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Gainsight/Scripts/Jupyter/Churned_Learners.ipynb

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Mostly worked on pandas and jupyter stuff. Made great progress analyzing churned customers.
2023-04-10 16:14:42 -04:00
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" <td>10,362</td>\n",
" <td>7,890</td>\n",
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" <td>8,177</td>\n",
" <td>8,468</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>4</td>\n",
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" <td>NaN</td>\n",
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" <td>386</td>\n",
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" <th>Portnoy, Messinger, Pearl &amp; Associates, Inc.</th>\n",
" <td>28</td>\n",
" <td>27</td>\n",
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" <td>17</td>\n",
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" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Safari Energy</th>\n",
" <td>2</td>\n",
" <td>37</td>\n",
" <td>19</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
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" <td>6</td>\n",
" <td>21.0</td>\n",
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" <td>7</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <th>Starwood Pet Travel</th>\n",
" <td>NaN</td>\n",
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" <th>Trax Technology Solutions Pte Ltd</th>\n",
" <td>381</td>\n",
" <td>677</td>\n",
" <td>583</td>\n",
" <td>671</td>\n",
" <td>515</td>\n",
" <td>380</td>\n",
" <td>181</td>\n",
" <td>449</td>\n",
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" <td>NaN</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>Uber London Limited (POOL)</th>\n",
" <td>721</td>\n",
" <td>775</td>\n",
" <td>825</td>\n",
" <td>606</td>\n",
" <td>578</td>\n",
" <td>501</td>\n",
" <td>497</td>\n",
" <td>543</td>\n",
" <td>628.0</td>\n",
" <td>505.0</td>\n",
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" <td>1,270</td>\n",
" <td>1,957</td>\n",
" <td>190.0</td>\n",
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" <th>Artsy</th>\n",
" <td>NaN</td>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" <td>20</td>\n",
" <td>8</td>\n",
" <td>7</td>\n",
" <td>4</td>\n",
" <td>3</td>\n",
" <td>4.0</td>\n",
" <td>NaN</td>\n",
" <td>10.0</td>\n",
" <td>9</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <th>BambooHR</th>\n",
" <td>2,766</td>\n",
" <td>2,895</td>\n",
" <td>2,633</td>\n",
" <td>2,378</td>\n",
" <td>2,263</td>\n",
" <td>2,143</td>\n",
" <td>2,060</td>\n",
" <td>587</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <th>BrightMove</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <tr>\n",
" <th>Cherokee Enterprises, Inc.</th>\n",
" <td>NaN</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>NaN</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Epiphany Healthcare</th>\n",
" <td>9</td>\n",
" <td>18</td>\n",
" <td>33</td>\n",
" <td>8</td>\n",
" <td>8</td>\n",
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" <td>13</td>\n",
" <td>6</td>\n",
" <td>2.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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"text/plain": [
" 2022-01 2022-02 2022-03 \n",
"Organization \n",
"Aquent 58 38 50 \\\n",
"BioLife Solutions, Inc. 11 7 4 \n",
"ZyXel Communications Inc 1 1 2 \n",
"BrightLine Eating Solutions LLC 10,362 7,890 7,272 \n",
"Casio America Inc NaN NaN NaN \n",
"Riviera Partners LLC 81 19 51 \n",
"Viveve NaN NaN NaN \n",
"connectRN Inc. 386 378 396 \n",
"Hammer Nutrition NaN 1 1 \n",
"National Campus and Community Radio Association 63 15 10 \n",
"Portnoy, Messinger, Pearl & Associates, Inc. 28 27 79 \n",
"Safari Energy 2 37 19 \n",
"Starwood Pet Travel NaN 1 4 \n",
"Trax Technology Solutions Pte Ltd 381 677 583 \n",
"Uber London Limited (POOL) 721 775 825 \n",
"Artsy NaN 5 5 \n",
"BambooHR 2,766 2,895 2,633 \n",
"BrightMove NaN NaN NaN \n",
"Cherokee Enterprises, Inc. NaN 1 2 \n",
"Epiphany Healthcare 9 18 33 \n",
"\n",
" 2022-04 2022-05 2022-06 \n",
"Organization \n",
"Aquent 50 39 36 \\\n",
"BioLife Solutions, Inc. 11 4 NaN \n",
"ZyXel Communications Inc 1 2 4 \n",
"BrightLine Eating Solutions LLC 8,177 8,468 7,524 \n",
"Casio America Inc NaN NaN 1 \n",
"Riviera Partners LLC 26 26 32 \n",
"Viveve NaN NaN 4 \n",
"connectRN Inc. 732 947 762 \n",
"Hammer Nutrition 2 7 5 \n",
"National Campus and Community Radio Association 4 8 2 \n",
"Portnoy, Messinger, Pearl & Associates, Inc. 17 1 3 \n",
"Safari Energy 2 1 38 \n",
"Starwood Pet Travel 22 2 1 \n",
"Trax Technology Solutions Pte Ltd 671 515 380 \n",
"Uber London Limited (POOL) 606 578 501 \n",
"Artsy 20 8 7 \n",
"BambooHR 2,378 2,263 2,143 \n",
"BrightMove NaN NaN NaN \n",
"Cherokee Enterprises, Inc. 2 NaN 1 \n",
"Epiphany Healthcare 8 8 5 \n",
"\n",
" 2022-07 2022-08 2022-09 \n",
"Organization \n",
"Aquent 46 46 43.0 \\\n",
"BioLife Solutions, Inc. NaN NaN NaN \n",
"ZyXel Communications Inc 2 2 1.0 \n",
"BrightLine Eating Solutions LLC 8,509 5,638 581.0 \n",
"Casio America Inc NaN NaN NaN \n",
"Riviera Partners LLC 79 68 35.0 \n",
"Viveve 1 NaN NaN \n",
"connectRN Inc. 1,203 889 438.0 \n",
"Hammer Nutrition 4 5 6.0 \n",
"National Campus and Community Radio Association 3 NaN 4.0 \n",
"Portnoy, Messinger, Pearl & Associates, Inc. 8 NaN 1.0 \n",
"Safari Energy 24 6 21.0 \n",
"Starwood Pet Travel 7 NaN NaN \n",
"Trax Technology Solutions Pte Ltd 181 449 12.0 \n",
"Uber London Limited (POOL) 497 543 628.0 \n",
"Artsy 4 3 4.0 \n",
"BambooHR 2,060 587 NaN \n",
"BrightMove NaN NaN NaN \n",
"Cherokee Enterprises, Inc. 2 NaN 2.0 \n",
"Epiphany Healthcare 13 28 14.0 \n",
"\n",
" 2022-10 2022-11 2022-12 \n",
"Organization \n",
"Aquent 27.0 24.0 26 \\\n",
"BioLife Solutions, Inc. NaN NaN NaN \n",
"ZyXel Communications Inc NaN NaN NaN \n",
"BrightLine Eating Solutions LLC NaN NaN NaN \n",
"Casio America Inc NaN NaN NaN \n",
"Riviera Partners LLC 23.0 33.0 25 \n",
"Viveve NaN NaN 19 \n",
"connectRN Inc. 178.0 115.0 214 \n",
"Hammer Nutrition 6.0 NaN NaN \n",
"National Campus and Community Radio Association 4.0 6.0 5 \n",
"Portnoy, Messinger, Pearl & Associates, Inc. NaN 1.0 1 \n",
"Safari Energy 35.0 10.0 7 \n",
"Starwood Pet Travel NaN NaN 2 \n",
"Trax Technology Solutions Pte Ltd NaN 1.0 1 \n",
"Uber London Limited (POOL) 505.0 650.0 1,270 \n",
"Artsy NaN 10.0 9 \n",
"BambooHR NaN NaN NaN \n",
"BrightMove NaN NaN NaN \n",
"Cherokee Enterprises, Inc. 1.0 2.0 NaN \n",
"Epiphany Healthcare 15.0 6.0 13 \n",
"\n",
" 2023-01 2023-02 2023-03 \n",
"Organization \n",
"Aquent 22 8.0 10.0 \\\n",
"BioLife Solutions, Inc. NaN NaN NaN \n",
"ZyXel Communications Inc NaN 1.0 1.0 \n",
"BrightLine Eating Solutions LLC NaN NaN NaN \n",
"Casio America Inc NaN NaN NaN \n",
"Riviera Partners LLC 75 71.0 29.0 \n",
"Viveve 3 NaN NaN \n",
"connectRN Inc. 92 165.0 NaN \n",
"Hammer Nutrition NaN NaN NaN \n",
"National Campus and Community Radio Association 5 2.0 NaN \n",
"Portnoy, Messinger, Pearl & Associates, Inc. 2 NaN NaN \n",
"Safari Energy 1 NaN NaN \n",
"Starwood Pet Travel NaN 2.0 NaN \n",
"Trax Technology Solutions Pte Ltd 1 NaN NaN \n",
"Uber London Limited (POOL) 1,957 190.0 NaN \n",
"Artsy NaN 1.0 NaN \n",
"BambooHR NaN NaN NaN \n",
"BrightMove NaN NaN NaN \n",
"Cherokee Enterprises, Inc. 1 NaN NaN \n",
"Epiphany Healthcare 6 2.0 NaN \n",
"\n",
" 2023-04 \n",
"Organization \n",
"Aquent 2.0 \n",
"BioLife Solutions, Inc. NaN \n",
"ZyXel Communications Inc NaN \n",
"BrightLine Eating Solutions LLC NaN \n",
"Casio America Inc NaN \n",
"Riviera Partners LLC 4.0 \n",
"Viveve NaN \n",
"connectRN Inc. NaN \n",
"Hammer Nutrition NaN \n",
"National Campus and Community Radio Association NaN \n",
"Portnoy, Messinger, Pearl & Associates, Inc. NaN \n",
"Safari Energy NaN \n",
"Starwood Pet Travel NaN \n",
"Trax Technology Solutions Pte Ltd NaN \n",
"Uber London Limited (POOL) NaN \n",
"Artsy NaN \n",
"BambooHR NaN \n",
"BrightMove NaN \n",
"Cherokee Enterprises, Inc. NaN \n",
"Epiphany Healthcare NaN "
]
},
"execution_count": 145,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib\n",
"import sketch\n",
"from sklearn.preprocessing import MinMaxScaler\n",
"cd = pd.read_csv(\"/Users/normrasmussen/Downloads/churned_analysis.csv\", index_col=0, header=[0])\n",
"cd.head(20)"
]
},
{
"cell_type": "code",
"execution_count": 146,
"metadata": {},
"outputs": [],
"source": [
"#cd.columns = cd.columns.map(''.join)\n",
"#cd.rename_axis('Organization').reset_index()\n",
"#cd.set_index(keys=cd.columns[1], inplace=True)\n",
"\n",
"#df = cd.iloc[0, 0]\n",
"#print(df)\n",
"\n",
"#columns = cd.columns\n",
"#print(columns)"
]
},
{
"cell_type": "code",
"execution_count": 147,
"id": "9b7b888f",
"metadata": {
"trusted": true
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" <th>2022-08</th>\n",
" <th>2022-09</th>\n",
" <th>2022-10</th>\n",
" <th>2022-11</th>\n",
" <th>2022-12</th>\n",
" <th>2023-01</th>\n",
" <th>2023-02</th>\n",
" <th>2023-03</th>\n",
" <th>2023-04</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Organization</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Aquent</th>\n",
" <td>58</td>\n",
" <td>38</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>39</td>\n",
