.0
+2014-10-06,64289,0.0,9.0,0.0
+2014-10-07,67728,1.0,9.0,0.0
+2014-10-08,70580,2.0,9.0,0.0
+2014-10-09,68939,3.0,9.0,0.0
+2014-10-10,65565,4.0,9.0,0.0
+2014-10-11,45396,5.0,9.0,0.0
+2014-10-12,46315,6.0,9.0,0.0
+2014-10-13,68081,0.0,9.0,1.0
+2014-10-14,70462,1.0,9.0,0.0
+2014-10-15,71679,2.0,9.0,0.0
+2014-10-16,71133,3.0,9.0,0.0
+2014-10-17,66584,4.0,9.0,0.0
+2014-10-18,45259,5.0,9.0,0.0
+2014-10-19,46726,6.0,9.0,0.0
+2014-10-20,71061,0.0,9.0,0.0
+2014-10-21,74351,1.0,9.0,0.0
+2014-10-22,71496,2.0,9.0,0.0
+2014-10-23,72852,3.0,9.0,0.0
+2014-10-24,68836,4.0,9.0,0.0
+2014-10-25,46343,5.0,9.0,0.0
+2014-10-26,51704,6.0,9.0,0.0
+2014-10-27,72386,0.0,9.0,0.0
+2014-10-28,73319,1.0,9.0,0.0
+2014-10-29,71694,2.0,9.0,0.0
+2014-10-30,73188,3.0,9.0,0.0
+2014-10-31,66606,4.0,9.0,0.0
+2014-11-01,43864,5.0,10.0,0.0
+2014-11-02,48725,6.0,10.0,0.0
+2014-11-03,72901,0.0,10.0,0.0
+2014-11-04,75637,1.0,10.0,0.0
+2014-11-05,76423,2.0,10.0,0.0
+2014-11-06,74164,3.0,10.0,0.0
+2014-11-07,71186,4.0,10.0,0.0
+2014-11-08,49033,5.0,10.0,0.0
+2014-11-09,52480,6.0,10.0,0.0
+2014-11-10,74984,0.0,10.0,0.0
+2014-11-11,76113,1.0,10.0,1.0
+2014-11-12,77768,2.0,10.0,0.0
+2014-11-13,77072,3.0,10.0,0.0
+2014-11-14,72203,4.0,10.0,0.0
+2014-11-15,50149,5.0,10.0,0.0
+2014-11-16,53584,6.0,10.0,0.0
+2014-11-17,77223,0.0,10.0,0.0
+2014-11-18,79371,1.0,10.0,0.0
+2014-11-19,79472,2.0,10.0,0.0
+2014-11-20,78357,3.0,10.0,0.0
+2014-11-21,73355,4.0,10.0,0.0
+2014-11-22,50881,5.0,10.0,0.0
+2014-11-23,55522,6.0,10.0,0.0
+2014-11-24,78109,0.0,10.0,0.0
+2014-11-25,79387,1.0,10.0,0.0
+2014-11-26,76170,2.0,10.0,0.0
+2014-11-27,67321,3.0,10.0,1.0
+2014-11-28,61368,4.0,10.0,0.0
+2014-11-29,46144,5.0,10.0,0.0
+2014-11-30,51623,6.0,10.0,0.0
+2014-12-01,77869,0.0,11.0,0.0
+2014-12-02,80799,1.0,11.0,0.0
+2014-12-03,80672,2.0,11.0,0.0
+2014-12-04,78755,3.0,11.0,0.0
+2014-12-05,74423,4.0,11.0,0.0
+2014-12-06,51209,5.0,11.0,0.0
+2014-12-07,54238,6.0,11.0,0.0
+2014-12-08,77058,0.0,11.0,0.0
+2014-12-09,79147,1.0,11.0,0.0
+2014-12-10,77471,2.0,11.0,0.0
+2014-12-11,76005,3.0,11.0,0.0
+2014-12-12,70489,4.0,11.0,0.0
+2014-12-13,47806,5.0,11.0,0.0
+2014-12-14,50486,6.0,11.0,0.0
+2014-12-15,73353,0.0,11.0,0.0
+2014-12-16,74217,1.0,11.0,0.0
+2014-12-17,72849,2.0,11.0,0.0
+2014-12-18,70140,3.0,11.0,0.0
+2014-12-19,64016,4.0,11.0,0.0
+2014-12-20,42131,5.0,11.0,0.0
+2014-12-21,45466,6.0,11.0,0.0
+2014-12-22,59804,0.0,11.0,0.0
+2014-12-23,57678,1.0,11.0,0.0
+2014-12-24,45609,2.0,11.0,0.0
+2014-12-25,34924,3.0,11.0,1.0
+2014-12-26,40747,4.0,11.0,0.0
+2014-12-27,37359,5.0,11.0,0.0
+2014-12-28,39682,6.0,11.0,0.0
+2014-12-29,53699,0.0,11.0,0.0
+2014-12-30,54029,1.0,11.0,0.0
+2014-12-31,18574,2.0,11.0,0.0
+2015-01-01,33211,3.0,0.0,1.0
+2015-01-02,48077,4.0,0.0,0.0
+2015-01-03,44563,5.0,0.0,0.0
+2015-01-04,49137,6.0,0.0,0.0
+2015-01-05,66676,0.0,0.0,0.0
+2015-01-06,66039,1.0,0.0,0.0
+2015-01-07,70055,2.0,0.0,0.0
+2015-01-08,71505,3.0,0.0,0.0
+2015-01-09,66446,4.0,0.0,0.0
+2015-01-10,49634,5.0,0.0,0.0
+2015-01-11,52346,6.0,0.0,0.0
+2015-01-12,76021,0.0,0.0,0.0
+2015-01-13,77374,1.0,0.0,0.0
+2015-01-14,78209,2.0,0.0,0.0
+2015-01-15,77896,3.0,0.0,0.0
+2015-01-16,73533,4.0,0.0,0.0
+2015-01-17,51229,5.0,0.0,0.0
+2015-01-18,54212,6.0,0.0,0.0
+2015-01-19,75243,0.0,0.0,1.0
+2015-01-20,80898,1.0,0.0,0.0
+2015-01-21,81397,2.0,0.0,0.0
+2015-01-22,80848,3.0,0.0,0.0
+2015-01-23,77202,4.0,0.0,0.0
+2015-01-24,55935,5.0,0.0,0.0
+2015-01-25,61597,6.0,0.0,0.0
+2015-01-26,79962,0.0,0.0,0.0
+2015-01-27,82207,1.0,0.0,0.0
+2015-01-28,82554,2.0,0.0,0.0
+2015-01-29,81467,3.0,0.0,0.0
+2015-01-30,76405,4.0,0.0,0.0
+2015-01-31,53052,5.0,0.0,0.0
+2015-02-01,55516,6.0,1.0,0.0
+2015-02-02,78483,0.0,1.0,0.0
+2015-02-03,80571,1.0,1.0,0.0
+2015-02-04,83041,2.0,1.0,0.0
+2015-02-05,82992,3.0,1.0,0.0
+2015-02-06,79509,4.0,1.0,0.0
+2015-02-07,54980,5.0,1.0,0.0
+2015-02-08,59201,6.0,1.0,0.0
+2015-02-09,84344,0.0,1.0,0.0
+2015-02-10,85600,1.0,1.0,0.0
+2015-02-11,84990,2.0,1.0,0.0
+2015-02-12,84056,3.0,1.0,0.0
+2015-02-13,78771,4.0,1.0,0.0
+2015-02-14,50473,5.0,1.0,0.0
+2015-02-15,55681,6.0,1.0,0.0
+2015-02-16,76934,0.0,1.0,1.0
+2015-02-17,80882,1.0,1.0,0.0
+2015-02-18,80672,2.0,1.0,0.0
+2015-02-19,79879,3.0,1.0,0.0
+2015-02-20,77309,4.0,1.0,0.0
+2015-02-21,56256,5.0,1.0,0.0
+2015-02-22,62005,6.0,1.0,0.0
+2015-02-23,81400,0.0,1.0,0.0
+2015-02-24,84252,1.0,1.0,0.0
+2015-02-25,85804,2.0,1.0,0.0
+2015-02-26,86417,3.0,1.0,0.0
+2015-02-27,81035,4.0,1.0,0.0
+2015-02-28,57647,5.0,1.0,0.0
+2015-03-01,59286,6.0,2.0,0.0
+2015-03-02,87020,0.0,2.0,0.0
+2015-03-03,89520,1.0,2.0,0.0
+2015-03-04,90519,2.0,2.0,0.0
+2015-03-05,88078,3.0,2.0,0.0
+2015-03-06,83016,4.0,2.0,0.0
+2015-03-07,57201,5.0,2.0,0.0
+2015-03-08,60121,6.0,2.0,0.0
+2015-03-09,88330,0.0,2.0,0.0
+2015-03-10,91456,1.0,2.0,0.0
+2015-03-11,91102,2.0,2.0,0.0
+2015-03-12,90934,3.0,2.0,0.0
+2015-03-13,86003,4.0,2.0,0.0
+2015-03-14,58089,5.0,2.0,0.0
+2015-03-15,62177,6.0,2.0,0.0
+2015-03-16,90924,0.0,2.0,0.0
+2015-03-17,93210,1.0,2.0,0.0
+2015-03-18,92153,2.0,2.0,0.0
+2015-03-19,91674,3.0,2.0,0.0
+2015-03-20,86065,4.0,2.0,0.0
+2015-03-21,59532,5.0,2.0,0.0
+2015-03-22,65999,6.0,2.0,0.0
+2015-03-23,91418,0.0,2.0,0.0
+2015-03-24,94159,1.0,2.0,0.0
+2015-03-25,93458,2.0,2.0,0.0
+2015-03-26,92072,3.0,2.0,0.0
+2015-03-27,83128,4.0,2.0,0.0
+2015-03-28,57894,5.0,2.0,0.0
+2015-03-29,60676,6.0,2.0,0.0
+2015-03-30,91212,0.0,2.0,0.0
+2015-03-31,93079,1.0,2.0,0.0
+2015-04-01,90691,2.0,3.0,0.0
+2015-04-02,86589,3.0,3.0,0.0
+2015-04-03,74443,4.0,3.0,0.0
+2015-04-04,55184,5.0,3.0,0.0
+2015-04-05,54861,6.0,3.0,0.0
+2015-04-06,78892,0.0,3.0,0.0
+2015-04-07,93458,1.0,3.0,0.0
+2015-04-08,95291,2.0,3.0,0.0
+2015-04-09,93141,3.0,3.0,0.0
+2015-04-10,86853,4.0,3.0,0.0
+2015-04-11,59522,5.0,3.0,0.0
+2015-04-12,63432,6.0,3.0,0.0
+2015-04-13,91817,0.0,3.0,0.0
+2015-04-14,94974,1.0,3.0,0.0
+2015-04-15,94061,2.0,3.0,0.0
+2015-04-16,94221,3.0,3.0,0.0
+2015-04-17,88699,4.0,3.0,0.0
+2015-04-18,59654,5.0,3.0,0.0
+2015-04-19,65146,6.0,3.0,0.0
+2015-04-20,94916,0.0,3.0,0.0
+2015-04-21,97299,1.0,3.0,0.0
+2015-04-22,97751,2.0,3.0,0.0
+2015-04-23,95638,3.0,3.0,0.0
+2015-04-24,89613,4.0,3.0,0.0
+2015-04-25,61119,5.0,3.0,0.0
+2015-04-26,68408,6.0,3.0,0.0
+2015-04-27,94300,0.0,3.0,0.0
+2015-04-28,97417,1.0,3.0,0.0
+2015-04-29,95247,2.0,3.0,0.0
+2015-04-30,89512,3.0,3.0,0.0
+2015-05-01,71100,4.0,4.0,0.0
+2015-05-02,55068,5.0,4.0,0.0
+2015-05-03,59245,6.0,4.0,0.0
+2015-05-04,89677,0.0,4.0,0.0
+2015-05-05,94643,1.0,4.0,0.0
+2015-05-06,94869,2.0,4.0,0.0
+2015-05-07,93583,3.0,4.0,0.0
+2015-05-08,85836,4.0,4.0,0.0
+2015-05-09,57774,5.0,4.0,0.0
+2015-05-10,61098,6.0,4.0,0.0
+2015-05-11,92261,0.0,4.0,0.0
+2015-05-12,96912,1.0,4.0,0.0
+2015-05-13,94490,2.0,4.0,0.0
+2015-05-14,88189,3.0,4.0,0.0
+2015-05-15,84151,4.0,4.0,0.0
+2015-05-16,57518,5.0,4.0,0.0
+2015-05-17,62282,6.0,4.0,0.0
+2015-05-18,92330,0.0,4.0,0.0
+2015-05-19,96248,1.0,4.0,0.0
+2015-05-20,96061,2.0,4.0,0.0
+2015-05-21,94121,3.0,4.0,0.0
+2015-05-22,87344,4.0,4.0,0.0
+2015-05-23,56965,5.0,4.0,0.0
+2015-05-24,60744,6.0,4.0,0.0
+2015-05-25,77609,0.0,4.0,1.0
+2015-05-26,93876,1.0,4.0,0.0
+2015-05-27,95475,2.0,4.0,0.0
+2015-05-28,92911,3.0,4.0,0.0
+2015-05-29,86540,4.0,4.0,0.0
+2015-05-30,56399,5.0,4.0,0.0
+2015-05-31,59770,6.0,4.0,0.0
+2015-06-01,89681,0.0,5.0,0.0
+2015-06-02,94065,1.0,5.0,0.0
+2015-06-03,93262,2.0,5.0,0.0
+2015-06-04,89150,3.0,5.0,0.0
+2015-06-05,84240,4.0,5.0,0.0
+2015-06-06,55264,5.0,5.0,0.0
+2015-06-07,59114,6.0,5.0,0.0
+2015-06-08,89414,0.0,5.0,0.0
+2015-06-09,94342,1.0,5.0,0.0
+2015-06-10,92730,2.0,5.0,0.0
+2015-06-11,90337,3.0,5.0,0.0
+2015-06-12,82629,4.0,5.0,0.0
+2015-06-13,54393,5.0,5.0,0.0
