Handling with Missing Values file finished.

Author: LimaOscarData

Handling_with_Missing_Values.py

@@ -1,6 +1,7 @@
 import pandas as pd
 import numpy as np
-import seaborn as sn
+import seaborn as sns
+import matplotlib.pyplot as plt
 
 id_no = ["P001","P002","P003","P004","P005","P006","P007","P008","P009","P010","P011"]
 gender=["M","F","M","F","M","F","M","F","M","F","M"]
@@ -699,7 +700,7 @@
 # where()
 # interpolate()
 
-print(df)
+# print(df)
 
 ########## a.Filling with a specific value :
 
@@ -1137,30 +1138,48 @@
 # 9   P010      F     FT   DS   NaN   7.0   125.0           FT         125.0
 # 10  P011      M     PT  AWS   6.0   9.0    59.0           PT          59.0
 
+######### Filling with interpolation ######################
+flights = sns.load_dataset('flights')
+# print(flights)
+#      year month  passengers
+# 0    1949   Jan         112
+# 1    1949   Feb         118
+# 2    1949   Mar         132
+# 3    1949   Apr         129
+# 4    1949   May         121
+# ..    ...   ...         ...
+# 139  1960   Aug         606
+# 140  1960   Sep         508
+# 141  1960   Oct         461
+# 142  1960   Nov         390
+# 143  1960   Dec         432
+#
+# [144 rows x 3 columns]
 
-# ------------------------------------------------------------
-# ------------------------------------------------------------
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+# print(flights.isnull().sum())
+# year          0
+# month         0
+# passengers    0
+# dtype: int64
+
+flights['passengers'].plot()
+# plt.show()
+
+flights_copy = flights.copy()
+flights_copy.loc[np.random.randint(1, 144, 20), 'passengers']=None
+# print(flights_copy.isnull().sum())
+# year           0
+# month          0
+# passengers    20
+# dtype: int64
+
+flights_copy['passengers'].plot()
+# plt.show()
+
+flights_copy['passengers'].interpolate().plot()
+# plt.show()
+
+flights['passengers'].plot()
+# plt.show()
+
+# ------------------------------------------------------------