" <td>36</td>\n",
" <td>46</td>\n",
" <td>46</td>\n",
" <td>43.0</td>\n",
" <td>27.0</td>\n",
" <td>24.0</td>\n",
" <td>26</td>\n",
" <td>22</td>\n",
" <td>8.0</td>\n",
" <td>10.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BioLife Solutions, Inc.</th>\n",
" <td>11</td>\n",
" <td>7</td>\n",
" <td>4</td>\n",
" <td>11</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ZyXel Communications Inc</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BrightLine Eating Solutions LLC</th>\n",
" <td>10362</td>\n",
" <td>7890</td>\n",
" <td>7272</td>\n",
" <td>8177</td>\n",
" <td>8468</td>\n",
" <td>7524</td>\n",
" <td>8509</td>\n",
" <td>5638</td>\n",
" <td>581.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Casio America Inc</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 2022-01 2022-02 2022-03 2022-04 2022-05 \n",
"Organization \n",
"Aquent 58 38 50 50 39 \\\n",
"BioLife Solutions, Inc. 11 7 4 11 4 \n",
"ZyXel Communications Inc 1 1 2 1 2 \n",
"BrightLine Eating Solutions LLC 10362 7890 7272 8177 8468 \n",
"Casio America Inc 0 0 0 0 0 \n",
"\n",
" 2022-06 2022-07 2022-08 2022-09 2022-10 \n",
"Organization \n",
"Aquent 36 46 46 43.0 27.0 \\\n",
"BioLife Solutions, Inc. 0 0 0 0.0 0.0 \n",
"ZyXel Communications Inc 4 2 2 1.0 0.0 \n",
"BrightLine Eating Solutions LLC 7524 8509 5638 581.0 0.0 \n",
"Casio America Inc 1 0 0 0.0 0.0 \n",
"\n",
" 2022-11 2022-12 2023-01 2023-02 2023-03 \n",
"Organization \n",
"Aquent 24.0 26 22 8.0 10.0 \\\n",
"BioLife Solutions, Inc. 0.0 0 0 0.0 0.0 \n",
"ZyXel Communications Inc 0.0 0 0 1.0 1.0 \n",
"BrightLine Eating Solutions LLC 0.0 0 0 0.0 0.0 \n",
"Casio America Inc 0.0 0 0 0.0 0.0 \n",
"\n",
" 2023-04 \n",
"Organization \n",
"Aquent 2.0 \n",
"BioLife Solutions, Inc. 0.0 \n",
"ZyXel Communications Inc 0.0 \n",
"BrightLine Eating Solutions LLC 0.0 \n",
"Casio America Inc 0.0 "
]
},
"execution_count": 147,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Replace all NaN values with 0\n",
"cd.fillna(0, inplace=True)\n",
"#cd.replace(np.inf, 0)\n",
"\n",
"# Remove all commas from strings\n",
"cd.replace(',','', regex=True, inplace=True)\n",
"# cd = cd.drop(['Churn Date', 'OrgID'], axis=1)\n",
"# cd.set_index(cd['Organization'])\n",
"cd.head(5)\n"
]
},
{
"cell_type": "code",
"execution_count": 148,
"id": "1d8b19f4",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>2022-01</th>\n",
" <th>2022-02</th>\n",
" <th>2022-03</th>\n",
" <th>2022-04</th>\n",
" <th>2022-05</th>\n",
" <th>2022-06</th>\n",
" <th>2022-07</th>\n",
" <th>2022-08</th>\n",
" <th>2022-09</th>\n",
" <th>2022-10</th>\n",
" <th>2022-11</th>\n",
" <th>2022-12</th>\n",
" <th>2023-01</th>\n",
" <th>2023-02</th>\n",
" <th>2023-03</th>\n",
" <th>2023-04</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Organization</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Aquent</th>\n",
" <td>58</td>\n",
" <td>38</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>39</td>\n",
" <td>36</td>\n",
" <td>46</td>\n",
" <td>46</td>\n",
" <td>43</td>\n",
" <td>27</td>\n",
" <td>24</td>\n",
" <td>26</td>\n",
" <td>22</td>\n",
" <td>8</td>\n",
" <td>10</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BioLife Solutions, Inc.</th>\n",
" <td>11</td>\n",
" <td>7</td>\n",
" <td>4</td>\n",
" <td>11</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ZyXel Communications Inc</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BrightLine Eating Solutions LLC</th>\n",
" <td>10362</td>\n",
" <td>7890</td>\n",
" <td>7272</td>\n",
" <td>8177</td>\n",
" <td>8468</td>\n",
" <td>7524</td>\n",
" <td>8509</td>\n",
" <td>5638</td>\n",
" <td>581</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Casio America Inc</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 2022-01 2022-02 2022-03 2022-04 2022-05 \n",
"Organization \n",
"Aquent 58 38 50 50 39 \\\n",
"BioLife Solutions, Inc. 11 7 4 11 4 \n",
"ZyXel Communications Inc 1 1 2 1 2 \n",
"BrightLine Eating Solutions LLC 10362 7890 7272 8177 8468 \n",
"Casio America Inc 0 0 0 0 0 \n",
"\n",
" 2022-06 2022-07 2022-08 2022-09 2022-10 \n",
"Organization \n",
"Aquent 36 46 46 43 27 \\\n",
"BioLife Solutions, Inc. 0 0 0 0 0 \n",
"ZyXel Communications Inc 4 2 2 1 0 \n",
"BrightLine Eating Solutions LLC 7524 8509 5638 581 0 \n",
"Casio America Inc 1 0 0 0 0 \n",
"\n",
" 2022-11 2022-12 2023-01 2023-02 2023-03 \n",
"Organization \n",
"Aquent 24 26 22 8 10 \\\n",
"BioLife Solutions, Inc. 0 0 0 0 0 \n",
"ZyXel Communications Inc 0 0 0 1 1 \n",
"BrightLine Eating Solutions LLC 0 0 0 0 0 \n",
"Casio America Inc 0 0 0 0 0 \n",
"\n",
" 2023-04 \n",
"Organization \n",
"Aquent 2 \n",
"BioLife Solutions, Inc. 0 \n",
"ZyXel Communications Inc 0 \n",
"BrightLine Eating Solutions LLC 0 \n",
"Casio America Inc 0 "
]
},
"execution_count": 148,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Convert all strings after the column 'Churn Data' to integers\n",
"for col in cd.columns[0:]:\n",
" cd[col] = cd[col].astype(int)\n",
"\n",
"cd.head()"
]
},
{
"cell_type": "code",
"execution_count": 149,
"id": "0c1ebbaa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2022-01 int64\n",
"2022-02 int64\n",
"2022-03 int64\n",
"2022-04 int64\n",
"2022-05 int64\n",
"2022-06 int64\n",
"2022-07 int64\n",
"2022-08 int64\n",
"2022-09 int64\n",
"2022-10 int64\n",
"2022-11 int64\n",
"2022-12 int64\n",
"2023-01 int64\n",
"2023-02 int64\n",
"2023-03 int64\n",
"2023-04 int64\n",
"dtype: object\n"
]
}
],
"source": [
"types = cd.dtypes\n",
"print(types)"
]
},
{
"cell_type": "code",
"execution_count": 117,
"id": "53e62d47",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div style=\"display:flex;flex-direction:row;justify-content:space-between;\">\n",
" <pre style=\"width: 100%; white-space: pre-wrap;\" id=\"7d44416c-7c88-4d28-96cc-73d3c9c5bafd\">\n",
"# Create a new dataframe to store the scaled values\n",
"scaled_df = pd.DataFrame()\n",
"\n",
"# Iterate through each row in the original dataframe\n",
"for index, row in cd.iterrows():\n",
" # Create a list to store the scaled values for each row\n",
" scaled_row = []\n",
" \n",
" # Iterate through each column in the row\n",
" for col in cd.columns:\n",
" # Calculate the min/max scale value for the column\n",
" min_val = row[col].min()\n",
" max_val = row[col].max()\n",
" \n",
" # Handle DivideByZero errors by setting the value to 0 if min and max are equal\n",
" if min_val == max_val:\n",
" scaled_val = 0\n",
" else:\n",
" scaled_val = (row[col] - min_val) / (max_val - min_val)\n",
"\n",
" # Append the scaled value to the list of scaled values for this row\n",
" scaled_row.append(scaled_val)\n",
"\n",
" # Add the list of scaled values to the new dataframe as a new row\n",
" scaled_df = scaled_df.append(pd.Series(scaled_row), ignore_index=True)\n",
"</pre>\n",
" <button style=\"height: fit-content;\" onclick=\"navigator.clipboard.writeText(JSON.parse(atob(`IlxuIyBDcmVhdGUgYSBuZXcgZGF0YWZyYW1lIHRvIHN0b3JlIHRoZSBzY2FsZWQgdmFsdWVzXG5zY2FsZWRfZGYgPSBwZC5EYXRhRnJhbWUoKVxuXG4jIEl0ZXJhdGUgdGhyb3VnaCBlYWNoIHJvdyBpbiB0aGUgb3JpZ2luYWwgZGF0YWZyYW1lXG5mb3IgaW5kZXgsIHJvdyBpbiBjZC5pdGVycm93cygpOlxuICAgICMgQ3JlYXRlIGEgbGlzdCB0byBzdG9yZSB0aGUgc2NhbGVkIHZhbHVlcyBmb3IgZWFjaCByb3dcbiAgICBzY2FsZWRfcm93ID0gW11cbiAgICBcbiAgICAjIEl0ZXJhdGUgdGhyb3VnaCBlYWNoIGNvbHVtbiBpbiB0aGUgcm93XG4gICAgZm9yIGNvbCBpbiBjZC5jb2x1bW5zOlxuICAgICAgICAjIENhbGN1bGF0ZSB0aGUgbWluL21heCBzY2FsZSB2YWx1ZSBmb3IgdGhlIGNvbHVtblxuICAgICAgICBtaW5fdmFsID0gcm93W2NvbF0ubWluKClcbiAgICAgICAgbWF4X3ZhbCA9IHJvd1tjb2xdLm1heCgpXG4gICAgICAgIFxuICAgICAgICAjIEhhbmRsZSBEaXZpZGVCeVplcm8gZXJyb3JzIGJ5IHNldHRpbmcgdGhlIHZhbHVlIHRvIDAgaWYgbWluIGFuZCBtYXggYXJlIGVxdWFsXG4gICAgICAgIGlmIG1pbl92YWwgPT0gbWF4X3ZhbDpcbiAgICAgICAgICAgIHNjYWxlZF92YWwgPSAwXG4gICAgICAgIGVsc2U6XG4gICAgICAgICAgICBzY2FsZWRfdmFsID0gKHJvd1tjb2xdIC0gbWluX3ZhbCkgLyAobWF4X3ZhbCAtIG1pbl92YWwpXG5cbiAgICAgICAgIyBBcHBlbmQgdGhlIHNjYWxlZCB2YWx1ZSB0byB0aGUgbGlzdCBvZiBzY2FsZWQgdmFsdWVzIGZvciB0aGlzIHJvd1xuICAgICAgICBzY2FsZWRfcm93LmFwcGVuZChzY2FsZWRfdmFsKVxuXG4gICAgIyBBZGQgdGhlIGxpc3Qgb2Ygc2NhbGVkIHZhbHVlcyB0byB0aGUgbmV3IGRhdGFmcmFtZSBhcyBhIG5ldyByb3dcbiAgICBzY2FsZWRfZGYgPSBzY2FsZWRfZGYuYXBwZW5kKHBkLlNlcmllcyhzY2FsZWRfcm93KSwgaWdub3JlX2luZGV4PVRydWUpXG4i`)))\">Copy</button>\n",
" </div>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cd.sketch.howto(\"Apply min/max scale with each min/max value being unique to each row. Handled DivideByZero errors by having the value equal 0.\")"
]
},
{
"cell_type": "code",
"execution_count": 150,
"id": "1563f3f5",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"\n",
" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>2022-01</th>\n",
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" </tr>\n",
" </thead>\n",
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"</table>\n",
"</div>"
],
"text/plain": [
"Empty DataFrame\n",
"Columns: [2022-01, 2022-02, 2022-03, 2022-04, 2022-05, 2022-06, 2022-07, 2022-08, 2022-09, 2022-10, 2022-11, 2022-12, 2023-01, 2023-02, 2023-03, 2023-04]\n",
"Index: []"
]
},
"execution_count": 150,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Create a new dataframe to store the scaled values\n",
"heading = cd.columns[0:]\n",
"scaled_df = pd.DataFrame(columns = heading)\n",
"scaled_df.head()\n"
]
},
{
"cell_type": "code",
"execution_count": 151,
"id": "391171e2",