+2015-06-14,58454,6.0,5.0,0.0
+2015-06-15,88580,0.0,5.0,0.0
+2015-06-16,91424,1.0,5.0,0.0
+2015-06-17,91408,2.0,5.0,0.0
+2015-06-18,89458,3.0,5.0,0.0
+2015-06-19,82843,4.0,5.0,0.0
+2015-06-20,52691,5.0,5.0,0.0
+2015-06-21,57034,6.0,5.0,0.0
+2015-06-22,84455,0.0,5.0,0.0
+2015-06-23,90430,1.0,5.0,0.0
+2015-06-24,89483,2.0,5.0,0.0
+2015-06-25,88234,3.0,5.0,0.0
+2015-06-26,81883,4.0,5.0,0.0
+2015-06-27,52129,5.0,5.0,0.0
+2015-06-28,54858,6.0,5.0,0.0
+2015-06-29,86080,0.0,5.0,0.0
+2015-06-30,88498,1.0,5.0,0.0
+2015-07-01,86019,2.0,6.0,0.0
+2015-07-02,84921,3.0,6.0,0.0
+2015-07-03,72626,4.0,6.0,1.0
+2015-07-04,47682,5.0,6.0,0.0
+2015-07-05,51161,6.0,6.0,0.0
+2015-07-06,84781,0.0,6.0,0.0
+2015-07-07,89887,1.0,6.0,0.0
+2015-07-08,89657,2.0,6.0,0.0
+2015-07-09,88592,3.0,6.0,0.0
+2015-07-10,82408,4.0,6.0,0.0
+2015-07-11,52448,5.0,6.0,0.0
+2015-07-12,56396,6.0,6.0,0.0
+2015-07-13,87354,0.0,6.0,0.0
+2015-07-14,88965,1.0,6.0,0.0
+2015-07-15,88859,2.0,6.0,0.0
+2015-07-16,86788,3.0,6.0,0.0
+2015-07-17,80759,4.0,6.0,0.0
+2015-07-18,51601,5.0,6.0,0.0
+2015-07-19,55215,6.0,6.0,0.0
+2015-07-20,85913,0.0,6.0,0.0
+2015-07-21,89034,1.0,6.0,0.0
+2015-07-22,89449,2.0,6.0,0.0
+2015-07-23,89039,3.0,6.0,0.0
+2015-07-24,82762,4.0,6.0,0.0
+2015-07-25,53435,5.0,6.0,0.0
+2015-07-26,57851,6.0,6.0,0.0
+2015-07-27,87111,0.0,6.0,0.0
+2015-07-28,89813,1.0,6.0,0.0
+2015-07-29,89080,2.0,6.0,0.0
+2015-07-30,86852,3.0,6.0,0.0
+2015-07-31,80715,4.0,6.0,0.0
+2015-08-01,49693,5.0,7.0,0.0
+2015-08-02,51980,6.0,7.0,0.0
+2015-08-03,83065,0.0,7.0,0.0
+2015-08-04,87753,1.0,7.0,0.0
+2015-08-05,87047,2.0,7.0,0.0
+2015-08-06,85675,3.0,7.0,0.0
+2015-08-07,79329,4.0,7.0,0.0
+2015-08-08,50372,5.0,7.0,0.0
+2015-08-09,53900,6.0,7.0,0.0
+2015-08-10,84498,0.0,7.0,0.0
+2015-08-11,88065,1.0,7.0,0.0
+2015-08-12,88003,2.0,7.0,0.0
+2015-08-13,86159,3.0,7.0,0.0
+2015-08-14,80407,4.0,7.0,0.0
+2015-08-15,52148,5.0,7.0,0.0
+2015-08-16,55563,6.0,7.0,0.0
+2015-08-17,85716,0.0,7.0,0.0
+2015-08-18,90098,1.0,7.0,0.0
+2015-08-19,90311,2.0,7.0,0.0
+2015-08-20,89112,3.0,7.0,0.0
+2015-08-21,83607,4.0,7.0,0.0
+2015-08-22,54685,5.0,7.0,0.0
+2015-08-23,59679,6.0,7.0,0.0
+2015-08-24,87916,0.0,7.0,0.0
+2015-08-25,89785,1.0,7.0,0.0
+2015-08-26,90842,2.0,7.0,0.0
+2015-08-27,89589,3.0,7.0,0.0
+2015-08-28,84012,4.0,7.0,0.0
+2015-08-29,52998,5.0,7.0,0.0
+2015-08-30,55886,6.0,7.0,0.0
+2015-08-31,86983,0.0,7.0,0.0
+2015-09-01,91295,1.0,8.0,0.0
+2015-09-02,91046,2.0,8.0,0.0
+2015-09-03,87017,3.0,8.0,0.0
+2015-09-04,80813,4.0,8.0,0.0
+2015-09-05,54463,5.0,8.0,0.0
+2015-09-06,59864,6.0,8.0,0.0
+2015-09-07,80617,0.0,8.0,1.0
+2015-09-08,93446,1.0,8.0,0.0
+2015-09-09,94640,2.0,8.0,0.0
+2015-09-10,94089,3.0,8.0,0.0
+2015-09-11,88287,4.0,8.0,0.0
+2015-09-12,57236,5.0,8.0,0.0
+2015-09-13,61339,6.0,8.0,0.0
+2015-09-14,94100,0.0,8.0,0.0
+2015-09-15,97210,1.0,8.0,0.0
+2015-09-16,97520,2.0,8.0,0.0
+2015-09-17,95561,3.0,8.0,0.0
+2015-09-18,90210,4.0,8.0,0.0
+2015-09-19,58521,5.0,8.0,0.0
+2015-09-20,62414,6.0,8.0,0.0
+2015-09-21,96432,0.0,8.0,0.0
+2015-09-22,99956,1.0,8.0,0.0
+2015-09-23,99207,2.0,8.0,0.0
+2015-09-24,97696,3.0,8.0,0.0
+2015-09-25,90619,4.0,8.0,0.0
+2015-09-26,59733,5.0,8.0,0.0
+2015-09-27,64337,6.0,8.0,0.0
+2015-09-28,95277,0.0,8.0,0.0
+2015-09-29,99909,1.0,8.0,0.0
+2015-09-30,98496,2.0,8.0,0.0
+2015-10-01,93111,3.0,9.0,0.0
+2015-10-02,86753,4.0,9.0,0.0
+2015-10-03,58268,5.0,9.0,0.0
+2015-10-04,62592,6.0,9.0,0.0
+2015-10-05,95603,0.0,9.0,0.0
+2015-10-06,99837,1.0,9.0,0.0
+2015-10-07,100860,2.0,9.0,0.0
+2015-10-08,102409,3.0,9.0,0.0
+2015-10-09,95631,4.0,9.0,0.0
+2015-10-10,66043,5.0,9.0,0.0
+2015-10-11,66601,6.0,9.0,0.0
+2015-10-12,98066,0.0,9.0,1.0
+2015-10-13,106570,1.0,9.0,0.0
+2015-10-14,105415,2.0,9.0,0.0
+2015-10-15,104366,3.0,9.0,0.0
+2015-10-16,97556,4.0,9.0,0.0
+2015-10-17,64064,5.0,9.0,0.0
+2015-10-18,69221,6.0,9.0,0.0
+2015-10-19,105710,0.0,9.0,0.0
+2015-10-20,108226,1.0,9.0,0.0
+2015-10-21,107216,2.0,9.0,0.0
+2015-10-22,106180,3.0,9.0,0.0
+2015-10-23,99348,4.0,9.0,0.0
+2015-10-24,67090,5.0,9.0,0.0
+2015-10-25,73283,6.0,9.0,0.0
+2015-10-26,104805,0.0,9.0,0.0
+2015-10-27,111076,1.0,9.0,0.0
+2015-10-28,110991,2.0,9.0,0.0
+2015-10-29,109068,3.0,9.0,0.0
+2015-10-30,100655,4.0,9.0,0.0
+2015-10-31,63910,5.0,9.0,0.0
+2015-11-01,67454,6.0,10.0,0.0
+2015-11-02,106405,0.0,10.0,0.0
+2015-11-03,113189,1.0,10.0,0.0
+2015-11-04,112399,2.0,10.0,0.0
+2015-11-05,112257,3.0,10.0,0.0
+2015-11-06,105629,4.0,10.0,0.0
+2015-11-07,70570,5.0,10.0,0.0
+2015-11-08,75161,6.0,10.0,0.0
+2015-11-09,110784,0.0,10.0,0.0
+2015-11-10,112978,1.0,10.0,0.0
+2015-11-11,107347,2.0,10.0,1.0
+2015-11-12,111293,3.0,10.0,0.0
+2015-11-13,104493,4.0,10.0,0.0
+2015-11-14,68039,5.0,10.0,0.0
+2015-11-15,73945,6.0,10.0,0.0
+2015-11-16,111285,0.0,10.0,0.0
+2015-11-17,115457,1.0,10.0,0.0
+2015-11-18,115393,2.0,10.0,0.0
+2015-11-19,115387,3.0,10.0,0.0
+2015-11-20,107008,4.0,10.0,0.0
+2015-11-21,71677,5.0,10.0,0.0
+2015-11-22,77702,6.0,10.0,0.0
+2015-11-23,113226,0.0,10.0,0.0
+2015-11-24,114841,1.0,10.0,0.0
+2015-11-25,109386,2.0,10.0,0.0
+2015-11-26,96620,3.0,10.0,1.0
+2015-11-27,88369,4.0,10.0,0.0
+2015-11-28,66696,5.0,10.0,0.0
+2015-11-29,74591,6.0,10.0,0.0
+2015-11-30,114424,0.0,10.0,0.0
+2015-12-01,117806,1.0,11.0,0.0
+2015-12-02,118201,2.0,11.0,0.0
+2015-12-03,117780,3.0,11.0,0.0
+2015-12-04,108975,4.0,11.0,0.0
+2015-12-05,72662,5.0,11.0,0.0
+2015-12-06,76360,6.0,11.0,0.0
+2015-12-07,113903,0.0,11.0,0.0
+2015-12-08,115911,1.0,11.0,0.0
+2015-12-09,115324,2.0,11.0,0.0
+2015-12-10,113844,3.0,11.0,0.0
+2015-12-11,105420,4.0,11.0,0.0
+2015-12-12,70442,5.0,11.0,0.0
+2015-12-13,74537,6.0,11.0,0.0
+2015-12-14,110352,0.0,11.0,0.0
+2015-12-15,111033,1.0,11.0,0.0
+2015-12-16,107508,2.0,11.0,0.0
+2015-12-17,103108,3.0,11.0,0.0
+2015-12-18,93664,4.0,11.0,0.0
+2015-12-19,60441,5.0,11.0,0.0
+2015-12-20,62608,6.0,11.0,0.0
+2015-12-21,91916,0.0,11.0,0.0
+2015-12-22,91125,1.0,11.0,0.0
+2015-12-23,84466,2.0,11.0,0.0
+2015-12-24,66672,3.0,11.0,0.0
+2015-12-25,50812,4.0,11.0,1.0
+2015-12-26,49720,5.0,11.0,0.0
+2015-12-27,57018,6.0,11.0,0.0
+2015-12-28,76983,0.0,11.0,0.0
+2015-12-29,80256,1.0,11.0,0.0
+2015-12-30,78067,2.0,11.0,0.0
+2016-01-01,46109,4.0,0.0,1.0
+2016-01-02,56771,5.0,0.0,0.0
+2016-01-03,63608,6.0,0.0,0.0
+2016-01-04,96670,0.0,0.0,0.0
+2016-01-05,102054,1.0,0.0,0.0
+2016-01-06,101968,2.0,0.0,0.0
+2016-01-07,103695,3.0,0.0,0.0
+2016-01-08,99226,4.0,0.0,0.0
+2016-01-09,68617,5.0,0.0,0.0
+2016-01-10,73313,6.0,0.0,0.0
+2016-01-11,107882,0.0,0.0,0.0
+2016-01-12,111240,1.0,0.0,0.0
+2016-01-13,111346,2.0,0.0,0.0
+2016-01-14,110350,3.0,0.0,0.0
+2016-01-15,103836,4.0,0.0,0.0
+2016-01-16,69762,5.0,0.0,0.0
+2016-01-17,73548,6.0,0.0,0.0
+2016-01-18,106252,0.0,0.0,1.0
+2016-01-19,114235,1.0,0.0,0.0
+2016-01-20,114520,2.0,0.0,0.0
+2016-01-21,113333,3.0,0.0,0.0
+2016-01-22,106865,4.0,0.0,0.0
+2016-01-23,74103,5.0,0.0,0.0
+2016-01-24,78655,6.0,0.0,0.0
+2016-01-25,114045,0.0,0.0,0.0
+2016-01-26,116293,1.0,0.0,0.0
+2016-01-27,117360,2.0,0.0,0.0
+2016-01-28,112890,3.0,0.0,0.0
+2016-01-29,110408,4.0,0.0,0.0
+2016-01-30,77881,5.0,0.0,0.0
+2016-01-31,81804,6.0,0.0,0.0
+2016-02-01,115705,0.0,1.0,0.0
+2016-02-02,117639,1.0,1.0,0.0
+2016-02-03,118168,2.0,1.0,0.0
+2016-02-04,115485,3.0,1.0,0.0
+2016-02-05,106779,4.0,1.0,0.0
+2016-02-06,72602,5.0,1.0,0.0
+2016-02-07,73299,6.0,1.0,0.0
+2016-02-08,103308,0.0,1.0,0.0
+2016-02-09,110246,1.0,1.0,0.0
+2016-02-10,111835,2.0,1.0,0.0
+2016-02-11,112118,3.0,1.0,0.0
+2016-02-12,105677,4.0,1.0,0.0
+2016-02-13,74145,5.0,1.0,0.0
+2016-02-14,76379,6.0,1.0,0.0
+2016-02-15,111654,0.0,1.0,1.0
+2016-02-16,121528,1.0,1.0,0.0
+2016-02-17,122884,2.0,1.0,0.0
