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Merge branch 'TakaakiFuruse-fix-chap01-chipotle'
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‎01_Getting_&_Knowing_Your_Data/Chipotle/Exercise_with_Solutions.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": 25,
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"execution_count": 1,
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"metadata": {
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"collapsed": false
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},
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 2,
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"metadata": {
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"collapsed": false
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 3,
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"metadata": {
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"collapsed": false,
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"scrolled": false
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"9 [Fresh Tomato Salsa, [Rice, Black Beans, Pinto... $9.25 "
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]
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},
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"execution_count": 4,
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"chipo.head(10)\n",
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"# chipo['choice_description'][4]"
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"chipo.head(10)"
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]
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},
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{
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"### Step 5. What is the number of observations in the dataset?"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"4622"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Solution 1\n",
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"\n",
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"chipo.shape[0] # entries <= 4622 observations"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"dtypes: int64(2), object(3)\n",
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"memory usage: 180.6+ KB\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"4622"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"chipo.info()#\n",
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"\n",
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"# OR\n",
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"# Solution 2\n",
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"\n",
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"chipo.shape[0]\n",
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"# 4622 observations"
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"chipo.info() # entries <= 4622 observations"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Step 9. Which was the most ordered item? "
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"### Step 9. Which was the most-ordered item? "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 41,
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"execution_count": 9,
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"metadata": {
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"collapsed": false
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},
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"Chicken Bowl 713926 761"
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]
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},
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"execution_count": 41,
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"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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}
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Step 10. How many items were ordered?"
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"### Step 10. For the most-ordered item, how many items were ordered?"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"execution_count": 10,
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"metadata": {
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"collapsed": false
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},
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"Chicken Bowl 713926 761"
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]
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},
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"execution_count": 21,
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count": 23,
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"execution_count": 11,
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"metadata": {
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"collapsed": false
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},
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"[Diet Coke] 123455 159"
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]
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},
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"execution_count": 23,
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count": 42,
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"execution_count": 12,
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"metadata": {
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"collapsed": false
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},
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"4972"
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]
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},
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"execution_count": 42,
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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"### Step 13. Turn the item price into a float"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Step 13.a. Check the item price type"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 43,
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"execution_count": 13,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"dtype('O')"
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]
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},
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"execution_count": 13,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"chipo.item_price.dtype"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Step 13.b. Create a lambda function and change the type of item price"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {
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"collapsed": true
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},
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"chipo.item_price = chipo.item_price.apply(dollarizer)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Step 13.c. Check the item price type"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"dtype('float64')"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"chipo.item_price.dtype"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {
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"collapsed": false
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},
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},
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{
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"cell_type": "code",
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"execution_count": 130,
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"execution_count": 17,
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"metadata": {
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"collapsed": false
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},
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"1834"
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]
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},
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"execution_count": 130,
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"execution_count": 17,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count": 140,
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"execution_count": 18,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"21.394231"
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"18.81142857142869"
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]
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},
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"execution_count": 4,
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"execution_count": 18,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"chipo['revenue'] = chipo['quantity']* chipo['item_price']\n",
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"order_grouped = chipo.groupby(by=['order_id']).sum()\n",
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"order_grouped.mean()['revenue']\n",
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"\n",
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"# Solution 1\n",
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"\n",
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"# Or \n",
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"chipo['revenue'] = chipo['quantity'] * chipo['item_price']\n",
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"order_grouped = chipo.groupby(by=['order_id']).sum()\n",
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"order_grouped.mean()['item_price']"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"18.81142857142869"
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]
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},
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"execution_count": 19,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Solution 2\n",
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"\n",
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"#chipo.groupby(by=['order_id']).sum().mean()['item_price']"
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"chipo.groupby(by=['order_id']).sum().mean()['item_price']"
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]
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},
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{
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},
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{
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"cell_type": "code",
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"execution_count": 148,
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"execution_count": 20,
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"metadata": {
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"collapsed": false
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},
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"50"
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]
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},
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"execution_count": 148,
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"execution_count": 20,
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"metadata": {},
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"output_type": "execute_result"
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}
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"display_name": "Python [default]",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.12"
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}
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"nbformat": 4,

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