"metadata": {},
"outputs": [
{
"data": {
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" </tr>\n",
" <tr>\n",
" <th>Organization</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
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" </thead>\n",
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" <td>1.000000</td>\n",
" <td>0.642857</td>\n",
" <td>0.857143</td>\n",
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" <td>0.785714</td>\n",
" <td>0.732143</td>\n",
" <td>0.446429</td>\n",
" <td>0.392857</td>\n",
" <td>0.428571</td>\n",
" <td>0.357143</td>\n",
" <td>0.107143</td>\n",
" <td>0.142857</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BioLife Solutions, Inc.</th>\n",
" <td>1.000000</td>\n",
" <td>0.636364</td>\n",
" <td>0.363636</td>\n",
" <td>1.000000</td>\n",
" <td>0.363636</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ZyXel Communications Inc</th>\n",
" <td>0.250000</td>\n",
" <td>0.250000</td>\n",
" <td>0.500000</td>\n",
" <td>0.250000</td>\n",
" <td>0.500000</td>\n",
" <td>1.000000</td>\n",
" <td>0.500000</td>\n",
" <td>0.500000</td>\n",
" <td>0.250000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.250000</td>\n",
" <td>0.250000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BrightLine Eating Solutions LLC</th>\n",
" <td>1.000000</td>\n",
" <td>0.761436</td>\n",
" <td>0.701795</td>\n",
" <td>0.789133</td>\n",
" <td>0.817217</td>\n",
" <td>0.726115</td>\n",
" <td>0.821174</td>\n",
" <td>0.544103</td>\n",
" <td>0.056070</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Casio America Inc</th>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Riviera Partners LLC</th>\n",
" <td>1.000000</td>\n",
" <td>0.194805</td>\n",
" <td>0.610390</td>\n",
" <td>0.285714</td>\n",
" <td>0.285714</td>\n",
" <td>0.363636</td>\n",
" <td>0.974026</td>\n",
" <td>0.831169</td>\n",
" <td>0.402597</td>\n",
" <td>0.246753</td>\n",
" <td>0.376623</td>\n",
" <td>0.272727</td>\n",
" <td>0.922078</td>\n",
" <td>0.870130</td>\n",
" <td>0.324675</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Viveve</th>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.210526</td>\n",
" <td>0.052632</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.157895</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>connectRN Inc.</th>\n",
" <td>0.320865</td>\n",
" <td>0.314214</td>\n",
" <td>0.329177</td>\n",
" <td>0.608479</td>\n",
" <td>0.787199</td>\n",
" <td>0.633416</td>\n",
" <td>1.000000</td>\n",
" <td>0.738986</td>\n",
" <td>0.364090</td>\n",
" <td>0.147963</td>\n",
" <td>0.095594</td>\n",
" <td>0.177889</td>\n",
" <td>0.076475</td>\n",
" <td>0.137157</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Hammer Nutrition</th>\n",
" <td>0.000000</td>\n",
" <td>0.142857</td>\n",
" <td>0.142857</td>\n",
" <td>0.285714</td>\n",
" <td>1.000000</td>\n",
" <td>0.714286</td>\n",
" <td>0.571429</td>\n",
" <td>0.714286</td>\n",
" <td>0.857143</td>\n",
" <td>0.857143</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>National Campus and Community Radio Association</th>\n",
" <td>1.000000</td>\n",
" <td>0.238095</td>\n",
" <td>0.158730</td>\n",
" <td>0.063492</td>\n",
" <td>0.126984</td>\n",
" <td>0.031746</td>\n",
" <td>0.047619</td>\n",
" <td>0.000000</td>\n",
" <td>0.063492</td>\n",
" <td>0.063492</td>\n",
" <td>0.095238</td>\n",
" <td>0.079365</td>\n",
" <td>0.079365</td>\n",
" <td>0.031746</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Portnoy, Messinger, Pearl &amp; Associates, Inc.</th>\n",
" <td>0.354430</td>\n",
" <td>0.341772</td>\n",
" <td>1.000000</td>\n",
" <td>0.215190</td>\n",
" <td>0.012658</td>\n",
" <td>0.037975</td>\n",
" <td>0.101266</td>\n",
" <td>0.000000</td>\n",
" <td>0.012658</td>\n",
" <td>0.000000</td>\n",
" <td>0.012658</td>\n",
" <td>0.012658</td>\n",
" <td>0.025316</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Safari Energy</th>\n",
" <td>0.052632</td>\n",
" <td>0.973684</td>\n",
" <td>0.500000</td>\n",
" <td>0.052632</td>\n",
" <td>0.026316</td>\n",
" <td>1.000000</td>\n",
" <td>0.631579</td>\n",
" <td>0.157895</td>\n",
" <td>0.552632</td>\n",
" <td>0.921053</td>\n",
" <td>0.263158</td>\n",
" <td>0.184211</td>\n",
" <td>0.026316</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Starwood Pet Travel</th>\n",
" <td>0.000000</td>\n",
" <td>0.045455</td>\n",
" <td>0.181818</td>\n",
" <td>1.000000</td>\n",
" <td>0.090909</td>\n",
" <td>0.045455</td>\n",
" <td>0.318182</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.090909</td>\n",
" <td>0.000000</td>\n",
" <td>0.090909</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Trax Technology Solutions Pte Ltd</th>\n",
" <td>0.562777</td>\n",
" <td>1.000000</td>\n",
" <td>0.861152</td>\n",
" <td>0.991137</td>\n",
" <td>0.760709</td>\n",
" <td>0.561300</td>\n",
" <td>0.267356</td>\n",
" <td>0.663220</td>\n",
" <td>0.017725</td>\n",
" <td>0.000000</td>\n",
" <td>0.001477</td>\n",
" <td>0.001477</td>\n",
" <td>0.001477</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Uber London Limited (POOL)</th>\n",
" <td>0.368421</td>\n",
" <td>0.396014</td>\n",
" <td>0.421564</td>\n",
" <td>0.309658</td>\n",
" <td>0.295350</td>\n",
" <td>0.256004</td>\n",
" <td>0.253960</td>\n",
" <td>0.277466</td>\n",
" <td>0.320899</td>\n",
" <td>0.258048</td>\n",
" <td>0.332141</td>\n",
" <td>0.648952</td>\n",
" <td>1.000000</td>\n",
" <td>0.097087</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Artsy</th>\n",
" <td>0.000000</td>\n",
" <td>0.250000</td>\n",
" <td>0.250000</td>\n",
" <td>1.000000</td>\n",
" <td>0.400000</td>\n",
" <td>0.350000</td>\n",
" <td>0.200000</td>\n",
" <td>0.150000</td>\n",
" <td>0.200000</td>\n",
" <td>0.000000</td>\n",
" <td>0.500000</td>\n",
" <td>0.450000</td>\n",
" <td>0.000000</td>\n",
" <td>0.050000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BambooHR</th>\n",
" <td>0.955440</td>\n",
" <td>1.000000</td>\n",
" <td>0.909499</td>\n",
" <td>0.821416</td>\n",
" <td>0.781693</td>\n",
" <td>0.740242</td>\n",
" <td>0.711572</td>\n",
" <td>0.202763</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BrightMove</th>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Cherokee Enterprises, Inc.</th>\n",
" <td>0.000000</td>\n",
" <td>0.500000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.500000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.500000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.500000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Epiphany Healthcare</th>\n",
" <td>0.272727</td>\n",
" <td>0.545455</td>\n",
" <td>1.000000</td>\n",
" <td>0.242424</td>\n",
" <td>0.242424</td>\n",
" <td>0.151515</td>\n",
" <td>0.393939</td>\n",
" <td>0.848485</td>\n",
" <td>0.424242</td>\n",
" <td>0.454545</td>\n",
" <td>0.181818</td>\n",
" <td>0.393939</td>\n",
" <td>0.181818</td>\n",
" <td>0.060606</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>H1 Insights, Inc.</th>\n",
" <td>0.797468</td>\n",
" <td>1.000000</td>\n",
" <td>0.860759</td>\n",
" <td>0.405063</td>\n",
" <td>0.474684</td>\n",
" <td>0.607595</td>\n",
" <td>0.525316</td>\n",
" <td>0.398734</td>\n",
" <td>0.240506</td>\n",
" <td>0.082278</td>\n",
" <td>0.063291</td>\n",
" <td>0.088608</td>\n",
" <td>0.082278</td>\n",
" <td>0.018987</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Health Current</th>\n",
" <td>1.000000</td>\n",
" <td>0.500000</td>\n",
" <td>0.250000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.250000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Innovaccer Inc.</th>\n",
" <td>0.952830</td>\n",
" <td>1.000000</td>\n",
" <td>0.787736</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Kinetica</th>\n",
" <td>0.619048</td>\n",
" <td>0.476190</td>\n",
" <td>0.285714</td>\n",
" <td>0.142857</td>\n",
" <td>0.333333</td>\n",
" <td>1.000000</td>\n",
" <td>0.095238</td>\n",
" <td>0.238095</td>\n",
" <td>0.380952</td>\n",
" <td>0.238095</td>\n",
" <td>0.190476</td>\n",
" <td>0.380952</td>\n",
" <td>0.095238</td>\n",
" <td>0.095238</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Minga</th>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Renu Contracting Restoration</th>\n",
" <td>0.101523</td>\n",
" <td>1.000000</td>\n",
" <td>0.121827</td>\n",
" <td>0.045685</td>\n",
" <td>0.116751</td>\n",
" <td>0.106599</td>\n",
" <td>0.192893</td>\n",
" <td>0.076142</td>\n",
" <td>0.020305</td>\n",
" <td>0.050761</td>\n",
" <td>0.010152</td>\n",
" <td>0.015228</td>\n",
" <td>0.020305</td>\n",
" <td>0.020305</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Velocity Risk Underwriters, LLC</th>\n",
" <td>0.226562</td>\n",
" <td>0.039062</td>\n",
" <td>0.054688</td>\n",
" <td>0.070312</td>\n",
" <td>0.093750</td>\n",
" <td>0.156250</td>\n",
" <td>0.031250</td>\n",
" <td>0.296875</td>\n",
" <td>0.078125</td>\n",
" <td>0.054688</td>\n",
" <td>0.117188</td>\n",
" <td>0.773438</td>\n",
" <td>1.000000</td>\n",
" <td>0.085938</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 2022-01 2022-02 2022-03 \n",
"Organization \n",
"Aquent 1.000000 0.642857 0.857143 \\\n",
"BioLife Solutions, Inc. 1.000000 0.636364 0.363636 \n",
"ZyXel Communications Inc 0.250000 0.250000 0.500000 \n",
"BrightLine Eating Solutions LLC 1.000000 0.761436 0.701795 \n",
"Casio America Inc 0.000000 0.000000 0.000000 \n",
"Riviera Partners LLC 1.000000 0.194805 0.610390 \n",