+2016-02-18,123112,3.0,1.0,0.0
+2016-02-19,117492,4.0,1.0,0.0
+2016-02-20,81509,5.0,1.0,0.0
+2016-02-21,86026,6.0,1.0,0.0
+2016-02-22,124960,0.0,1.0,0.0
+2016-02-23,128025,1.0,1.0,0.0
+2016-02-24,128860,2.0,1.0,0.0
+2016-02-25,126574,3.0,1.0,0.0
+2016-02-26,119158,4.0,1.0,0.0
+2016-02-27,81761,5.0,1.0,0.0
+2016-02-28,86421,6.0,1.0,0.0
+2016-02-29,125898,0.0,1.0,0.0
+2016-03-01,128020,1.0,2.0,0.0
+2016-03-02,130518,2.0,2.0,0.0
+2016-03-03,129859,3.0,2.0,0.0
+2016-03-04,121636,4.0,2.0,0.0
+2016-03-05,83814,5.0,2.0,0.0
+2016-03-06,86859,6.0,2.0,0.0
+2016-03-07,127229,0.0,2.0,0.0
+2016-03-08,129281,1.0,2.0,0.0
+2016-03-09,131505,2.0,2.0,0.0
+2016-03-10,126847,3.0,2.0,0.0
+2016-03-11,121670,4.0,2.0,0.0
+2016-03-12,82209,5.0,2.0,0.0
+2016-03-13,87358,6.0,2.0,0.0
+2016-03-14,129607,0.0,2.0,0.0
+2016-03-15,132397,1.0,2.0,0.0
+2016-03-16,132666,2.0,2.0,0.0
+2016-03-17,129579,3.0,2.0,0.0
+2016-03-18,120239,4.0,2.0,0.0
+2016-03-19,81427,5.0,2.0,0.0
+2016-03-20,86878,6.0,2.0,0.0
+2016-03-21,128245,0.0,2.0,0.0
+2016-03-22,130351,1.0,2.0,0.0
+2016-03-23,128611,2.0,2.0,0.0
+2016-03-24,122141,3.0,2.0,0.0
+2016-03-25,105815,4.0,2.0,0.0
+2016-03-26,78197,5.0,2.0,0.0
+2016-03-27,78675,6.0,2.0,0.0
+2016-03-28,116328,0.0,2.0,0.0
+2016-03-29,131001,1.0,2.0,0.0
+2016-03-30,133101,2.0,2.0,0.0
+2016-03-31,130283,3.0,2.0,0.0
+2016-04-01,119257,4.0,3.0,0.0
+2016-04-02,81281,5.0,3.0,0.0
+2016-04-03,87360,6.0,3.0,0.0
+2016-04-04,126389,0.0,3.0,0.0
+2016-04-05,133803,1.0,3.0,0.0
+2016-04-06,135934,2.0,3.0,0.0
+2016-04-07,134653,3.0,3.0,0.0
+2016-04-08,125221,4.0,3.0,0.0
+2016-04-09,85645,5.0,3.0,0.0
+2016-04-10,91857,6.0,3.0,0.0
+2016-04-11,136700,0.0,3.0,0.0
+2016-04-12,138801,1.0,3.0,0.0
+2016-04-13,137409,2.0,3.0,0.0
+2016-04-14,134651,3.0,3.0,0.0
+2016-04-15,125713,4.0,3.0,0.0
+2016-04-16,84789,5.0,3.0,0.0
+2016-04-17,90514,6.0,3.0,0.0
+2016-04-18,135770,0.0,3.0,0.0
+2016-04-19,140338,1.0,3.0,0.0
+2016-04-20,138994,2.0,3.0,0.0
+2016-04-21,134338,3.0,3.0,0.0
+2016-04-22,125713,4.0,3.0,0.0
+2016-04-23,85348,5.0,3.0,0.0
+2016-04-24,91963,6.0,3.0,0.0
+2016-04-25,135422,0.0,3.0,0.0
+2016-04-26,141059,1.0,3.0,0.0
+2016-04-27,138390,2.0,3.0,0.0
+2016-04-28,134493,3.0,3.0,0.0
+2016-04-29,123089,4.0,3.0,0.0
+2016-04-30,78081,5.0,3.0,0.0
+2016-05-01,80160,6.0,4.0,0.0
+2016-05-02,118508,0.0,4.0,0.0
+2016-05-03,131204,1.0,4.0,0.0
+2016-05-04,132146,2.0,4.0,0.0
+2016-05-05,123214,3.0,4.0,0.0
+2016-05-06,117566,4.0,4.0,0.0
+2016-05-07,78005,5.0,4.0,0.0
+2016-05-08,81871,6.0,4.0,0.0
+2016-05-09,127489,0.0,4.0,0.0
+2016-05-10,136121,1.0,4.0,0.0
+2016-05-11,135402,2.0,4.0,0.0
+2016-05-12,132926,3.0,4.0,0.0
+2016-05-13,123555,4.0,4.0,0.0
+2016-05-14,80533,5.0,4.0,0.0
+2016-05-15,84697,6.0,4.0,0.0
+2016-05-16,125306,0.0,4.0,0.0
+2016-05-17,135812,1.0,4.0,0.0
+2016-05-18,135197,2.0,4.0,0.0
+2016-05-19,131924,3.0,4.0,0.0
+2016-05-20,122504,4.0,4.0,0.0
+2016-05-21,79192,5.0,4.0,0.0
+2016-05-22,84851,6.0,4.0,0.0
+2016-05-23,127438,0.0,4.0,0.0
+2016-05-24,133972,1.0,4.0,0.0
+2016-05-25,131697,2.0,4.0,0.0
+2016-05-26,126174,3.0,4.0,0.0
+2016-05-27,117773,4.0,4.0,0.0
+2016-05-28,74793,5.0,4.0,0.0
+2016-05-29,79262,6.0,4.0,0.0
+2016-05-30,113390,0.0,4.0,1.0
+2016-05-31,129636,1.0,4.0,0.0
+2016-06-01,129838,2.0,5.0,0.0
+2016-06-02,127650,3.0,5.0,0.0
+2016-06-03,119107,4.0,5.0,0.0
+2016-06-04,76582,5.0,5.0,0.0
+2016-06-05,80829,6.0,5.0,0.0
+2016-06-06,123175,0.0,5.0,0.0
+2016-06-07,128655,1.0,5.0,0.0
+2016-06-08,126728,2.0,5.0,0.0
+2016-06-09,116963,3.0,5.0,0.0
+2016-06-10,108602,4.0,5.0,0.0
+2016-06-11,73541,5.0,5.0,0.0
+2016-06-12,82245,6.0,5.0,0.0
+2016-06-13,119977,0.0,5.0,0.0
+2016-06-14,125678,1.0,5.0,0.0
+2016-06-15,125977,2.0,5.0,0.0
+2016-06-16,122900,3.0,5.0,0.0
+2016-06-17,113905,4.0,5.0,0.0
+2016-06-18,71738,5.0,5.0,0.0
+2016-06-19,74376,6.0,5.0,0.0
+2016-06-20,93499,0.0,5.0,0.0
+2016-06-21,124257,1.0,5.0,0.0
+2016-06-22,122793,2.0,5.0,0.0
+2016-06-23,120902,3.0,5.0,0.0
+2016-06-24,108118,4.0,5.0,0.0
+2016-06-25,69170,5.0,5.0,0.0
+2016-06-26,72480,6.0,5.0,0.0
+2016-06-27,115501,0.0,5.0,0.0
+2016-06-28,121523,1.0,5.0,0.0
+2016-06-29,121456,2.0,5.0,0.0
+2016-06-30,119093,3.0,5.0,0.0
+2016-07-01,107813,4.0,6.0,0.0
+2016-07-02,66427,5.0,6.0,0.0
+2016-07-03,68168,6.0,6.0,0.0
+2016-07-04,101448,0.0,6.0,1.0
+2016-07-05,114130,1.0,6.0,0.0
+2016-07-06,118196,2.0,6.0,0.0
+2016-07-07,116360,3.0,6.0,0.0
+2016-07-08,109588,4.0,6.0,0.0
+2016-07-09,68949,5.0,6.0,0.0
+2016-07-10,71387,6.0,6.0,0.0
+2016-07-11,116802,0.0,6.0,0.0
+2016-07-12,119864,1.0,6.0,0.0
+2016-07-13,120468,2.0,6.0,0.0
+2016-07-14,117523,3.0,6.0,0.0
+2016-07-15,108681,4.0,6.0,0.0
+2016-07-16,67189,5.0,6.0,0.0
+2016-07-17,71085,6.0,6.0,0.0
+2016-07-18,116616,0.0,6.0,0.0
+2016-07-19,121000,1.0,6.0,0.0
+2016-07-20,119165,2.0,6.0,0.0
+2016-07-21,117941,3.0,6.0,0.0
+2016-07-22,110570,4.0,6.0,0.0
+2016-07-23,68398,5.0,6.0,0.0
+2016-07-24,71980,6.0,6.0,0.0
+2016-07-25,116361,0.0,6.0,0.0
+2016-07-26,120986,1.0,6.0,0.0
+2016-07-27,120932,2.0,6.0,0.0
+2016-07-28,118101,3.0,6.0,0.0
+2016-07-29,110240,4.0,6.0,0.0
+2016-07-30,69022,5.0,6.0,0.0
+2016-07-31,71959,6.0,6.0,0.0
+2016-08-01,114920,0.0,7.0,0.0
+2016-08-02,120783,1.0,7.0,0.0
+2016-08-03,119825,2.0,7.0,0.0
+2016-08-04,117712,3.0,7.0,0.0
+2016-08-05,109966,4.0,7.0,0.0
+2016-08-06,67755,5.0,7.0,0.0
+2016-08-07,70693,6.0,7.0,0.0
+2016-08-08,115440,0.0,7.0,0.0
+2016-08-09,118682,1.0,7.0,0.0
+2016-08-10,119555,2.0,7.0,0.0
+2016-08-11,117924,3.0,7.0,0.0
+2016-08-12,110083,4.0,7.0,0.0
+2016-08-13,68028,5.0,7.0,0.0
+2016-08-14,69705,6.0,7.0,0.0
+2016-08-15,109543,0.0,7.0,0.0
+2016-08-16,120896,1.0,7.0,0.0
+2016-08-17,121107,2.0,7.0,0.0
+2016-08-18,119516,3.0,7.0,0.0
+2016-08-19,112999,4.0,7.0,0.0
+2016-08-20,71603,5.0,7.0,0.0
+2016-08-21,74724,6.0,7.0,0.0
+2016-08-22,120374,0.0,7.0,0.0
+2016-08-23,125253,1.0,7.0,0.0
+2016-08-24,124546,2.0,7.0,0.0
+2016-08-25,123134,3.0,7.0,0.0
+2016-08-26,115443,4.0,7.0,0.0
+2016-08-27,73510,5.0,7.0,0.0
+2016-08-28,77456,6.0,7.0,0.0
+2016-08-29,122370,0.0,7.0,0.0
+2016-08-30,128081,1.0,7.0,0.0
+2016-08-31,127520,2.0,7.0,0.0
+2016-09-01,124829,3.0,8.0,0.0
+2016-09-02,115659,4.0,8.0,0.0
+2016-09-03,71772,5.0,8.0,0.0
+2016-09-04,76164,6.0,8.0,0.0
+2016-09-05,109751,0.0,8.0,1.0
+2016-09-06,127745,1.0,8.0,0.0
+2016-09-07,128145,2.0,8.0,0.0
+2016-09-08,127996,3.0,8.0,0.0
+2016-09-09,120314,4.0,8.0,0.0
+2016-09-10,77719,5.0,8.0,0.0
+2016-09-11,81649,6.0,8.0,0.0
+2016-09-12,127325,0.0,8.0,0.0
+2016-09-13,131451,1.0,8.0,0.0
+2016-09-14,128826,2.0,8.0,0.0
+2016-09-15,120041,3.0,8.0,0.0
+2016-09-16,113989,4.0,8.0,0.0
+2016-09-17,80862,5.0,8.0,0.0
+2016-09-18,91832,6.0,8.0,0.0
+2016-09-19,131871,0.0,8.0,0.0
+2016-09-20,138590,1.0,8.0,0.0
+2016-09-21,138146,2.0,8.0,0.0
+2016-09-22,136479,3.0,8.0,0.0
+2016-09-23,127803,4.0,8.0,0.0
+2016-09-24,81861,5.0,8.0,0.0
+2016-09-25,86861,6.0,8.0,0.0
+2016-09-26,137176,0.0,8.0,0.0
+2016-09-27,139433,1.0,8.0,0.0
+2016-09-28,140373,2.0,8.0,0.0
+2016-09-29,138011,3.0,8.0,0.0
+2016-09-30,127044,4.0,8.0,0.0
+2016-10-01,78726,5.0,9.0,0.0
+2016-10-02,82758,6.0,9.0,0.0
+2016-10-03,125866,0.0,9.0,0.0
+2016-10-04,132182,1.0,9.0,0.0
+2016-10-05,131995,2.0,9.0,0.0
+2016-10-06,132759,3.0,9.0,0.0
+2016-10-07,124588,4.0,9.0,0.0
+2016-10-08,90358,5.0,9.0,0.0
+2016-10-09,96542,6.0,9.0,0.0
+2016-10-10,135850,0.0,9.0,1.0
+2016-10-11,144073,1.0,9.0,0.0
+2016-10-12,143248,2.0,9.0,0.0
+2016-10-13,144176,3.0,9.0,0.0
+2016-10-14,134423,4.0,9.0,0.0
+2016-10-15,88312,5.0,9.0,0.0
+2016-10-16,94694,6.0,9.0,0.0
+2016-10-17,140981,0.0,9.0,0.0
+2016-10-18,150758,1.0,9.0,0.0
+2016-10-19,148760,2.0,9.0,0.0
+2016-10-20,145021,3.0,9.0,0.0
+2016-10-21,123991,4.0,9.0,0.0
