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fix: dates
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‎notebooks/sn03_aggregate_data.ipynb‎

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"cells": [
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{
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"cell_type": "code",
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"execution_count": 63,
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"execution_count": 74,
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"id": "d69d493a-0716-47e7-bc80-0ef36753fdf8",
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"metadata": {},
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"outputs": [],
@@ -54,7 +54,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 64,
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"execution_count": 75,
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"id": "7302bac8-3643-4701-a1af-ea028dc8af38",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": 65,
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"execution_count": 76,
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"id": "d93c4011-0731-4992-9863-c198d570e18e",
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"metadata": {},
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"outputs": [
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},
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{
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"cell_type": "code",
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"execution_count": 66,
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"execution_count": 77,
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"id": "5ed00545-9d1e-4521-9d44-c6da89d5e4e5",
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"metadata": {},
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"outputs": [
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},
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{
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"cell_type": "code",
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"execution_count": 67,
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"execution_count": 78,
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"id": "9c93b32b-443e-4321-80fa-3d46fa8a0b1d",
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"metadata": {},
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"outputs": [
@@ -570,7 +570,7 @@
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th>Date</th>\n",
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" <th></th>\n",
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" <th>Item</th>\n",
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" <th>Brand</th>\n",
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" <th>Price</th>\n",
@@ -580,7 +580,7 @@
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" <tr>\n",
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" <th>OrderNo</th>\n",
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" <th>Empno</th>\n",
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" <th></th>\n",
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" <th>Date</th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
@@ -592,7 +592,7 @@
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" <tr>\n",
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" <th>4626232</th>\n",
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" <th>9003</th>\n",
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" <td>2021-08-042021-08-04</td>\n",
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" <th>2021-08-04</th>\n",
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" <td>SocksJeans</td>\n",
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" <td>VansQuiksilver</td>\n",
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" <td>97.0</td>\n",
@@ -602,7 +602,7 @@
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" <tr>\n",
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" <th>4626377</th>\n",
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" <th>9003</th>\n",
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" <td>2021-08-052021-08-05</td>\n",
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" <th>2021-08-05</th>\n",
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" <td>HoodyCargo Shorts</td>\n",
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" <td>AnimalAnimal</td>\n",
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" <td>82.0</td>\n",
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" <tr>\n",
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" <th>4626412</th>\n",
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" <th>9004</th>\n",
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" <td>2021-08-05</td>\n",
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" <th>2021-08-05</th>\n",
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" <td>Shirt</td>\n",
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" <td>Volcom</td>\n",
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" <td>78.0</td>\n",
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" <tr>\n",
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" <th>4626490</th>\n",
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" <th>9004</th>\n",
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" <td>2021-08-062021-08-06</td>\n",
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" <th>2021-08-06</th>\n",
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" <td>Cargo ShortsSweater</td>\n",
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" <td>BillabongDickies</td>\n",
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" <td>110.0</td>\n",
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" <tr>\n",
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" <th>9423517</th>\n",
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" <th>9001</th>\n",
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" <td>2021-08-042021-08-04</td>\n",
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" <th>2021-08-04</th>\n",
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" <td>JeansJacket</td>\n",
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" <td>Rip CurlThe North Face</td>\n",
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" <td>199.0</td>\n",
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" <tr>\n",
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" <th>9423534</th>\n",
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" <th>9001</th>\n",
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" <td>2021-08-042021-08-04</td>\n",
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" <th>2021-08-04</th>\n",
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" <td>SocksSocks</td>\n",
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" <td>DCQuiksilver</td>\n",
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" <td>22.0</td>\n",
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" <tr>\n",
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" <th>9423679</th>\n",
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" <th>9002</th>\n",
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" <td>2021-08-05</td>\n",
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" <th>2021-08-05</th>\n",
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" <td>T-shirt</td>\n",
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" <td>Patagonia</td>\n",
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" <td>35.0</td>\n",
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" <tr>\n",
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" <th>9423783</th>\n",
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" <th>9002</th>\n",
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" <td>2021-08-062021-08-06</td>\n",
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" <th>2021-08-06</th>\n",
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" <td>Boxer ShortsShorts</td>\n",
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" <td>SuperdryGlobe</td>\n",
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" <td>56.0</td>\n",
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"</div>"
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],
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"text/plain": [
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" Date Item \\\n",
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"OrderNo Empno \n",
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"4626232 9003 2021-08-042021-08-04 SocksJeans \n",
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"4626377 9003 2021-08-052021-08-05 HoodyCargo Shorts \n",
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"4626412 9004 2021-08-05 Shirt \n",
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"4626490 9004 2021-08-062021-08-06 Cargo ShortsSweater \n",
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"9423517 9001 2021-08-042021-08-04 JeansJacket \n",
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"9423534 9001 2021-08-042021-08-04 SocksSocks \n",
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"9423679 9002 2021-08-05 T-shirt \n",
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"9423783 9002 2021-08-062021-08-06 Boxer ShortsShorts \n",
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" Item Brand Price \\\n",
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"OrderNo Empno Date \n",
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"4626232 9003 2021-08-04 SocksJeans VansQuiksilver 97.0 \n",
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"4626377 9003 2021-08-05 HoodyCargo Shorts AnimalAnimal 82.0 \n",
681+
"4626412 9004 2021-08-05 Shirt Volcom 78.0 \n",
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"4626490 9004 2021-08-06 Cargo ShortsSweater BillabongDickies 110.0 \n",
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"9423517 9001 2021-08-04 JeansJacket Rip CurlThe North Face 199.0 \n",
684+
"9423534 9001 2021-08-04 SocksSocks DCQuiksilver 22.0 \n",
685+
"9423679 9002 2021-08-05 T-shirt Patagonia 35.0 \n",
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"9423783 9002 2021-08-06 Boxer ShortsShorts SuperdryGlobe 56.0 \n",
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"\n",
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" Brand Price Quantity Total \n",
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"OrderNo Empno \n",
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"4626232 9003 VansQuiksilver 97.0 2 97.0 \n",
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"4626377 9003 AnimalAnimal 82.0 2 82.0 \n",
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"4626412 9004 Volcom 78.0 1 78.0 \n",
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"4626490 9004 BillabongDickies 110.0 2 110.0 \n",
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"9423517 9001 Rip CurlThe North Face 199.0 2 199.0 \n",
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"9423534 9001 DCQuiksilver 22.0 4 44.0 \n",
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"9423679 9002 Patagonia 35.0 1 35.0 \n",
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"9423783 9002 SuperdryGlobe 56.0 3 86.0 "
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" Quantity Total \n",
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"OrderNo Empno Date \n",
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"4626232 9003 2021-08-04 2 97.0 \n",
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"4626377 9003 2021-08-05 2 82.0 \n",
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"4626412 9004 2021-08-05 1 78.0 \n",
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"4626490 9004 2021-08-06 2 110.0 \n",
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"9423517 9001 2021-08-04 2 199.0 \n",
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"9423534 9001 2021-08-04 4 44.0 \n",
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"9423679 9002 2021-08-05 1 35.0 \n",
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"9423783 9002 2021-08-06 3 86.0 "
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]
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},
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"metadata": {},
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"source": [
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"# A new DataFrame grouping by Order can be created to sum the total for each order using `groupby`\n",
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"\n",
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"df_order_totals = df_sales.groupby(['OrderNo', 'Empno']).sum()\n",
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"df_order_totals = df_sales.groupby(['OrderNo', 'Empno', 'Date']).sum()\n",
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"\n",
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"display(df_order_totals)"
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]

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