"Viveve 0.000000 0.000000 0.000000 \n",
"connectRN Inc. 0.320865 0.314214 0.329177 \n",
"Hammer Nutrition 0.000000 0.142857 0.142857 \n",
"National Campus and Community Radio Association 1.000000 0.238095 0.158730 \n",
"Portnoy, Messinger, Pearl & Associates, Inc. 0.354430 0.341772 1.000000 \n",
"Safari Energy 0.052632 0.973684 0.500000 \n",
"Starwood Pet Travel 0.000000 0.045455 0.181818 \n",
"Trax Technology Solutions Pte Ltd 0.562777 1.000000 0.861152 \n",
"Uber London Limited (POOL) 0.368421 0.396014 0.421564 \n",
"Artsy 0.000000 0.250000 0.250000 \n",
"BambooHR 0.955440 1.000000 0.909499 \n",
"BrightMove 0.000000 0.000000 0.000000 \n",
"Cherokee Enterprises, Inc. 0.000000 0.500000 1.000000 \n",
"Epiphany Healthcare 0.272727 0.545455 1.000000 \n",
"H1 Insights, Inc. 0.797468 1.000000 0.860759 \n",
"Health Current 1.000000 0.500000 0.250000 \n",
"Innovaccer Inc. 0.952830 1.000000 0.787736 \n",
"Kinetica 0.619048 0.476190 0.285714 \n",
"Minga 0.000000 0.000000 0.000000 \n",
"Renu Contracting Restoration 0.101523 1.000000 0.121827 \n",
"Velocity Risk Underwriters, LLC 0.226562 0.039062 0.054688 \n",
"\n",
" 2022-04 2022-05 2022-06 \n",
"Organization \n",
"Aquent 0.857143 0.660714 0.607143 \\\n",
"BioLife Solutions, Inc. 1.000000 0.363636 0.000000 \n",
"ZyXel Communications Inc 0.250000 0.500000 1.000000 \n",
"BrightLine Eating Solutions LLC 0.789133 0.817217 0.726115 \n",
"Casio America Inc 0.000000 0.000000 1.000000 \n",
"Riviera Partners LLC 0.285714 0.285714 0.363636 \n",
"Viveve 0.000000 0.000000 0.210526 \n",
"connectRN Inc. 0.608479 0.787199 0.633416 \n",
"Hammer Nutrition 0.285714 1.000000 0.714286 \n",
"National Campus and Community Radio Association 0.063492 0.126984 0.031746 \n",
"Portnoy, Messinger, Pearl & Associates, Inc. 0.215190 0.012658 0.037975 \n",
"Safari Energy 0.052632 0.026316 1.000000 \n",
"Starwood Pet Travel 1.000000 0.090909 0.045455 \n",
"Trax Technology Solutions Pte Ltd 0.991137 0.760709 0.561300 \n",
"Uber London Limited (POOL) 0.309658 0.295350 0.256004 \n",
"Artsy 1.000000 0.400000 0.350000 \n",
"BambooHR 0.821416 0.781693 0.740242 \n",
"BrightMove 0.000000 0.000000 0.000000 \n",
"Cherokee Enterprises, Inc. 1.000000 0.000000 0.500000 \n",
"Epiphany Healthcare 0.242424 0.242424 0.151515 \n",
"H1 Insights, Inc. 0.405063 0.474684 0.607595 \n",
"Health Current 0.000000 0.000000 0.000000 \n",
"Innovaccer Inc. 0.000000 0.000000 0.000000 \n",
"Kinetica 0.142857 0.333333 1.000000 \n",
"Minga 0.000000 0.000000 0.000000 \n",
"Renu Contracting Restoration 0.045685 0.116751 0.106599 \n",
"Velocity Risk Underwriters, LLC 0.070312 0.093750 0.156250 \n",
"\n",
" 2022-07 2022-08 2022-09 \n",
"Organization \n",
"Aquent 0.785714 0.785714 0.732143 \\\n",
"BioLife Solutions, Inc. 0.000000 0.000000 0.000000 \n",
"ZyXel Communications Inc 0.500000 0.500000 0.250000 \n",
"BrightLine Eating Solutions LLC 0.821174 0.544103 0.056070 \n",
"Casio America Inc 0.000000 0.000000 0.000000 \n",
"Riviera Partners LLC 0.974026 0.831169 0.402597 \n",
"Viveve 0.052632 0.000000 0.000000 \n",
"connectRN Inc. 1.000000 0.738986 0.364090 \n",
"Hammer Nutrition 0.571429 0.714286 0.857143 \n",
"National Campus and Community Radio Association 0.047619 0.000000 0.063492 \n",
"Portnoy, Messinger, Pearl & Associates, Inc. 0.101266 0.000000 0.012658 \n",
"Safari Energy 0.631579 0.157895 0.552632 \n",
"Starwood Pet Travel 0.318182 0.000000 0.000000 \n",
"Trax Technology Solutions Pte Ltd 0.267356 0.663220 0.017725 \n",
"Uber London Limited (POOL) 0.253960 0.277466 0.320899 \n",
"Artsy 0.200000 0.150000 0.200000 \n",
"BambooHR 0.711572 0.202763 0.000000 \n",
"BrightMove 0.000000 0.000000 0.000000 \n",
"Cherokee Enterprises, Inc. 1.000000 0.000000 1.000000 \n",
"Epiphany Healthcare 0.393939 0.848485 0.424242 \n",
"H1 Insights, Inc. 0.525316 0.398734 0.240506 \n",
"Health Current 0.000000 0.000000 0.000000 \n",
"Innovaccer Inc. 0.000000 0.000000 0.000000 \n",
"Kinetica 0.095238 0.238095 0.380952 \n",
"Minga 0.000000 0.000000 0.000000 \n",
"Renu Contracting Restoration 0.192893 0.076142 0.020305 \n",
"Velocity Risk Underwriters, LLC 0.031250 0.296875 0.078125 \n",
"\n",
" 2022-10 2022-11 2022-12 \n",
"Organization \n",
"Aquent 0.446429 0.392857 0.428571 \\\n",
"BioLife Solutions, Inc. 0.000000 0.000000 0.000000 \n",
"ZyXel Communications Inc 0.000000 0.000000 0.000000 \n",
"BrightLine Eating Solutions LLC 0.000000 0.000000 0.000000 \n",
"Casio America Inc 0.000000 0.000000 0.000000 \n",
"Riviera Partners LLC 0.246753 0.376623 0.272727 \n",
"Viveve 0.000000 0.000000 1.000000 \n",
"connectRN Inc. 0.147963 0.095594 0.177889 \n",
"Hammer Nutrition 0.857143 0.000000 0.000000 \n",
"National Campus and Community Radio Association 0.063492 0.095238 0.079365 \n",
"Portnoy, Messinger, Pearl & Associates, Inc. 0.000000 0.012658 0.012658 \n",
"Safari Energy 0.921053 0.263158 0.184211 \n",
"Starwood Pet Travel 0.000000 0.000000 0.090909 \n",
"Trax Technology Solutions Pte Ltd 0.000000 0.001477 0.001477 \n",
"Uber London Limited (POOL) 0.258048 0.332141 0.648952 \n",
"Artsy 0.000000 0.500000 0.450000 \n",
"BambooHR 0.000000 0.000000 0.000000 \n",
"BrightMove 0.000000 0.000000 0.000000 \n",
"Cherokee Enterprises, Inc. 0.500000 1.000000 0.000000 \n",
"Epiphany Healthcare 0.454545 0.181818 0.393939 \n",
"H1 Insights, Inc. 0.082278 0.063291 0.088608 \n",
"Health Current 0.000000 0.000000 0.000000 \n",
"Innovaccer Inc. 0.000000 0.000000 0.000000 \n",
"Kinetica 0.238095 0.190476 0.380952 \n",
"Minga 0.000000 0.000000 0.000000 \n",
"Renu Contracting Restoration 0.050761 0.010152 0.015228 \n",
"Velocity Risk Underwriters, LLC 0.054688 0.117188 0.773438 \n",
"\n",
" 2023-01 2023-02 2023-03 \n",
"Organization \n",
"Aquent 0.357143 0.107143 0.142857 \\\n",
"BioLife Solutions, Inc. 0.000000 0.000000 0.000000 \n",
"ZyXel Communications Inc 0.000000 0.250000 0.250000 \n",
"BrightLine Eating Solutions LLC 0.000000 0.000000 0.000000 \n",
"Casio America Inc 0.000000 0.000000 0.000000 \n",
"Riviera Partners LLC 0.922078 0.870130 0.324675 \n",
"Viveve 0.157895 0.000000 0.000000 \n",
"connectRN Inc. 0.076475 0.137157 0.000000 \n",
"Hammer Nutrition 0.000000 0.000000 0.000000 \n",
"National Campus and Community Radio Association 0.079365 0.031746 0.000000 \n",
"Portnoy, Messinger, Pearl & Associates, Inc. 0.025316 0.000000 0.000000 \n",
"Safari Energy 0.026316 0.000000 0.000000 \n",
"Starwood Pet Travel 0.000000 0.090909 0.000000 \n",
"Trax Technology Solutions Pte Ltd 0.001477 0.000000 0.000000 \n",
"Uber London Limited (POOL) 1.000000 0.097087 0.000000 \n",
"Artsy 0.000000 0.050000 0.000000 \n",
"BambooHR 0.000000 0.000000 0.000000 \n",
"BrightMove 0.000000 0.000000 0.000000 \n",
"Cherokee Enterprises, Inc. 0.500000 0.000000 0.000000 \n",
"Epiphany Healthcare 0.181818 0.060606 0.000000 \n",
"H1 Insights, Inc. 0.082278 0.018987 0.000000 \n",
"Health Current 0.250000 0.000000 0.000000 \n",
"Innovaccer Inc. 0.000000 0.000000 0.000000 \n",
"Kinetica 0.095238 0.095238 0.000000 \n",
"Minga 0.000000 1.000000 1.000000 \n",
"Renu Contracting Restoration 0.020305 0.020305 0.000000 \n",
"Velocity Risk Underwriters, LLC 1.000000 0.085938 0.000000 \n",
"\n",
" 2023-04 \n",
"Organization \n",
"Aquent 0.0 \n",
"BioLife Solutions, Inc. 0.0 \n",
"ZyXel Communications Inc 0.0 \n",
"BrightLine Eating Solutions LLC 0.0 \n",
"Casio America Inc 0.0 \n",
"Riviera Partners LLC 0.0 \n",
"Viveve 0.0 \n",
"connectRN Inc. 0.0 \n",
"Hammer Nutrition 0.0 \n",
"National Campus and Community Radio Association 0.0 \n",
"Portnoy, Messinger, Pearl & Associates, Inc. 0.0 \n",
"Safari Energy 0.0 \n",
"Starwood Pet Travel 0.0 \n",
"Trax Technology Solutions Pte Ltd 0.0 \n",
"Uber London Limited (POOL) 0.0 \n",
"Artsy 0.0 \n",
"BambooHR 0.0 \n",
"BrightMove 0.0 \n",
"Cherokee Enterprises, Inc. 0.0 \n",
"Epiphany Healthcare 0.0 \n",
"H1 Insights, Inc. 0.0 \n",
"Health Current 0.0 \n",
"Innovaccer Inc. 0.0 \n",
"Kinetica 0.0 \n",
"Minga 0.0 \n",
"Renu Contracting Restoration 0.0 \n",
"Velocity Risk Underwriters, LLC 0.0 "
]
},
"execution_count": 151,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Iterate through each row of the original dataframe\n",
"count = 0\n",
"for index, row in cd.iterrows():\n",
" # Create a list to store the scaled values for each row\n",
" scaled_row = []\n",
"\n",
" # Iterate through each column of the row|\n",
" for col in cd.columns:\n",
" count += 1\n",
" # Calculate the min and max values for the row\n",
" min_val = row.min()\n",
" max_val = row.max()\n",
"\n",
" # Calculate the scaled value for the column\n",
" if max_val == 0:\n",
" scaled_val = 0\n",
" else:\n",
" scaled_val = (row[col] - min_val) / (max_val - min_val)\n",
"\n",
" # Append the scaled value to the list of scaled values for the row\n",
" scaled_row.append(scaled_val)\n",
" scaled_df.loc[count] = scaled_row\n",
"\n",
"scaled_df.set_index(keys=cd.index, inplace=True)\n",
"scaled_df.head(100)\n"
]
},
{
"cell_type": "code",
"execution_count": 246,
"id": "5d15b141",
"metadata": {},
"outputs": [
{
"data": {
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" color: red;\n",
"}\n",
"</style>\n",
"<table id=\"T_2394e\">\n",
" <thead>\n",
" <tr>\n",
" <th class=\"blank level0\" >&nbsp;</th>\n",
" <th id=\"T_2394e_level0_col0\" class=\"col_heading level0 col0\" >2022-01</th>\n",