+2016-10-22,90117,5.0,9.0,0.0
+2016-10-23,95498,6.0,9.0,0.0
+2016-10-24,146136,0.0,9.0,0.0
+2016-10-25,150283,1.0,9.0,0.0
+2016-10-26,149086,2.0,9.0,0.0
+2016-10-27,146600,3.0,9.0,0.0
+2016-10-28,134101,4.0,9.0,0.0
+2016-10-29,85873,5.0,9.0,0.0
+2016-10-30,91905,6.0,9.0,0.0
+2016-10-31,141022,0.0,9.0,0.0
+2016-11-01,142467,1.0,10.0,0.0
+2016-11-02,148404,2.0,10.0,0.0
+2016-11-03,149540,3.0,10.0,0.0
+2016-11-04,138040,4.0,10.0,0.0
+2016-11-05,93128,5.0,10.0,0.0
+2016-11-06,99820,6.0,10.0,0.0
+2016-11-07,150788,0.0,10.0,0.0
+2016-11-08,150053,1.0,10.0,0.0
+2016-11-09,140674,2.0,10.0,0.0
+2016-11-10,146301,3.0,10.0,0.0
+2016-11-11,132609,4.0,10.0,1.0
+2016-11-12,93843,5.0,10.0,0.0
+2016-11-13,100633,6.0,10.0,0.0
+2016-11-14,150935,0.0,10.0,0.0
+2016-11-15,156066,1.0,10.0,0.0
+2016-11-16,156273,2.0,10.0,0.0
+2016-11-17,154473,3.0,10.0,0.0
+2016-11-18,144040,4.0,10.0,0.0
+2016-11-19,95853,5.0,10.0,0.0
+2016-11-20,103220,6.0,10.0,0.0
+2016-11-21,154232,0.0,10.0,0.0
+2016-11-22,156131,1.0,10.0,0.0
+2016-11-23,149146,2.0,10.0,0.0
+2016-11-24,133080,3.0,10.0,1.0
+2016-11-25,120535,4.0,10.0,0.0
+2016-11-26,90022,5.0,10.0,0.0
+2016-11-27,100373,6.0,10.0,0.0
+2016-11-28,154971,0.0,10.0,0.0
+2016-11-29,161691,1.0,10.0,0.0
+2016-11-30,159450,2.0,10.0,0.0
+2016-12-01,157196,3.0,11.0,0.0
+2016-12-02,147743,4.0,11.0,0.0
+2016-12-03,98102,5.0,11.0,0.0
+2016-12-04,104400,6.0,11.0,0.0
+2016-12-05,156268,0.0,11.0,0.0
+2016-12-06,158169,1.0,11.0,0.0
+2016-12-07,158758,2.0,11.0,0.0
+2016-12-08,152258,3.0,11.0,0.0
+2016-12-09,142222,4.0,11.0,0.0
+2016-12-10,95665,5.0,11.0,0.0
+2016-12-11,100707,6.0,11.0,0.0
+2016-12-12,148783,0.0,11.0,0.0
+2016-12-13,152591,1.0,11.0,0.0
+2016-12-14,149908,2.0,11.0,0.0
+2016-12-15,145085,3.0,11.0,0.0
+2016-12-16,131580,4.0,11.0,0.0
+2016-12-17,84443,5.0,11.0,0.0
+2016-12-18,88845,6.0,11.0,0.0
+2016-12-19,134794,0.0,11.0,0.0
+2016-12-20,136427,1.0,11.0,0.0
+2016-12-21,131770,2.0,11.0,0.0
+2016-12-22,124751,3.0,11.0,0.0
+2016-12-23,105776,4.0,11.0,0.0
+2016-12-24,66740,5.0,11.0,0.0
+2016-12-25,60535,6.0,11.0,0.0
+2016-12-26,86775,0.0,11.0,1.0
+2016-12-27,102574,1.0,11.0,0.0
+2016-12-28,106393,2.0,11.0,0.0
+2016-12-29,105158,3.0,11.0,0.0
+2016-12-30,98098,4.0,11.0,0.0
+2016-12-31,64696,5.0,11.0,0.0
+2017-01-01,59005,6.0,0.0,0.0
+2017-01-02,95818,0.0,0.0,1.0
+2017-01-03,127728,1.0,0.0,0.0
+2017-01-04,133210,2.0,0.0,0.0
+2017-01-05,128376,3.0,0.0,0.0
+2017-01-06,125230,4.0,0.0,0.0
+2017-01-07,71521,5.0,0.0,0.0
+2017-01-08,94736,6.0,0.0,0.0
+2017-01-09,140861,0.0,0.0,0.0
+2017-01-10,145521,1.0,0.0,0.0
+2017-01-11,145604,2.0,0.0,0.0
+2017-01-12,144985,3.0,0.0,0.0
+2017-01-13,135657,4.0,0.0,0.0
+2017-01-14,91791,5.0,0.0,0.0
+2017-01-15,97570,6.0,0.0,0.0
+2017-01-16,140046,0.0,0.0,1.0
+2017-01-17,151455,1.0,0.0,0.0
+2017-01-18,151122,2.0,0.0,0.0
+2017-01-19,149733,3.0,0.0,0.0
+2017-01-20,140506,4.0,0.0,0.0
+2017-01-21,97774,5.0,0.0,0.0
+2017-01-22,106965,6.0,0.0,0.0
+2017-01-23,147843,0.0,0.0,0.0
+2017-01-24,149039,1.0,0.0,0.0
+2017-01-25,144802,2.0,0.0,0.0
+2017-01-26,138288,3.0,0.0,0.0
+2017-01-27,127738,4.0,0.0,0.0
+2017-01-28,88164,5.0,0.0,0.0
+2017-01-29,92052,6.0,0.0,0.0
+2017-01-30,137919,0.0,0.0,0.0
+2017-01-31,143069,1.0,0.0,0.0
+2017-02-01,143529,2.0,1.0,0.0
+2017-02-02,145011,3.0,1.0,0.0
+2017-02-03,139875,4.0,1.0,0.0
+2017-02-04,101218,5.0,1.0,0.0
+2017-02-05,104585,6.0,1.0,0.0
+2017-02-06,152808,0.0,1.0,0.0
+2017-02-07,161273,1.0,1.0,0.0
+2017-02-08,162144,2.0,1.0,0.0
+2017-02-09,159440,3.0,1.0,0.0
+2017-02-10,149755,4.0,1.0,0.0
+2017-02-11,100746,5.0,1.0,0.0
+2017-02-12,106434,6.0,1.0,0.0
+2017-02-13,160474,0.0,1.0,0.0
+2017-02-14,159982,1.0,1.0,0.0
+2017-02-15,161897,2.0,1.0,0.0
+2017-02-16,164364,3.0,1.0,0.0
+2017-02-17,153956,4.0,1.0,0.0
+2017-02-18,104661,5.0,1.0,0.0
+2017-02-19,109589,6.0,1.0,0.0
+2017-02-20,158043,0.0,1.0,1.0
+2017-02-21,170265,1.0,1.0,0.0
+2017-02-22,170559,2.0,1.0,0.0
+2017-02-23,163711,3.0,1.0,0.0
+2017-02-24,154537,4.0,1.0,0.0
+2017-02-25,106039,5.0,1.0,0.0
+2017-02-26,111816,6.0,1.0,0.0
+2017-02-27,163119,0.0,1.0,0.0
+2017-02-28,165643,1.0,1.0,0.0
+2017-03-01,167480,2.0,2.0,0.0
+2017-03-02,168730,3.0,2.0,0.0
+2017-03-03,158171,4.0,2.0,0.0
+2017-03-04,106739,5.0,2.0,0.0
+2017-03-05,114464,6.0,2.0,0.0
+2017-03-06,169538,0.0,2.0,0.0
+2017-03-07,173736,1.0,2.0,0.0
+2017-03-08,168734,2.0,2.0,0.0
+2017-03-09,171452,3.0,2.0,0.0
+2017-03-10,159470,4.0,2.0,0.0
+2017-03-11,107371,5.0,2.0,0.0
+2017-03-12,114907,6.0,2.0,0.0
+2017-03-13,170043,0.0,2.0,0.0
+2017-03-14,174748,1.0,2.0,0.0
+2017-03-15,171274,2.0,2.0,0.0
+2017-03-16,172067,3.0,2.0,0.0
+2017-03-17,159312,4.0,2.0,0.0
+2017-03-18,107141,5.0,2.0,0.0
+2017-03-19,116705,6.0,2.0,0.0
+2017-03-20,173053,0.0,2.0,0.0
+2017-03-21,179270,1.0,2.0,0.0
+2017-03-22,178776,2.0,2.0,0.0
+2017-03-23,175353,3.0,2.0,0.0
+2017-03-24,155802,4.0,2.0,0.0
+2017-03-25,107862,5.0,2.0,0.0
+2017-03-26,114867,6.0,2.0,0.0
+2017-03-27,174989,0.0,2.0,0.0
+2017-03-28,177936,1.0,2.0,0.0
+2017-03-29,177053,2.0,2.0,0.0
+2017-03-30,174951,3.0,2.0,0.0
+2017-03-31,161692,4.0,2.0,0.0
+2017-04-01,111982,5.0,3.0,0.0
+2017-04-02,109185,6.0,3.0,0.0
+2017-04-03,159117,0.0,3.0,0.0
+2017-04-04,162855,1.0,3.0,0.0
+2017-04-05,176611,2.0,3.0,0.0
+2017-04-06,174519,3.0,3.0,0.0
+2017-04-07,161085,4.0,3.0,0.0
+2017-04-08,106383,5.0,3.0,0.0
+2017-04-09,112315,6.0,3.0,0.0
+2017-04-10,169584,0.0,3.0,0.0
+2017-04-11,171826,1.0,3.0,0.0
+2017-04-12,168847,2.0,3.0,0.0
+2017-04-13,160786,3.0,3.0,0.0
+2017-04-14,137040,4.0,3.0,0.0
+2017-04-15,100190,5.0,3.0,0.0
+2017-04-16,100898,6.0,3.0,0.0
+2017-04-17,152066,0.0,3.0,0.0
+2017-04-18,174171,1.0,3.0,0.0
+2017-04-19,175620,2.0,3.0,0.0
+2017-04-20,173856,3.0,3.0,0.0
+2017-04-21,160574,4.0,3.0,0.0
+2017-04-22,110084,5.0,3.0,0.0
+2017-04-23,117159,6.0,3.0,0.0
+2017-04-24,174875,0.0,3.0,0.0
+2017-04-25,179750,1.0,3.0,0.0
+2017-04-26,179115,2.0,3.0,0.0
+2017-04-27,172230,3.0,3.0,0.0
+2017-04-28,157630,4.0,3.0,0.0
+2017-04-29,99513,5.0,3.0,0.0
+2017-04-30,100849,6.0,3.0,0.0
+2017-05-01,137413,0.0,4.0,0.0
+2017-05-02,169970,1.0,4.0,0.0
+2017-05-03,173007,2.0,4.0,0.0
+2017-05-04,171814,3.0,4.0,0.0
+2017-05-05,158556,4.0,4.0,0.0
+2017-05-06,104891,5.0,4.0,0.0
+2017-05-07,111184,6.0,4.0,0.0
+2017-05-08,167207,0.0,4.0,0.0
+2017-05-09,174139,1.0,4.0,0.0
+2017-05-10,173376,2.0,4.0,0.0
+2017-05-11,170399,3.0,4.0,0.0
+2017-05-12,159003,4.0,4.0,0.0
+2017-05-13,104441,5.0,4.0,0.0
+2017-05-14,108658,6.0,4.0,0.0
+2017-05-15,169555,0.0,4.0,0.0
+2017-05-16,174468,1.0,4.0,0.0
+2017-05-17,172630,2.0,4.0,0.0
+2017-05-18,168885,3.0,4.0,0.0
+2017-05-19,158328,4.0,4.0,0.0
+2017-05-20,101883,5.0,4.0,0.0
+2017-05-21,108279,6.0,4.0,0.0
+2017-05-22,167274,0.0,4.0,0.0
+2017-05-23,173357,1.0,4.0,0.0
+2017-05-24,170350,2.0,4.0,0.0
+2017-05-25,157737,3.0,4.0,0.0
+2017-05-26,150028,4.0,4.0,0.0
+2017-05-27,103856,5.0,4.0,0.0
+2017-05-28,99612,6.0,4.0,0.0
+2017-05-29,138303,0.0,4.0,1.0
+2017-05-30,159403,1.0,4.0,0.0
+2017-05-31,167107,2.0,4.0,0.0
+2017-06-01,165586,3.0,5.0,0.0
+2017-06-02,154671,4.0,5.0,0.0
+2017-06-03,99082,5.0,5.0,0.0
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/helper.py b/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/helper.py
similarity index 94%
rename from how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/helper.py
rename to how-to-use-azureml/automated-machine-learning/forecasting-github-dau/helper.py
index 5b78e0ba4..f67458c95 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/helper.py
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/helper.py
@@ -105,13 +105,8 @@ def run_inference(
     train_run.download_file(
         "outputs/{}".format(model_base_name), "inference/{}".format(model_base_name)
