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Merge pull request guipsamora#5 from mtd91429/chipotle
changed solutions to utilize pandas functionality @mtd91429 thank you for the contribution.
2 parents 6c5947f + 5b6e7ff commit 1849f10

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3 files changed

+103
-44
lines changed

‎01_Getting_&_Knowing_Your_Data/Chipotle/Exercise_with_Solutions.ipynb

Lines changed: 47 additions & 26 deletions
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@@ -473,7 +473,26 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Step 13. How much was the revenue for the period in the dataset?"
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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": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"dollarizer = lambda x: float(x[1:-1])\n",
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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 14. How much was the revenue for the period in the dataset?"
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]
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},
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{
@@ -484,28 +503,25 @@
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The revenue of the period was: $34500.16\n"
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]
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"data": {
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"text/plain": [
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"34500.16000000046"
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]
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},
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"execution_count": 130,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# create a list of prices\n",
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"prices = [float(value[1:-1]) for value in chipo.item_price] # strip the dollar sign and trailing space\n",
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"\n",
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"total = sum(prices) #sum the items\n",
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"\n",
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"\n",
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"print(\"The revenue of the period was: \" + \"${0:.2f}\".format(total))"
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"chipo.item_price.sum()"
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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 14. How many orders were made in the period?"
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"### Step 15. How many orders were made in the period?"
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]
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},
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{
@@ -527,15 +543,14 @@
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}
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],
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"source": [
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"orders = len((set([order for order in chipo.order_id])))\n",
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"orders"
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"chipo.order_id.value_counts().count()"
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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 15. What is the average amount per order?"
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"### Step 16. What is the average amount per order?"
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]
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},
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{
@@ -546,24 +561,30 @@
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The average order is: $18.81\n"
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]
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"data": {
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"text/plain": [
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"18.811428571428689"
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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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"avg_order = total / orders\n",
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"order_grouped = chipo.groupby(by=['order_id']).sum()\n",
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"order_grouped.mean()['item_price']\n",
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"\n",
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"# Or \n",
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"\n",
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"print \"The average order is: $%s\" % round(avg_order, 2)"
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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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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Step 16 How many different items are sold?"
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"### Step 17. How many different items are sold?"
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]
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},
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{
@@ -585,7 +606,7 @@
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}
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],
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"source": [
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"len(chipo.item_name.unique())"
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"chipo.item_name.value_counts().count()"
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]
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}
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],

‎01_Getting_&_Knowing_Your_Data/Chipotle/Exercises.ipynb

Lines changed: 20 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -197,7 +197,23 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Step 13. How much was the revenue for the period in the dataset?"
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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": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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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 14. How much was the revenue for the period in the dataset?"
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]
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},
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{
@@ -213,7 +229,7 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Step 14. How many orders were made in the period?"
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"### Step 15. How many orders were made in the period?"
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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 15. What is the average amount per order?"
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"### Step 16. What is the average amount per order?"
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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 16. How many different items are sold?"
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"### Step 17. How many different items are sold?"
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]
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},
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{

‎01_Getting_&_Knowing_Your_Data/Chipotle/Solutions.ipynb

Lines changed: 36 additions & 14 deletions
Original file line numberDiff line numberDiff line change
@@ -441,7 +441,23 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Step 13. How much was the revenue for the period in the dataset?"
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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": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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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 14. How much was the revenue for the period in the dataset?"
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]
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},
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{
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The revenue of the period was: $34500.16\n"
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]
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"data": {
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"text/plain": [
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"34500.16000000046"
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]
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},
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"execution_count": 130,
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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": []
@@ -465,7 +484,7 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Step 14. How many orders were made in the period?"
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"### Step 15. How many orders were made in the period?"
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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 15. What is the average amount per order?"
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"### Step 16. What is the average amount per order?"
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]
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},
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{
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The average order is: $18.81\n"
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]
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"data": {
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"text/plain": [
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"18.811428571428689"
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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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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Step 16 How many different items are sold?"
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"### Step 17. How many different items are sold?"
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]
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},
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{

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