" <th id=\"T_2394e_level0_col1\" class=\"col_heading level0 col1\" >2022-02</th>\n",
" <th id=\"T_2394e_level0_col2\" class=\"col_heading level0 col2\" >2022-03</th>\n",
" <th id=\"T_2394e_level0_col3\" class=\"col_heading level0 col3\" >2022-04</th>\n",
" <th id=\"T_2394e_level0_col4\" class=\"col_heading level0 col4\" >2022-05</th>\n",
" <th id=\"T_2394e_level0_col5\" class=\"col_heading level0 col5\" >2022-06</th>\n",
" <th id=\"T_2394e_level0_col6\" class=\"col_heading level0 col6\" >2022-07</th>\n",
" <th id=\"T_2394e_level0_col7\" class=\"col_heading level0 col7\" >2022-08</th>\n",
" <th id=\"T_2394e_level0_col8\" class=\"col_heading level0 col8\" >2022-09</th>\n",
" <th id=\"T_2394e_level0_col9\" class=\"col_heading level0 col9\" >2022-10</th>\n",
" <th id=\"T_2394e_level0_col10\" class=\"col_heading level0 col10\" >2022-11</th>\n",
" <th id=\"T_2394e_level0_col11\" class=\"col_heading level0 col11\" >2022-12</th>\n",
" <th id=\"T_2394e_level0_col12\" class=\"col_heading level0 col12\" >2023-01</th>\n",
" <th id=\"T_2394e_level0_col13\" class=\"col_heading level0 col13\" >2023-02</th>\n",
" <th id=\"T_2394e_level0_col14\" class=\"col_heading level0 col14\" >2023-03</th>\n",
" <th id=\"T_2394e_level0_col15\" class=\"col_heading level0 col15\" >2023-04</th>\n",
" </tr>\n",
" <tr>\n",
" <th class=\"index_name level0\" >Organization</th>\n",
" <th class=\"blank col0\" >&nbsp;</th>\n",
" <th class=\"blank col1\" >&nbsp;</th>\n",
" <th class=\"blank col2\" >&nbsp;</th>\n",
" <th class=\"blank col3\" >&nbsp;</th>\n",
" <th class=\"blank col4\" >&nbsp;</th>\n",
" <th class=\"blank col5\" >&nbsp;</th>\n",
" <th class=\"blank col6\" >&nbsp;</th>\n",
" <th class=\"blank col7\" >&nbsp;</th>\n",
" <th class=\"blank col8\" >&nbsp;</th>\n",
" <th class=\"blank col9\" >&nbsp;</th>\n",
" <th class=\"blank col10\" >&nbsp;</th>\n",
" <th class=\"blank col11\" >&nbsp;</th>\n",
" <th class=\"blank col12\" >&nbsp;</th>\n",
" <th class=\"blank col13\" >&nbsp;</th>\n",
" <th class=\"blank col14\" >&nbsp;</th>\n",
" <th class=\"blank col15\" >&nbsp;</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row0\" class=\"row_heading level0 row0\" >Aquent</th>\n",
" <td id=\"T_2394e_row0_col0\" class=\"data row0 col0\" >1.000000</td>\n",
" <td id=\"T_2394e_row0_col1\" class=\"data row0 col1\" >0.642857</td>\n",
" <td id=\"T_2394e_row0_col2\" class=\"data row0 col2\" >0.857143</td>\n",
" <td id=\"T_2394e_row0_col3\" class=\"data row0 col3\" >0.857143</td>\n",
" <td id=\"T_2394e_row0_col4\" class=\"data row0 col4\" >0.660714</td>\n",
" <td id=\"T_2394e_row0_col5\" class=\"data row0 col5\" >0.607143</td>\n",
" <td id=\"T_2394e_row0_col6\" class=\"data row0 col6\" >0.785714</td>\n",
" <td id=\"T_2394e_row0_col7\" class=\"data row0 col7\" >0.785714</td>\n",
" <td id=\"T_2394e_row0_col8\" class=\"data row0 col8\" >0.732143</td>\n",
" <td id=\"T_2394e_row0_col9\" class=\"data row0 col9\" >0.446429</td>\n",
" <td id=\"T_2394e_row0_col10\" class=\"data row0 col10\" >0.392857</td>\n",
" <td id=\"T_2394e_row0_col11\" class=\"data row0 col11\" >0.428571</td>\n",
" <td id=\"T_2394e_row0_col12\" class=\"data row0 col12\" >0.357143</td>\n",
" <td id=\"T_2394e_row0_col13\" class=\"data row0 col13\" >0.107143</td>\n",
" <td id=\"T_2394e_row0_col14\" class=\"data row0 col14\" >0.142857</td>\n",
" <td id=\"T_2394e_row0_col15\" class=\"data row0 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row1\" class=\"row_heading level0 row1\" >BioLife Solutions, Inc.</th>\n",
" <td id=\"T_2394e_row1_col0\" class=\"data row1 col0\" >1.000000</td>\n",
" <td id=\"T_2394e_row1_col1\" class=\"data row1 col1\" >0.636364</td>\n",
" <td id=\"T_2394e_row1_col2\" class=\"data row1 col2\" >0.363636</td>\n",
" <td id=\"T_2394e_row1_col3\" class=\"data row1 col3\" >1.000000</td>\n",
" <td id=\"T_2394e_row1_col4\" class=\"data row1 col4\" >0.363636</td>\n",
" <td id=\"T_2394e_row1_col5\" class=\"data row1 col5\" >0.000000</td>\n",
" <td id=\"T_2394e_row1_col6\" class=\"data row1 col6\" >0.000000</td>\n",
" <td id=\"T_2394e_row1_col7\" class=\"data row1 col7\" >0.000000</td>\n",
" <td id=\"T_2394e_row1_col8\" class=\"data row1 col8\" >0.000000</td>\n",
" <td id=\"T_2394e_row1_col9\" class=\"data row1 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row1_col10\" class=\"data row1 col10\" >0.000000</td>\n",
" <td id=\"T_2394e_row1_col11\" class=\"data row1 col11\" >0.000000</td>\n",
" <td id=\"T_2394e_row1_col12\" class=\"data row1 col12\" >0.000000</td>\n",
" <td id=\"T_2394e_row1_col13\" class=\"data row1 col13\" >0.000000</td>\n",
" <td id=\"T_2394e_row1_col14\" class=\"data row1 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row1_col15\" class=\"data row1 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row2\" class=\"row_heading level0 row2\" >ZyXel Communications Inc</th>\n",
" <td id=\"T_2394e_row2_col0\" class=\"data row2 col0\" >0.250000</td>\n",
" <td id=\"T_2394e_row2_col1\" class=\"data row2 col1\" >0.250000</td>\n",
" <td id=\"T_2394e_row2_col2\" class=\"data row2 col2\" >0.500000</td>\n",
" <td id=\"T_2394e_row2_col3\" class=\"data row2 col3\" >0.250000</td>\n",
" <td id=\"T_2394e_row2_col4\" class=\"data row2 col4\" >0.500000</td>\n",
" <td id=\"T_2394e_row2_col5\" class=\"data row2 col5\" >1.000000</td>\n",
" <td id=\"T_2394e_row2_col6\" class=\"data row2 col6\" >0.500000</td>\n",
" <td id=\"T_2394e_row2_col7\" class=\"data row2 col7\" >0.500000</td>\n",
" <td id=\"T_2394e_row2_col8\" class=\"data row2 col8\" >0.250000</td>\n",
" <td id=\"T_2394e_row2_col9\" class=\"data row2 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row2_col10\" class=\"data row2 col10\" >0.000000</td>\n",
" <td id=\"T_2394e_row2_col11\" class=\"data row2 col11\" >0.000000</td>\n",
" <td id=\"T_2394e_row2_col12\" class=\"data row2 col12\" >0.000000</td>\n",
" <td id=\"T_2394e_row2_col13\" class=\"data row2 col13\" >0.250000</td>\n",
" <td id=\"T_2394e_row2_col14\" class=\"data row2 col14\" >0.250000</td>\n",
" <td id=\"T_2394e_row2_col15\" class=\"data row2 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row3\" class=\"row_heading level0 row3\" >BrightLine Eating Solutions LLC</th>\n",
" <td id=\"T_2394e_row3_col0\" class=\"data row3 col0\" >1.000000</td>\n",
" <td id=\"T_2394e_row3_col1\" class=\"data row3 col1\" >0.761436</td>\n",
" <td id=\"T_2394e_row3_col2\" class=\"data row3 col2\" >0.701795</td>\n",
" <td id=\"T_2394e_row3_col3\" class=\"data row3 col3\" >0.789133</td>\n",
" <td id=\"T_2394e_row3_col4\" class=\"data row3 col4\" >0.817217</td>\n",
" <td id=\"T_2394e_row3_col5\" class=\"data row3 col5\" >0.726115</td>\n",
" <td id=\"T_2394e_row3_col6\" class=\"data row3 col6\" >0.821174</td>\n",
" <td id=\"T_2394e_row3_col7\" class=\"data row3 col7\" >0.544103</td>\n",
" <td id=\"T_2394e_row3_col8\" class=\"data row3 col8\" >0.056070</td>\n",
" <td id=\"T_2394e_row3_col9\" class=\"data row3 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row3_col10\" class=\"data row3 col10\" >0.000000</td>\n",
" <td id=\"T_2394e_row3_col11\" class=\"data row3 col11\" >0.000000</td>\n",
" <td id=\"T_2394e_row3_col12\" class=\"data row3 col12\" >0.000000</td>\n",
" <td id=\"T_2394e_row3_col13\" class=\"data row3 col13\" >0.000000</td>\n",
" <td id=\"T_2394e_row3_col14\" class=\"data row3 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row3_col15\" class=\"data row3 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row4\" class=\"row_heading level0 row4\" >Casio America Inc</th>\n",
" <td id=\"T_2394e_row4_col0\" class=\"data row4 col0\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col1\" class=\"data row4 col1\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col2\" class=\"data row4 col2\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col3\" class=\"data row4 col3\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col4\" class=\"data row4 col4\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col5\" class=\"data row4 col5\" >1.000000</td>\n",
" <td id=\"T_2394e_row4_col6\" class=\"data row4 col6\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col7\" class=\"data row4 col7\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col8\" class=\"data row4 col8\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col9\" class=\"data row4 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col10\" class=\"data row4 col10\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col11\" class=\"data row4 col11\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col12\" class=\"data row4 col12\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col13\" class=\"data row4 col13\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col14\" class=\"data row4 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row4_col15\" class=\"data row4 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row5\" class=\"row_heading level0 row5\" >Riviera Partners LLC</th>\n",
" <td id=\"T_2394e_row5_col0\" class=\"data row5 col0\" >1.000000</td>\n",
" <td id=\"T_2394e_row5_col1\" class=\"data row5 col1\" >0.194805</td>\n",
" <td id=\"T_2394e_row5_col2\" class=\"data row5 col2\" >0.610390</td>\n",
" <td id=\"T_2394e_row5_col3\" class=\"data row5 col3\" >0.285714</td>\n",