     )
-    train_run.download_file("outputs/conda_env_v_1_0_0.yml", "inference/condafile.yml")
 
-    inference_env = Environment("myenv")
-    inference_env.docker.enabled = True
-    inference_env.python.conda_dependencies = CondaDependencies(
-        conda_dependencies_file_path="inference/condafile.yml"
-    )
+    inference_env = train_run.get_environment()
 
     est = Estimator(
         source_directory=script_folder,
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/infer.py b/how-to-use-azureml/automated-machine-learning/forecasting-github-dau/infer.py
similarity index 100%
rename from how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/infer.py
rename to how-to-use-azureml/automated-machine-learning/forecasting-github-dau/infer.py
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-hierarchical-timeseries/auto-ml-forecasting-hierarchical-timeseries.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-hierarchical-timeseries/auto-ml-forecasting-hierarchical-timeseries.ipynb
index e2ab133f9..ec2a72e75 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-hierarchical-timeseries/auto-ml-forecasting-hierarchical-timeseries.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-hierarchical-timeseries/auto-ml-forecasting-hierarchical-timeseries.ipynb
@@ -78,7 +78,7 @@
         "output[\"Resource Group\"] = ws.resource_group\n",
         "output[\"Location\"] = ws.location\n",
         "output[\"Default datastore name\"] = dstore.name\n",
-        "pd.set_option(\"display.max_colwidth\", -1)\n",
+        "pd.set_option(\"display.max_colwidth\", None)\n",
         "outputDf = pd.DataFrame(data=output, index=[\"\"])\n",
         "outputDf.T"
       ]
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-many-models/auto-ml-forecasting-many-models.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-many-models/auto-ml-forecasting-many-models.ipynb
index 75caf8596..7aaa858bc 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-many-models/auto-ml-forecasting-many-models.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-many-models/auto-ml-forecasting-many-models.ipynb
@@ -78,7 +78,7 @@
         "output[\"Resource Group\"] = ws.resource_group\n",
         "output[\"Location\"] = ws.location\n",
         "output[\"Default datastore name\"] = dstore.name\n",
-        "pd.set_option(\"display.max_colwidth\", -1)\n",
+        "pd.set_option(\"display.max_colwidth\", None)\n",
         "outputDf = pd.DataFrame(data=output, index=[\"\"])\n",
         "outputDf.T"
       ]
@@ -234,11 +234,14 @@
         "input_ds_small = Dataset.Tabular.from_delimited_files(\n",
         "    path=oj_datastore.path(ds_name_small + \"/\"), validate=False\n",
         ")\n",
+        "# Drop the columns 'Revenue' as this column contains leak feature.\n",
+        "input_ds_small = input_ds_small.drop_columns(columns=[\"Revenue\"])\n",
         "\n",
         "inference_name_small = \"oj-inference-small-tabular\"\n",
         "inference_ds_small = Dataset.Tabular.from_delimited_files(\n",
         "    path=oj_datastore.path(inference_name_small + \"/\"), validate=False\n",
-        ")"
+        ")\n",
+        "inference_ds_small = inference_ds_small.drop_columns(columns=[\"Revenue\"])"
       ]
     },
     {
@@ -354,7 +357,6 @@
         "    \"label_column_name\": \"Quantity\",\n",
         "    \"n_cross_validations\": 3,\n",
         "    \"time_column_name\": \"WeekStarting\",\n",
-        "    \"drop_column_names\": \"Revenue\",\n",
         "    \"max_horizon\": 6,\n",
         "    \"grain_column_names\": partition_column_names,\n",
         "    \"track_child_runs\": False,\n",
@@ -649,7 +651,6 @@
         "    \"Quantity\",\n",
         "    \"Advert\",\n",
         "    \"Price\",\n",
-        "    \"Revenue\",\n",
         "    \"Predicted\",\n",
         "]\n",
         "print(\n",
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb
index d41a93bc0..6323963be 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb
@@ -82,7 +82,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
@@ -113,7 +113,7 @@
         "output[\"Resource Group\"] = ws.resource_group\n",
         "output[\"Location\"] = ws.location\n",
         "output[\"Run History Name\"] = experiment_name\n",
-        "pd.set_option(\"display.max_colwidth\", -1)\n",
+        "pd.set_option(\"display.max_colwidth\", None)\n",
         "outputDf = pd.DataFrame(data=output, index=[\"\"])\n",
         "outputDf.T"
       ]
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-recipes-univariate/auto-ml-forecasting-univariate-recipe-run-experiment.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-recipes-univariate/auto-ml-forecasting-univariate-recipe-run-experiment.ipynb
index 7483fec05..7927a66dc 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-recipes-univariate/auto-ml-forecasting-univariate-recipe-run-experiment.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-recipes-univariate/auto-ml-forecasting-univariate-recipe-run-experiment.ipynb
@@ -229,7 +229,7 @@
         "output[\"Resource Group\"] = ws.resource_group\n",
         "output[\"Location\"] = ws.location\n",
         "output[\"Run History Name\"] = experiment_name\n",
-        "pd.set_option(\"display.max_colwidth\", -1)\n",
+        "pd.set_option(\"display.max_colwidth\", None)\n",
         "outputDf = pd.DataFrame(data=output, index=[\"\"])\n",
         "print(outputDf.T)"
       ]
diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-recipes-univariate/helper_functions.py b/how-to-use-azureml/automated-machine-learning/forecasting-recipes-univariate/helper_functions.py
index 9f988def0..682ebf51a 100644
--- a/how-to-use-azureml/automated-machine-learning/forecasting-recipes-univariate/helper_functions.py
+++ b/how-to-use-azureml/automated-machine-learning/forecasting-recipes-univariate/helper_functions.py
@@ -46,11 +46,11 @@ def kpss_test(series, **kw):
     """
     if kw["store"]:
         statistic, p_value, critical_values, rstore = stattools.kpss(
-            series, regression=kw["reg_type"], lags=kw["lags"], store=kw["store"]
+            series, regression=kw["reg_type"], nlags=kw["lags"], store=kw["store"]
         )
     else:
         statistic, p_value, lags, critical_values = stattools.kpss(
-            series, regression=kw["reg_type"], lags=kw["lags"]
+            series, regression=kw["reg_type"], nlags=kw["lags"]
         )
     output = {
         "statistic": statistic,
diff --git a/how-to-use-azureml/automated-machine-learning/local-run-classification-credit-card-fraud/auto-ml-classification-credit-card-fraud-local.ipynb b/how-to-use-azureml/automated-machine-learning/local-run-classification-credit-card-fraud/auto-ml-classification-credit-card-fraud-local.ipynb
index b6302f391..59d31d666 100644
--- a/how-to-use-azureml/automated-machine-learning/local-run-classification-credit-card-fraud/auto-ml-classification-credit-card-fraud-local.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/local-run-classification-credit-card-fraud/auto-ml-classification-credit-card-fraud-local.ipynb
@@ -96,7 +96,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
@@ -119,7 +119,7 @@
         "output['Resource Group'] = ws.resource_group\n",
         "output['Location'] = ws.location\n",
         "output['Experiment Name'] = experiment.name\n",
-        "pd.set_option('display.max_colwidth', -1)\n",
+        "pd.set_option('display.max_colwidth', None)\n",
         "outputDf = pd.DataFrame(data = output, index = [''])\n",
         "outputDf.T"
       ]