" <td id=\"T_2394e_row5_col4\" class=\"data row5 col4\" >0.285714</td>\n",
" <td id=\"T_2394e_row5_col5\" class=\"data row5 col5\" >0.363636</td>\n",
" <td id=\"T_2394e_row5_col6\" class=\"data row5 col6\" >0.974026</td>\n",
" <td id=\"T_2394e_row5_col7\" class=\"data row5 col7\" >0.831169</td>\n",
" <td id=\"T_2394e_row5_col8\" class=\"data row5 col8\" >0.402597</td>\n",
" <td id=\"T_2394e_row5_col9\" class=\"data row5 col9\" >0.246753</td>\n",
" <td id=\"T_2394e_row5_col10\" class=\"data row5 col10\" >0.376623</td>\n",
" <td id=\"T_2394e_row5_col11\" class=\"data row5 col11\" >0.272727</td>\n",
" <td id=\"T_2394e_row5_col12\" class=\"data row5 col12\" >0.922078</td>\n",
" <td id=\"T_2394e_row5_col13\" class=\"data row5 col13\" >0.870130</td>\n",
" <td id=\"T_2394e_row5_col14\" class=\"data row5 col14\" >0.324675</td>\n",
" <td id=\"T_2394e_row5_col15\" class=\"data row5 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row6\" class=\"row_heading level0 row6\" >Viveve</th>\n",
" <td id=\"T_2394e_row6_col0\" class=\"data row6 col0\" >0.000000</td>\n",
" <td id=\"T_2394e_row6_col1\" class=\"data row6 col1\" >0.000000</td>\n",
" <td id=\"T_2394e_row6_col2\" class=\"data row6 col2\" >0.000000</td>\n",
" <td id=\"T_2394e_row6_col3\" class=\"data row6 col3\" >0.000000</td>\n",
" <td id=\"T_2394e_row6_col4\" class=\"data row6 col4\" >0.000000</td>\n",
" <td id=\"T_2394e_row6_col5\" class=\"data row6 col5\" >0.210526</td>\n",
" <td id=\"T_2394e_row6_col6\" class=\"data row6 col6\" >0.052632</td>\n",
" <td id=\"T_2394e_row6_col7\" class=\"data row6 col7\" >0.000000</td>\n",
" <td id=\"T_2394e_row6_col8\" class=\"data row6 col8\" >0.000000</td>\n",
" <td id=\"T_2394e_row6_col9\" class=\"data row6 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row6_col10\" class=\"data row6 col10\" >0.000000</td>\n",
" <td id=\"T_2394e_row6_col11\" class=\"data row6 col11\" >1.000000</td>\n",
" <td id=\"T_2394e_row6_col12\" class=\"data row6 col12\" >0.157895</td>\n",
" <td id=\"T_2394e_row6_col13\" class=\"data row6 col13\" >0.000000</td>\n",
" <td id=\"T_2394e_row6_col14\" class=\"data row6 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row6_col15\" class=\"data row6 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row7\" class=\"row_heading level0 row7\" >connectRN Inc.</th>\n",
" <td id=\"T_2394e_row7_col0\" class=\"data row7 col0\" >0.320865</td>\n",
" <td id=\"T_2394e_row7_col1\" class=\"data row7 col1\" >0.314214</td>\n",
" <td id=\"T_2394e_row7_col2\" class=\"data row7 col2\" >0.329177</td>\n",
" <td id=\"T_2394e_row7_col3\" class=\"data row7 col3\" >0.608479</td>\n",
" <td id=\"T_2394e_row7_col4\" class=\"data row7 col4\" >0.787199</td>\n",
" <td id=\"T_2394e_row7_col5\" class=\"data row7 col5\" >0.633416</td>\n",
" <td id=\"T_2394e_row7_col6\" class=\"data row7 col6\" >1.000000</td>\n",
" <td id=\"T_2394e_row7_col7\" class=\"data row7 col7\" >0.738986</td>\n",
" <td id=\"T_2394e_row7_col8\" class=\"data row7 col8\" >0.364090</td>\n",
" <td id=\"T_2394e_row7_col9\" class=\"data row7 col9\" >0.147963</td>\n",
" <td id=\"T_2394e_row7_col10\" class=\"data row7 col10\" >0.095594</td>\n",
" <td id=\"T_2394e_row7_col11\" class=\"data row7 col11\" >0.177889</td>\n",
" <td id=\"T_2394e_row7_col12\" class=\"data row7 col12\" >0.076475</td>\n",
" <td id=\"T_2394e_row7_col13\" class=\"data row7 col13\" >0.137157</td>\n",
" <td id=\"T_2394e_row7_col14\" class=\"data row7 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row7_col15\" class=\"data row7 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row8\" class=\"row_heading level0 row8\" >Hammer Nutrition</th>\n",
" <td id=\"T_2394e_row8_col0\" class=\"data row8 col0\" >0.000000</td>\n",
" <td id=\"T_2394e_row8_col1\" class=\"data row8 col1\" >0.142857</td>\n",
" <td id=\"T_2394e_row8_col2\" class=\"data row8 col2\" >0.142857</td>\n",
" <td id=\"T_2394e_row8_col3\" class=\"data row8 col3\" >0.285714</td>\n",
" <td id=\"T_2394e_row8_col4\" class=\"data row8 col4\" >1.000000</td>\n",
" <td id=\"T_2394e_row8_col5\" class=\"data row8 col5\" >0.714286</td>\n",
" <td id=\"T_2394e_row8_col6\" class=\"data row8 col6\" >0.571429</td>\n",
" <td id=\"T_2394e_row8_col7\" class=\"data row8 col7\" >0.714286</td>\n",
" <td id=\"T_2394e_row8_col8\" class=\"data row8 col8\" >0.857143</td>\n",
" <td id=\"T_2394e_row8_col9\" class=\"data row8 col9\" >0.857143</td>\n",
" <td id=\"T_2394e_row8_col10\" class=\"data row8 col10\" >0.000000</td>\n",
" <td id=\"T_2394e_row8_col11\" class=\"data row8 col11\" >0.000000</td>\n",
" <td id=\"T_2394e_row8_col12\" class=\"data row8 col12\" >0.000000</td>\n",
" <td id=\"T_2394e_row8_col13\" class=\"data row8 col13\" >0.000000</td>\n",
" <td id=\"T_2394e_row8_col14\" class=\"data row8 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row8_col15\" class=\"data row8 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row9\" class=\"row_heading level0 row9\" >National Campus and Community Radio Association</th>\n",
" <td id=\"T_2394e_row9_col0\" class=\"data row9 col0\" >1.000000</td>\n",
" <td id=\"T_2394e_row9_col1\" class=\"data row9 col1\" >0.238095</td>\n",
" <td id=\"T_2394e_row9_col2\" class=\"data row9 col2\" >0.158730</td>\n",
" <td id=\"T_2394e_row9_col3\" class=\"data row9 col3\" >0.063492</td>\n",
" <td id=\"T_2394e_row9_col4\" class=\"data row9 col4\" >0.126984</td>\n",
" <td id=\"T_2394e_row9_col5\" class=\"data row9 col5\" >0.031746</td>\n",
" <td id=\"T_2394e_row9_col6\" class=\"data row9 col6\" >0.047619</td>\n",
" <td id=\"T_2394e_row9_col7\" class=\"data row9 col7\" >0.000000</td>\n",
" <td id=\"T_2394e_row9_col8\" class=\"data row9 col8\" >0.063492</td>\n",
" <td id=\"T_2394e_row9_col9\" class=\"data row9 col9\" >0.063492</td>\n",
" <td id=\"T_2394e_row9_col10\" class=\"data row9 col10\" >0.095238</td>\n",
" <td id=\"T_2394e_row9_col11\" class=\"data row9 col11\" >0.079365</td>\n",
" <td id=\"T_2394e_row9_col12\" class=\"data row9 col12\" >0.079365</td>\n",
" <td id=\"T_2394e_row9_col13\" class=\"data row9 col13\" >0.031746</td>\n",
" <td id=\"T_2394e_row9_col14\" class=\"data row9 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row9_col15\" class=\"data row9 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row10\" class=\"row_heading level0 row10\" >Portnoy, Messinger, Pearl & Associates, Inc.</th>\n",
" <td id=\"T_2394e_row10_col0\" class=\"data row10 col0\" >0.354430</td>\n",
" <td id=\"T_2394e_row10_col1\" class=\"data row10 col1\" >0.341772</td>\n",
" <td id=\"T_2394e_row10_col2\" class=\"data row10 col2\" >1.000000</td>\n",
" <td id=\"T_2394e_row10_col3\" class=\"data row10 col3\" >0.215190</td>\n",
" <td id=\"T_2394e_row10_col4\" class=\"data row10 col4\" >0.012658</td>\n",
" <td id=\"T_2394e_row10_col5\" class=\"data row10 col5\" >0.037975</td>\n",
" <td id=\"T_2394e_row10_col6\" class=\"data row10 col6\" >0.101266</td>\n",
" <td id=\"T_2394e_row10_col7\" class=\"data row10 col7\" >0.000000</td>\n",
" <td id=\"T_2394e_row10_col8\" class=\"data row10 col8\" >0.012658</td>\n",
" <td id=\"T_2394e_row10_col9\" class=\"data row10 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row10_col10\" class=\"data row10 col10\" >0.012658</td>\n",
" <td id=\"T_2394e_row10_col11\" class=\"data row10 col11\" >0.012658</td>\n",
" <td id=\"T_2394e_row10_col12\" class=\"data row10 col12\" >0.025316</td>\n",
" <td id=\"T_2394e_row10_col13\" class=\"data row10 col13\" >0.000000</td>\n",
" <td id=\"T_2394e_row10_col14\" class=\"data row10 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row10_col15\" class=\"data row10 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row11\" class=\"row_heading level0 row11\" >Safari Energy</th>\n",
" <td id=\"T_2394e_row11_col0\" class=\"data row11 col0\" >0.052632</td>\n",
" <td id=\"T_2394e_row11_col1\" class=\"data row11 col1\" >0.973684</td>\n",
" <td id=\"T_2394e_row11_col2\" class=\"data row11 col2\" >0.500000</td>\n",
" <td id=\"T_2394e_row11_col3\" class=\"data row11 col3\" >0.052632</td>\n",
" <td id=\"T_2394e_row11_col4\" class=\"data row11 col4\" >0.026316</td>\n",
" <td id=\"T_2394e_row11_col5\" class=\"data row11 col5\" >1.000000</td>\n",
" <td id=\"T_2394e_row11_col6\" class=\"data row11 col6\" >0.631579</td>\n",
" <td id=\"T_2394e_row11_col7\" class=\"data row11 col7\" >0.157895</td>\n",
" <td id=\"T_2394e_row11_col8\" class=\"data row11 col8\" >0.552632</td>\n",
" <td id=\"T_2394e_row11_col9\" class=\"data row11 col9\" >0.921053</td>\n",
" <td id=\"T_2394e_row11_col10\" class=\"data row11 col10\" >0.263158</td>\n",
" <td id=\"T_2394e_row11_col11\" class=\"data row11 col11\" >0.184211</td>\n",
" <td id=\"T_2394e_row11_col12\" class=\"data row11 col12\" >0.026316</td>\n",
" <td id=\"T_2394e_row11_col13\" class=\"data row11 col13\" >0.000000</td>\n",
" <td id=\"T_2394e_row11_col14\" class=\"data row11 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row11_col15\" class=\"data row11 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row12\" class=\"row_heading level0 row12\" >Starwood Pet Travel</th>\n",
" <td id=\"T_2394e_row12_col0\" class=\"data row12 col0\" >0.000000</td>\n",
" <td id=\"T_2394e_row12_col1\" class=\"data row12 col1\" >0.045455</td>\n",
" <td id=\"T_2394e_row12_col2\" class=\"data row12 col2\" >0.181818</td>\n",
" <td id=\"T_2394e_row12_col3\" class=\"data row12 col3\" >1.000000</td>\n",
" <td id=\"T_2394e_row12_col4\" class=\"data row12 col4\" >0.090909</td>\n",
" <td id=\"T_2394e_row12_col5\" class=\"data row12 col5\" >0.045455</td>\n",
" <td id=\"T_2394e_row12_col6\" class=\"data row12 col6\" >0.318182</td>\n",
" <td id=\"T_2394e_row12_col7\" class=\"data row12 col7\" >0.000000</td>\n",
" <td id=\"T_2394e_row12_col8\" class=\"data row12 col8\" >0.000000</td>\n",
" <td id=\"T_2394e_row12_col9\" class=\"data row12 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row12_col10\" class=\"data row12 col10\" >0.000000</td>\n",
" <td id=\"T_2394e_row12_col11\" class=\"data row12 col11\" >0.090909</td>\n",
" <td id=\"T_2394e_row12_col12\" class=\"data row12 col12\" >0.000000</td>\n",
" <td id=\"T_2394e_row12_col13\" class=\"data row12 col13\" >0.090909</td>\n",
" <td id=\"T_2394e_row12_col14\" class=\"data row12 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row12_col15\" class=\"data row12 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row13\" class=\"row_heading level0 row13\" >Trax Technology Solutions Pte Ltd</th>\n",
" <td id=\"T_2394e_row13_col0\" class=\"data row13 col0\" >0.562777</td>\n",
" <td id=\"T_2394e_row13_col1\" class=\"data row13 col1\" >1.000000</td>\n",
" <td id=\"T_2394e_row13_col2\" class=\"data row13 col2\" >0.861152</td>\n",
" <td id=\"T_2394e_row13_col3\" class=\"data row13 col3\" >0.991137</td>\n",
" <td id=\"T_2394e_row13_col4\" class=\"data row13 col4\" >0.760709</td>\n",
" <td id=\"T_2394e_row13_col5\" class=\"data row13 col5\" >0.561300</td>\n",
" <td id=\"T_2394e_row13_col6\" class=\"data row13 col6\" >0.267356</td>\n",
" <td id=\"T_2394e_row13_col7\" class=\"data row13 col7\" >0.663220</td>\n",
" <td id=\"T_2394e_row13_col8\" class=\"data row13 col8\" >0.017725</td>\n",
" <td id=\"T_2394e_row13_col9\" class=\"data row13 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row13_col10\" class=\"data row13 col10\" >0.001477</td>\n",
" <td id=\"T_2394e_row13_col11\" class=\"data row13 col11\" >0.001477</td>\n",
" <td id=\"T_2394e_row13_col12\" class=\"data row13 col12\" >0.001477</td>\n",
" <td id=\"T_2394e_row13_col13\" class=\"data row13 col13\" >0.000000</td>\n",
" <td id=\"T_2394e_row13_col14\" class=\"data row13 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row13_col15\" class=\"data row13 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row14\" class=\"row_heading level0 row14\" >Uber London Limited (POOL)</th>\n",
" <td id=\"T_2394e_row14_col0\" class=\"data row14 col0\" >0.368421</td>\n",
" <td id=\"T_2394e_row14_col1\" class=\"data row14 col1\" >0.396014</td>\n",
" <td id=\"T_2394e_row14_col2\" class=\"data row14 col2\" >0.421564</td>\n",
" <td id=\"T_2394e_row14_col3\" class=\"data row14 col3\" >0.309658</td>\n",
" <td id=\"T_2394e_row14_col4\" class=\"data row14 col4\" >0.295350</td>\n",
" <td id=\"T_2394e_row14_col5\" class=\"data row14 col5\" >0.256004</td>\n",
" <td id=\"T_2394e_row14_col6\" class=\"data row14 col6\" >0.253960</td>\n",
" <td id=\"T_2394e_row14_col7\" class=\"data row14 col7\" >0.277466</td>\n",
" <td id=\"T_2394e_row14_col8\" class=\"data row14 col8\" >0.320899</td>\n",
" <td id=\"T_2394e_row14_col9\" class=\"data row14 col9\" >0.258048</td>\n",
" <td id=\"T_2394e_row14_col10\" class=\"data row14 col10\" >0.332141</td>\n",
" <td id=\"T_2394e_row14_col11\" class=\"data row14 col11\" >0.648952</td>\n",
" <td id=\"T_2394e_row14_col12\" class=\"data row14 col12\" >1.000000</td>\n",
" <td id=\"T_2394e_row14_col13\" class=\"data row14 col13\" >0.097087</td>\n",
" <td id=\"T_2394e_row14_col14\" class=\"data row14 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row14_col15\" class=\"data row14 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row15\" class=\"row_heading level0 row15\" >Artsy</th>\n",
" <td id=\"T_2394e_row15_col0\" class=\"data row15 col0\" >0.000000</td>\n",
" <td id=\"T_2394e_row15_col1\" class=\"data row15 col1\" >0.250000</td>\n",
" <td id=\"T_2394e_row15_col2\" class=\"data row15 col2\" >0.250000</td>\n",
" <td id=\"T_2394e_row15_col3\" class=\"data row15 col3\" >1.000000</td>\n",
" <td id=\"T_2394e_row15_col4\" class=\"data row15 col4\" >0.400000</td>\n",
" <td id=\"T_2394e_row15_col5\" class=\"data row15 col5\" >0.350000</td>\n",
" <td id=\"T_2394e_row15_col6\" class=\"data row15 col6\" >0.200000</td>\n",
" <td id=\"T_2394e_row15_col7\" class=\"data row15 col7\" >0.150000</td>\n",
" <td id=\"T_2394e_row15_col8\" class=\"data row15 col8\" >0.200000</td>\n",
" <td id=\"T_2394e_row15_col9\" class=\"data row15 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row15_col10\" class=\"data row15 col10\" >0.500000</td>\n",
" <td id=\"T_2394e_row15_col11\" class=\"data row15 col11\" >0.450000</td>\n",
" <td id=\"T_2394e_row15_col12\" class=\"data row15 col12\" >0.000000</td>\n",
" <td id=\"T_2394e_row15_col13\" class=\"data row15 col13\" >0.050000</td>\n",
" <td id=\"T_2394e_row15_col14\" class=\"data row15 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row15_col15\" class=\"data row15 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row16\" class=\"row_heading level0 row16\" >BambooHR</th>\n",
" <td id=\"T_2394e_row16_col0\" class=\"data row16 col0\" >0.955440</td>\n",
" <td id=\"T_2394e_row16_col1\" class=\"data row16 col1\" >1.000000</td>\n",
" <td id=\"T_2394e_row16_col2\" class=\"data row16 col2\" >0.909499</td>\n",
" <td id=\"T_2394e_row16_col3\" class=\"data row16 col3\" >0.821416</td>\n",
" <td id=\"T_2394e_row16_col4\" class=\"data row16 col4\" >0.781693</td>\n",
" <td id=\"T_2394e_row16_col5\" class=\"data row16 col5\" >0.740242</td>\n",
" <td id=\"T_2394e_row16_col6\" class=\"data row16 col6\" >0.711572</td>\n",
" <td id=\"T_2394e_row16_col7\" class=\"data row16 col7\" >0.202763</td>\n",
" <td id=\"T_2394e_row16_col8\" class=\"data row16 col8\" >0.000000</td>\n",
" <td id=\"T_2394e_row16_col9\" class=\"data row16 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row16_col10\" class=\"data row16 col10\" >0.000000</td>\n",
" <td id=\"T_2394e_row16_col11\" class=\"data row16 col11\" >0.000000</td>\n",
" <td id=\"T_2394e_row16_col12\" class=\"data row16 col12\" >0.000000</td>\n",
" <td id=\"T_2394e_row16_col13\" class=\"data row16 col13\" >0.000000</td>\n",
" <td id=\"T_2394e_row16_col14\" class=\"data row16 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row16_col15\" class=\"data row16 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row17\" class=\"row_heading level0 row17\" >BrightMove</th>\n",
" <td id=\"T_2394e_row17_col0\" class=\"data row17 col0\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col1\" class=\"data row17 col1\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col2\" class=\"data row17 col2\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col3\" class=\"data row17 col3\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col4\" class=\"data row17 col4\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col5\" class=\"data row17 col5\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col6\" class=\"data row17 col6\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col7\" class=\"data row17 col7\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col8\" class=\"data row17 col8\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col9\" class=\"data row17 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col10\" class=\"data row17 col10\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col11\" class=\"data row17 col11\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col12\" class=\"data row17 col12\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col13\" class=\"data row17 col13\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col14\" class=\"data row17 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row17_col15\" class=\"data row17 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row18\" class=\"row_heading level0 row18\" >Cherokee Enterprises, Inc.</th>\n",
" <td id=\"T_2394e_row18_col0\" class=\"data row18 col0\" >0.000000</td>\n",
" <td id=\"T_2394e_row18_col1\" class=\"data row18 col1\" >0.500000</td>\n",
" <td id=\"T_2394e_row18_col2\" class=\"data row18 col2\" >1.000000</td>\n",
" <td id=\"T_2394e_row18_col3\" class=\"data row18 col3\" >1.000000</td>\n",
" <td id=\"T_2394e_row18_col4\" class=\"data row18 col4\" >0.000000</td>\n",
" <td id=\"T_2394e_row18_col5\" class=\"data row18 col5\" >0.500000</td>\n",
" <td id=\"T_2394e_row18_col6\" class=\"data row18 col6\" >1.000000</td>\n",
" <td id=\"T_2394e_row18_col7\" class=\"data row18 col7\" >0.000000</td>\n",
" <td id=\"T_2394e_row18_col8\" class=\"data row18 col8\" >1.000000</td>\n",
" <td id=\"T_2394e_row18_col9\" class=\"data row18 col9\" >0.500000</td>\n",
" <td id=\"T_2394e_row18_col10\" class=\"data row18 col10\" >1.000000</td>\n",
" <td id=\"T_2394e_row18_col11\" class=\"data row18 col11\" >0.000000</td>\n",
" <td id=\"T_2394e_row18_col12\" class=\"data row18 col12\" >0.500000</td>\n",
" <td id=\"T_2394e_row18_col13\" class=\"data row18 col13\" >0.000000</td>\n",
" <td id=\"T_2394e_row18_col14\" class=\"data row18 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row18_col15\" class=\"data row18 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row19\" class=\"row_heading level0 row19\" >Epiphany Healthcare</th>\n",