diff --git a/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/auto-ml-regression-explanation-featurization.ipynb b/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/auto-ml-regression-explanation-featurization.ipynb
index e033ee4ab..6487f46a2 100644
--- a/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/auto-ml-regression-explanation-featurization.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/auto-ml-regression-explanation-featurization.ipynb
@@ -96,7 +96,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
@@ -118,7 +118,7 @@
         "output['Resource Group'] = ws.resource_group\n",
         "output['Location'] = ws.location\n",
         "output['Experiment Name'] = experiment.name\n",
-        "pd.set_option('display.max_colwidth', -1)\n",
+        "pd.set_option('display.max_colwidth', None)\n",
         "outputDf = pd.DataFrame(data = output, index = [''])\n",
         "outputDf.T"
       ]
@@ -847,7 +847,7 @@
       "outputs": [],
       "source": [
         "%matplotlib inline\n",
-        "test_pred = plt.scatter(y_test, y_pred_test, color='')\n",
+        "test_pred = plt.scatter(y_test, y_pred_test, color=None)\n",
         "test_test = plt.scatter(y_test, y_test, color='g')\n",
         "plt.legend((test_pred, test_test), ('prediction', 'truth'), loc='upper left', fontsize=8)\n",
         "plt.show()"
diff --git a/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/score_explain.py b/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/score_explain.py
index 25e48cdf8..68c4222f8 100644
--- a/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/score_explain.py
+++ b/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/score_explain.py
@@ -2,6 +2,7 @@
 import joblib
 from azureml.core.model import Model
 from azureml.train.automl.runtime.automl_explain_utilities import automl_setup_model_explanations
+import scipy as sp
 
 
 def init():
@@ -18,6 +19,22 @@ def init():
     scoring_explainer = joblib.load(scoring_explainer_path)
 
 
+def is_multi_dimensional(matrix):
+    if hasattr(matrix, 'ndim') and matrix.ndim > 1:
+        return True
+    if hasattr(matrix, 'shape') and matrix.shape[1]:
+        return True
+    return False
+
+
+def convert_matrix(matrix):
+    if sp.sparse.issparse(matrix):
+        matrix = matrix.todense()
+    if is_multi_dimensional(matrix):
+        matrix = matrix.tolist()
+    return matrix
+
+
 def run(raw_data):
     # Get predictions and explanations for each data point
     data = pd.read_json(raw_data, orient='records')
@@ -28,8 +45,12 @@ def run(raw_data):
                                                                  X_test=data, task='regression')
     # Retrieve model explanations for engineered explanations
     engineered_local_importance_values = scoring_explainer.explain(automl_explainer_setup_obj.X_test_transform)
+    engineered_local_importance_values = convert_matrix(engineered_local_importance_values)
+
     # Retrieve model explanations for raw explanations
     raw_local_importance_values = scoring_explainer.explain(automl_explainer_setup_obj.X_test_transform, get_raw=True)
+    raw_local_importance_values = convert_matrix(raw_local_importance_values)
+
     # You can return any data type as long as it is JSON-serializable
     return {'predictions': predictions.tolist(),
             'engineered_local_importance_values': engineered_local_importance_values,
diff --git a/how-to-use-azureml/automated-machine-learning/regression/auto-ml-regression.ipynb b/how-to-use-azureml/automated-machine-learning/regression/auto-ml-regression.ipynb
index 0109754de..6e00c6ada 100644
--- a/how-to-use-azureml/automated-machine-learning/regression/auto-ml-regression.ipynb
+++ b/how-to-use-azureml/automated-machine-learning/regression/auto-ml-regression.ipynb
@@ -92,7 +92,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
@@ -115,7 +115,7 @@
         "output['Resource Group'] = ws.resource_group\n",
         "output['Location'] = ws.location\n",
         "output['Run History Name'] = experiment_name\n",
-        "pd.set_option('display.max_colwidth', -1)\n",
+        "pd.set_option('display.max_colwidth', None)\n",
         "outputDf = pd.DataFrame(data = output, index = [''])\n",
         "outputDf.T"
       ]
@@ -430,7 +430,7 @@
       "outputs": [],
       "source": [
         "%matplotlib inline\n",
-        "test_pred = plt.scatter(y_test, y_pred_test, color='')\n",
+        "test_pred = plt.scatter(y_test, y_pred_test, color=None)\n",
         "test_test = plt.scatter(y_test, y_test, color='g')\n",
         "plt.legend((test_pred, test_test), ('prediction', 'truth'), loc='upper left', fontsize=8)\n",
         "plt.show()"
diff --git a/how-to-use-azureml/deployment/deploy-to-local/register-model-deploy-local-advanced.ipynb b/how-to-use-azureml/deployment/deploy-to-local/register-model-deploy-local-advanced.ipynb
index 5684e0750..9095363a7 100644
--- a/how-to-use-azureml/deployment/deploy-to-local/register-model-deploy-local-advanced.ipynb
+++ b/how-to-use-azureml/deployment/deploy-to-local/register-model-deploy-local-advanced.ipynb
@@ -81,7 +81,7 @@
       "source": [
         "## Create trained model\n",
         "\n",
-        "For this example, we will train a small model on scikit-learn's [diabetes dataset](https://scikit-learn.org/stable/datasets/index.html#diabetes-dataset). "
+        "For this example, we will train a small model on scikit-learn's [diabetes dataset](https://scikit-learn.org/stable/datasets/toy_dataset.html#diabetes-dataset). "
       ]
     },
     {
@@ -263,7 +263,7 @@
         "\n",
         "# explicitly set base_image to None when setting base_dockerfile\n",
         "myenv.docker.base_image = None\n",
-        "myenv.docker.base_dockerfile = \"FROM mcr.microsoft.com/azureml/base:intelmpi2018.3-ubuntu16.04\\nRUN echo \\\"this is test\\\"\"\n",
+        "myenv.docker.base_dockerfile = \"FROM mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu20.04\\nRUN echo \\\"this is test\\\"\"\n",
         "myenv.inferencing_stack_version = \"latest\"\n",
         "\n",
         "inference_config = InferenceConfig(source_directory=source_directory,\n",
diff --git a/how-to-use-azureml/explain-model/azure-integration/gpu-explanation/train-explain-model-gpu-tree-explainer.ipynb b/how-to-use-azureml/explain-model/azure-integration/gpu-explanation/train-explain-model-gpu-tree-explainer.ipynb
index be9f0f593..d15fb62f9 100644
--- a/how-to-use-azureml/explain-model/azure-integration/gpu-explanation/train-explain-model-gpu-tree-explainer.ipynb
+++ b/how-to-use-azureml/explain-model/azure-integration/gpu-explanation/train-explain-model-gpu-tree-explainer.ipynb
@@ -106,7 +106,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
diff --git a/how-to-use-azureml/explain-model/azure-integration/remote-explanation/explain-model-on-amlcompute.yml b/how-to-use-azureml/explain-model/azure-integration/remote-explanation/explain-model-on-amlcompute.yml
index 33b489b5a..51aac531f 100644
--- a/how-to-use-azureml/explain-model/azure-integration/remote-explanation/explain-model-on-amlcompute.yml
+++ b/how-to-use-azureml/explain-model/azure-integration/remote-explanation/explain-model-on-amlcompute.yml
@@ -11,4 +11,4 @@ dependencies:
   - matplotlib
   - azureml-dataset-runtime
   - ipywidgets
-  - raiwidgets~=0.16.0
+  - raiwidgets~=0.17.0
diff --git a/how-to-use-azureml/explain-model/azure-integration/run-history/save-retrieve-explanations-run-history.yml b/how-to-use-azureml/explain-model/azure-integration/run-history/save-retrieve-explanations-run-history.yml
index 38102bf3a..2699ef633 100644
--- a/how-to-use-azureml/explain-model/azure-integration/run-history/save-retrieve-explanations-run-history.yml
+++ b/how-to-use-azureml/explain-model/azure-integration/run-history/save-retrieve-explanations-run-history.yml
@@ -10,4 +10,5 @@ dependencies:
   - ipython
   - matplotlib
   - ipywidgets
-  - raiwidgets~=0.16.0
+  - raiwidgets~=0.17.0
+  - packaging>=20.9
diff --git a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.ipynb b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.ipynb
index 4ba86a097..271b13bce 100644
--- a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.ipynb
+++ b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.ipynb
@@ -391,7 +391,7 @@
         "\n",
         "\n",
         "aciconfig = AciWebservice.deploy_configuration(cpu_cores=1, \n",
-        "                                               memory_gb=1, \n",
+        "                                               memory_gb=2, \n",
         "                                               tags={\"data\": \"IBM_Attrition\",  \n",
         "                                                     \"method\" : \"local_explanation\"}, \n",
         "                                               description='Get local explanations for IBM Employee Attrition data')\n",
diff --git a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.yml b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.yml
index 7407efc77..c238c081c 100644
--- a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.yml
+++ b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.yml
@@ -10,4 +10,5 @@ dependencies:
   - ipython
   - matplotlib
   - ipywidgets
-  - raiwidgets~=0.16.0
+  - raiwidgets~=0.17.0
+  - packaging>=20.9
diff --git a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-on-amlcompute-and-deploy.yml b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-on-amlcompute-and-deploy.yml
index 80f09a3e3..fdc16b92a 100644
--- a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-on-amlcompute-and-deploy.yml
+++ b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-on-amlcompute-and-deploy.yml
@@ -12,4 +12,4 @@ dependencies:
   - azureml-dataset-runtime
   - azureml-core
   - ipywidgets
-  - raiwidgets~=0.16.0
+  - raiwidgets~=0.17.0
diff --git a/how-to-use-azureml/ml-frameworks/fastai/fastai-with-custom-docker/fastai-with-custom-docker.ipynb b/how-to-use-azureml/ml-frameworks/fastai/fastai-with-custom-docker/fastai-with-custom-docker.ipynb
index f30e80395..aaef2d82b 100644
--- a/how-to-use-azureml/ml-frameworks/fastai/fastai-with-custom-docker/fastai-with-custom-docker.ipynb
+++ b/how-to-use-azureml/ml-frameworks/fastai/fastai-with-custom-docker/fastai-with-custom-docker.ipynb
@@ -199,7 +199,7 @@
         "Specify docker steps as a string:\n",
         "```python \n",
         "dockerfile = r\"\"\" \\\n",
-        "FROM mcr.microsoft.com/azureml/base:intelmpi2018.3-ubuntu16.04\n",
+        "FROM mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu20.04\n",
         "RUN echo \"Hello from custom container!\" \\\n",
         "\"\"\"\n",
         "```\n",
diff --git a/how-to-use-azureml/reinforcement-learning/cartpole-on-single-compute/cartpole_sc.ipynb b/how-to-use-azureml/reinforcement-learning/cartpole-on-single-compute/cartpole_sc.ipynb
index 1dd3bdf72..9d2929ee9 100644
--- a/how-to-use-azureml/reinforcement-learning/cartpole-on-single-compute/cartpole_sc.ipynb
+++ b/how-to-use-azureml/reinforcement-learning/cartpole-on-single-compute/cartpole_sc.ipynb
@@ -261,7 +261,7 @@
         "    \n",
         "    # 2.  Execute the Python process via the xvfb-run command to set up the headless display driver.\n",
         "    xvfb_env.python.user_managed_dependencies = True\n",
-        "    xvfb_env.python.interpreter_path = \"xvfb-run -s '-screen 0 640x480x16 -ac +extension GLX +render' python\"\n",
+        "    xvfb_env.python.interpreter_path = \"xvfb-run -s '-screen 0 640x480x24 -ac +extension GLX +render' python\"\n",
         "\n",
         "\n",
         "training_estimator = ReinforcementLearningEstimator(\n",
@@ -718,7 +718,7 @@
         "# 2.  Execute the Python process via the xvfb-run command to set up the headless display driver.\n",
         "xvfb_env.python.user_managed_dependencies = True\n",
         "if video_capture:\n",
-        "    xvfb_env.python.interpreter_path = \"xvfb-run -s '-screen 0 640x480x16 -ac +extension GLX +render' python\"\n",
+        "    xvfb_env.python.interpreter_path = \"xvfb-run -s '-screen 0 640x480x24 -ac +extension GLX +render' python\"\n",
         "\n",
         "\n",
         "rollout_estimator = ReinforcementLearningEstimator(\n",
diff --git a/how-to-use-azureml/reinforcement-learning/cartpole-on-single-compute/files/docker/Dockerfile b/how-to-use-azureml/reinforcement-learning/cartpole-on-single-compute/files/docker/Dockerfile
index 50df0fc76..d8e5a2836 100644
--- a/how-to-use-azureml/reinforcement-learning/cartpole-on-single-compute/files/docker/Dockerfile
+++ b/how-to-use-azureml/reinforcement-learning/cartpole-on-single-compute/files/docker/Dockerfile
@@ -26,6 +26,6 @@ RUN conda install -y conda=4.7.12 python=3.7 && conda clean -ay && \
     ray[rllib,dashboard,tune]==0.8.3 \
     psutil \
     setproctitle \
-    gym[atari] && \
+    gym[classic_control] && \
     conda install -y -c conda-forge x264='1!152.20180717' ffmpeg=4.0.2 && \
     conda install -c anaconda opencv
diff --git a/how-to-use-azureml/responsible-ai/auto-ml-regression-responsibleai/auto-ml-regression-responsibleai.ipynb b/how-to-use-azureml/responsible-ai/auto-ml-regression-responsibleai/auto-ml-regression-responsibleai.ipynb
index 479e71faa..915e01c88 100644
--- a/how-to-use-azureml/responsible-ai/auto-ml-regression-responsibleai/auto-ml-regression-responsibleai.ipynb
+++ b/how-to-use-azureml/responsible-ai/auto-ml-regression-responsibleai/auto-ml-regression-responsibleai.ipynb
@@ -95,7 +95,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
diff --git a/how-to-use-azureml/responsible-ai/visualize-upload-loan-decision/rai-loan-decision.yml b/how-to-use-azureml/responsible-ai/visualize-upload-loan-decision/rai-loan-decision.yml
index e97668491..c62b0bb15 100644
--- a/how-to-use-azureml/responsible-ai/visualize-upload-loan-decision/rai-loan-decision.yml
+++ b/how-to-use-azureml/responsible-ai/visualize-upload-loan-decision/rai-loan-decision.yml
@@ -8,5 +8,6 @@ dependencies:
   - matplotlib
   - azureml-dataset-runtime
   - ipywidgets
-  - raiwidgets~=0.16.0
+  - raiwidgets~=0.17.0
   - liac-arff
+  - packaging>=20.9
diff --git a/how-to-use-azureml/track-and-monitor-experiments/logging-api/logging-api.ipynb b/how-to-use-azureml/track-and-monitor-experiments/logging-api/logging-api.ipynb
index be9548436..3bb0066fc 100644
--- a/how-to-use-azureml/track-and-monitor-experiments/logging-api/logging-api.ipynb
+++ b/how-to-use-azureml/track-and-monitor-experiments/logging-api/logging-api.ipynb
@@ -100,7 +100,7 @@
         "\n",
         "# Check core SDK version number\n",
         "\n",
-        "print(\"This notebook was created using SDK version 1.38.0, you are currently running version\", azureml.core.VERSION)"
+        "print(\"This notebook was created using SDK version 1.39.0, you are currently running version\", azureml.core.VERSION)"
       ]
     },
     {
diff --git a/index.md b/index.md
index 0536b396a..a5fa04287 100644
--- a/index.md
+++ b/index.md
@@ -108,8 +108,8 @@ Machine Learning notebook samples and encourage efficient retrieval of topics an
 | [auto-ml-continuous-retraining](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/automated-machine-learning/continuous-retraining/auto-ml-continuous-retraining.ipynb) |  |  |  |  |  |  |
 | [auto-ml-regression-model-proxy](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb) |  |  |  |  |  |  |
 | [auto-ml-forecasting-backtest-many-models](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/automated-machine-learning/forecasting-backtest-many-models/auto-ml-forecasting-backtest-many-models.ipynb) |  |  |  |  |  |  |
-| [auto-ml-forecasting-beer-remote](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.ipynb) |  |  |  |  |  |  |
 | [auto-ml-forecasting-energy-demand](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/automated-machine-learning/forecasting-energy-demand/auto-ml-forecasting-energy-demand.ipynb) |  |  |  |  |  |  |
+| [auto-ml-forecasting-github-dau](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/automated-machine-learning/forecasting-github-dau/auto-ml-forecasting-github-dau.ipynb) |  |  |  |  |  |  |
 | [auto-ml-forecasting-hierarchical-timeseries](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/automated-machine-learning/forecasting-hierarchical-timeseries/auto-ml-forecasting-hierarchical-timeseries.ipynb) |  |  |  |  |  |  |
 | [auto-ml-forecasting-many-models](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/automated-machine-learning/forecasting-many-models/auto-ml-forecasting-many-models.ipynb) |  |  |  |  |  |  |
 | [auto-ml-forecasting-univariate-recipe-experiment-settings](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/automated-machine-learning/forecasting-recipes-univariate/auto-ml-forecasting-univariate-recipe-experiment-settings.ipynb) |  |  |  |  |  |  |
diff --git a/setup-environment/configuration.ipynb b/setup-environment/configuration.ipynb
index 664443702..60a068a93 100644
--- a/setup-environment/configuration.ipynb
+++ b/setup-environment/configuration.ipynb
@@ -102,7 +102,7 @@
       "source": [
         "import azureml.core\n",
         "\n",
-        "print(\"This notebook was created using version 1.38.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.39.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
diff --git a/tutorials/compute-instance-quickstarts/quickstart-azureml-in-10mins/quickstart-azureml-in-10mins.ipynb b/tutorials/compute-instance-quickstarts/quickstart-azureml-in-10mins/quickstart-azureml-in-10mins.ipynb
index b50c52665..8dacd74e3 100644
--- a/tutorials/compute-instance-quickstarts/quickstart-azureml-in-10mins/quickstart-azureml-in-10mins.ipynb
+++ b/tutorials/compute-instance-quickstarts/quickstart-azureml-in-10mins/quickstart-azureml-in-10mins.ipynb
@@ -19,7 +19,7 @@
       "source": [
         "# Quickstart: Train and deploy a model in Azure Machine Learning in 10 minutes\n",
         "\n",
-        "In this quickstart, learn how to get started with Azure Machine Learning. You'll train an image classification model using the [MNIST](https://azure.microsoft.com/services/open-datasets/catalog/mnist/) dataset.\n",
+        "In this quickstart, learn how to get started with Azure Machine Learning. You'll train an image classification model using the [MNIST](https://docs.microsoft.com/azure/open-datasets/dataset-mnist) dataset.\n",
         "\n",
         "You'll learn how to:\n",
         "\n",
@@ -280,7 +280,7 @@
         "# get a curated environment\n",
         "env = Environment.get(\n",
         "    workspace=ws, \n",
-        "    name=\"AzureML-sklearn-0.24.1-ubuntu18.04-py37-cpu-inference\",\n",
+        "    name=\"AzureML-sklearn-1.0-ubuntu20.04-py38-cpu\",\n",
         "    version=1\n",
         ")\n",
         "env.inferencing_stack_version='latest'\n",
diff --git a/tutorials/compute-instance-quickstarts/quickstart-azureml-python-sdk/quickstart-azureml-python-sdk.ipynb b/tutorials/compute-instance-quickstarts/quickstart-azureml-python-sdk/quickstart-azureml-python-sdk.ipynb
index fe3d35782..931e140ef 100644
--- a/tutorials/compute-instance-quickstarts/quickstart-azureml-python-sdk/quickstart-azureml-python-sdk.ipynb
+++ b/tutorials/compute-instance-quickstarts/quickstart-azureml-python-sdk/quickstart-azureml-python-sdk.ipynb
@@ -21,7 +21,7 @@
         "\n",
         "In this quickstart, you learn how to submit a batch training job using the Python SDK. In this example, we submit the job to the 'local' machine (the compute instance you are running this notebook on). However, you can use exactly the same method to submit the job to different compute targets (for example, AKS, Azure Machine Learning Compute Cluster, Synapse, etc) by changing a single line of code. A full list of support compute targets can be viewed [here](https://docs.microsoft.com/en-us/azure/machine-learning/concept-compute-target). \n",
         "\n",
-        "This quickstart trains a simple logistic regression using the [MNIST](https://azure.microsoft.com/services/open-datasets/catalog/mnist/) dataset and [scikit-learn](http://scikit-learn.org) with Azure Machine Learning.  MNIST is a popular dataset consisting of 70,000 grayscale images. Each image is a handwritten digit of 28x28 pixels, representing a number from 0 to 9. The goal is to create a multi-class classifier to identify the digit a given image represents. \n",
+        "This quickstart trains a simple logistic regression using the [MNIST](https://docs.microsoft.com/azure/open-datasets/dataset-mnist) dataset and [scikit-learn](http://scikit-learn.org) with Azure Machine Learning.  MNIST is a popular dataset consisting of 70,000 grayscale images. Each image is a handwritten digit of 28x28 pixels, representing a number from 0 to 9. The goal is to create a multi-class classifier to identify the digit a given image represents. \n",
         "\n",
         "You will learn how to:\n",
         "\n",
diff --git a/tutorials/image-classification-mnist-data/img-classification-part1-training.ipynb b/tutorials/image-classification-mnist-data/img-classification-part1-training.ipynb
index b0b11eb40..62e0ec1ae 100644
--- a/tutorials/image-classification-mnist-data/img-classification-part1-training.ipynb
+++ b/tutorials/image-classification-mnist-data/img-classification-part1-training.ipynb
@@ -17,7 +17,7 @@
         "\n",
         "In this tutorial, you train a machine learning model on remote compute resources. You'll use the training and deployment workflow for Azure Machine Learning service (preview) in a Python Jupyter notebook.  You can then use the notebook as a template to train your own machine learning model with your own data. This tutorial is **part one of a two-part tutorial series**.  \n",
         "\n",
-        "This tutorial trains a simple logistic regression using the [MNIST](https://azure.microsoft.com/services/open-datasets/catalog/mnist/) dataset and [scikit-learn](http://scikit-learn.org) with Azure Machine Learning.  MNIST is a popular dataset consisting of 70,000 grayscale images. Each image is a handwritten digit of 28x28 pixels, representing a number from 0 to 9. The goal is to create a multi-class classifier to identify the digit a given image represents. \n",
+        "This tutorial trains a simple logistic regression using the [MNIST](https://docs.microsoft.com/azure/open-datasets/dataset-mnist) dataset and [scikit-learn](http://scikit-learn.org) with Azure Machine Learning.  MNIST is a popular dataset consisting of 70,000 grayscale images. Each image is a handwritten digit of 28x28 pixels, representing a number from 0 to 9. The goal is to create a multi-class classifier to identify the digit a given image represents. \n",
         "\n",
         "Learn how to:\n",
         "\n",