" <td id=\"T_2394e_row19_col0\" class=\"data row19 col0\" >0.272727</td>\n",
" <td id=\"T_2394e_row19_col1\" class=\"data row19 col1\" >0.545455</td>\n",
" <td id=\"T_2394e_row19_col2\" class=\"data row19 col2\" >1.000000</td>\n",
" <td id=\"T_2394e_row19_col3\" class=\"data row19 col3\" >0.242424</td>\n",
" <td id=\"T_2394e_row19_col4\" class=\"data row19 col4\" >0.242424</td>\n",
" <td id=\"T_2394e_row19_col5\" class=\"data row19 col5\" >0.151515</td>\n",
" <td id=\"T_2394e_row19_col6\" class=\"data row19 col6\" >0.393939</td>\n",
" <td id=\"T_2394e_row19_col7\" class=\"data row19 col7\" >0.848485</td>\n",
" <td id=\"T_2394e_row19_col8\" class=\"data row19 col8\" >0.424242</td>\n",
" <td id=\"T_2394e_row19_col9\" class=\"data row19 col9\" >0.454545</td>\n",
" <td id=\"T_2394e_row19_col10\" class=\"data row19 col10\" >0.181818</td>\n",
" <td id=\"T_2394e_row19_col11\" class=\"data row19 col11\" >0.393939</td>\n",
" <td id=\"T_2394e_row19_col12\" class=\"data row19 col12\" >0.181818</td>\n",
" <td id=\"T_2394e_row19_col13\" class=\"data row19 col13\" >0.060606</td>\n",
" <td id=\"T_2394e_row19_col14\" class=\"data row19 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row19_col15\" class=\"data row19 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row20\" class=\"row_heading level0 row20\" >H1 Insights, Inc.</th>\n",
" <td id=\"T_2394e_row20_col0\" class=\"data row20 col0\" >0.797468</td>\n",
" <td id=\"T_2394e_row20_col1\" class=\"data row20 col1\" >1.000000</td>\n",
" <td id=\"T_2394e_row20_col2\" class=\"data row20 col2\" >0.860759</td>\n",
" <td id=\"T_2394e_row20_col3\" class=\"data row20 col3\" >0.405063</td>\n",
" <td id=\"T_2394e_row20_col4\" class=\"data row20 col4\" >0.474684</td>\n",
" <td id=\"T_2394e_row20_col5\" class=\"data row20 col5\" >0.607595</td>\n",
" <td id=\"T_2394e_row20_col6\" class=\"data row20 col6\" >0.525316</td>\n",
" <td id=\"T_2394e_row20_col7\" class=\"data row20 col7\" >0.398734</td>\n",
" <td id=\"T_2394e_row20_col8\" class=\"data row20 col8\" >0.240506</td>\n",
" <td id=\"T_2394e_row20_col9\" class=\"data row20 col9\" >0.082278</td>\n",
" <td id=\"T_2394e_row20_col10\" class=\"data row20 col10\" >0.063291</td>\n",
" <td id=\"T_2394e_row20_col11\" class=\"data row20 col11\" >0.088608</td>\n",
" <td id=\"T_2394e_row20_col12\" class=\"data row20 col12\" >0.082278</td>\n",
" <td id=\"T_2394e_row20_col13\" class=\"data row20 col13\" >0.018987</td>\n",
" <td id=\"T_2394e_row20_col14\" class=\"data row20 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row20_col15\" class=\"data row20 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row21\" class=\"row_heading level0 row21\" >Health Current</th>\n",
" <td id=\"T_2394e_row21_col0\" class=\"data row21 col0\" >1.000000</td>\n",
" <td id=\"T_2394e_row21_col1\" class=\"data row21 col1\" >0.500000</td>\n",
" <td id=\"T_2394e_row21_col2\" class=\"data row21 col2\" >0.250000</td>\n",
" <td id=\"T_2394e_row21_col3\" class=\"data row21 col3\" >0.000000</td>\n",
" <td id=\"T_2394e_row21_col4\" class=\"data row21 col4\" >0.000000</td>\n",
" <td id=\"T_2394e_row21_col5\" class=\"data row21 col5\" >0.000000</td>\n",
" <td id=\"T_2394e_row21_col6\" class=\"data row21 col6\" >0.000000</td>\n",
" <td id=\"T_2394e_row21_col7\" class=\"data row21 col7\" >0.000000</td>\n",
" <td id=\"T_2394e_row21_col8\" class=\"data row21 col8\" >0.000000</td>\n",
" <td id=\"T_2394e_row21_col9\" class=\"data row21 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row21_col10\" class=\"data row21 col10\" >0.000000</td>\n",
" <td id=\"T_2394e_row21_col11\" class=\"data row21 col11\" >0.000000</td>\n",
" <td id=\"T_2394e_row21_col12\" class=\"data row21 col12\" >0.250000</td>\n",
" <td id=\"T_2394e_row21_col13\" class=\"data row21 col13\" >0.000000</td>\n",
" <td id=\"T_2394e_row21_col14\" class=\"data row21 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row21_col15\" class=\"data row21 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row22\" class=\"row_heading level0 row22\" >Innovaccer Inc.</th>\n",
" <td id=\"T_2394e_row22_col0\" class=\"data row22 col0\" >0.952830</td>\n",
" <td id=\"T_2394e_row22_col1\" class=\"data row22 col1\" >1.000000</td>\n",
" <td id=\"T_2394e_row22_col2\" class=\"data row22 col2\" >0.787736</td>\n",
" <td id=\"T_2394e_row22_col3\" class=\"data row22 col3\" >0.000000</td>\n",
" <td id=\"T_2394e_row22_col4\" class=\"data row22 col4\" >0.000000</td>\n",
" <td id=\"T_2394e_row22_col5\" class=\"data row22 col5\" >0.000000</td>\n",
" <td id=\"T_2394e_row22_col6\" class=\"data row22 col6\" >0.000000</td>\n",
" <td id=\"T_2394e_row22_col7\" class=\"data row22 col7\" >0.000000</td>\n",
" <td id=\"T_2394e_row22_col8\" class=\"data row22 col8\" >0.000000</td>\n",
" <td id=\"T_2394e_row22_col9\" class=\"data row22 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row22_col10\" class=\"data row22 col10\" >0.000000</td>\n",
" <td id=\"T_2394e_row22_col11\" class=\"data row22 col11\" >0.000000</td>\n",
" <td id=\"T_2394e_row22_col12\" class=\"data row22 col12\" >0.000000</td>\n",
" <td id=\"T_2394e_row22_col13\" class=\"data row22 col13\" >0.000000</td>\n",
" <td id=\"T_2394e_row22_col14\" class=\"data row22 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row22_col15\" class=\"data row22 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row23\" class=\"row_heading level0 row23\" >Kinetica</th>\n",
" <td id=\"T_2394e_row23_col0\" class=\"data row23 col0\" >0.619048</td>\n",
" <td id=\"T_2394e_row23_col1\" class=\"data row23 col1\" >0.476190</td>\n",
" <td id=\"T_2394e_row23_col2\" class=\"data row23 col2\" >0.285714</td>\n",
" <td id=\"T_2394e_row23_col3\" class=\"data row23 col3\" >0.142857</td>\n",
" <td id=\"T_2394e_row23_col4\" class=\"data row23 col4\" >0.333333</td>\n",
" <td id=\"T_2394e_row23_col5\" class=\"data row23 col5\" >1.000000</td>\n",
" <td id=\"T_2394e_row23_col6\" class=\"data row23 col6\" >0.095238</td>\n",
" <td id=\"T_2394e_row23_col7\" class=\"data row23 col7\" >0.238095</td>\n",
" <td id=\"T_2394e_row23_col8\" class=\"data row23 col8\" >0.380952</td>\n",
" <td id=\"T_2394e_row23_col9\" class=\"data row23 col9\" >0.238095</td>\n",
" <td id=\"T_2394e_row23_col10\" class=\"data row23 col10\" >0.190476</td>\n",
" <td id=\"T_2394e_row23_col11\" class=\"data row23 col11\" >0.380952</td>\n",
" <td id=\"T_2394e_row23_col12\" class=\"data row23 col12\" >0.095238</td>\n",
" <td id=\"T_2394e_row23_col13\" class=\"data row23 col13\" >0.095238</td>\n",
" <td id=\"T_2394e_row23_col14\" class=\"data row23 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row23_col15\" class=\"data row23 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row24\" class=\"row_heading level0 row24\" >Minga</th>\n",
" <td id=\"T_2394e_row24_col0\" class=\"data row24 col0\" >0.000000</td>\n",
" <td id=\"T_2394e_row24_col1\" class=\"data row24 col1\" >0.000000</td>\n",
" <td id=\"T_2394e_row24_col2\" class=\"data row24 col2\" >0.000000</td>\n",
" <td id=\"T_2394e_row24_col3\" class=\"data row24 col3\" >0.000000</td>\n",
" <td id=\"T_2394e_row24_col4\" class=\"data row24 col4\" >0.000000</td>\n",
" <td id=\"T_2394e_row24_col5\" class=\"data row24 col5\" >0.000000</td>\n",
" <td id=\"T_2394e_row24_col6\" class=\"data row24 col6\" >0.000000</td>\n",
" <td id=\"T_2394e_row24_col7\" class=\"data row24 col7\" >0.000000</td>\n",
" <td id=\"T_2394e_row24_col8\" class=\"data row24 col8\" >0.000000</td>\n",
" <td id=\"T_2394e_row24_col9\" class=\"data row24 col9\" >0.000000</td>\n",
" <td id=\"T_2394e_row24_col10\" class=\"data row24 col10\" >0.000000</td>\n",
" <td id=\"T_2394e_row24_col11\" class=\"data row24 col11\" >0.000000</td>\n",
" <td id=\"T_2394e_row24_col12\" class=\"data row24 col12\" >0.000000</td>\n",
" <td id=\"T_2394e_row24_col13\" class=\"data row24 col13\" >1.000000</td>\n",
" <td id=\"T_2394e_row24_col14\" class=\"data row24 col14\" >1.000000</td>\n",
" <td id=\"T_2394e_row24_col15\" class=\"data row24 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row25\" class=\"row_heading level0 row25\" >Renu Contracting Restoration</th>\n",
" <td id=\"T_2394e_row25_col0\" class=\"data row25 col0\" >0.101523</td>\n",
" <td id=\"T_2394e_row25_col1\" class=\"data row25 col1\" >1.000000</td>\n",
" <td id=\"T_2394e_row25_col2\" class=\"data row25 col2\" >0.121827</td>\n",
" <td id=\"T_2394e_row25_col3\" class=\"data row25 col3\" >0.045685</td>\n",
" <td id=\"T_2394e_row25_col4\" class=\"data row25 col4\" >0.116751</td>\n",
" <td id=\"T_2394e_row25_col5\" class=\"data row25 col5\" >0.106599</td>\n",
" <td id=\"T_2394e_row25_col6\" class=\"data row25 col6\" >0.192893</td>\n",
" <td id=\"T_2394e_row25_col7\" class=\"data row25 col7\" >0.076142</td>\n",
" <td id=\"T_2394e_row25_col8\" class=\"data row25 col8\" >0.020305</td>\n",
" <td id=\"T_2394e_row25_col9\" class=\"data row25 col9\" >0.050761</td>\n",
" <td id=\"T_2394e_row25_col10\" class=\"data row25 col10\" >0.010152</td>\n",
" <td id=\"T_2394e_row25_col11\" class=\"data row25 col11\" >0.015228</td>\n",
" <td id=\"T_2394e_row25_col12\" class=\"data row25 col12\" >0.020305</td>\n",
" <td id=\"T_2394e_row25_col13\" class=\"data row25 col13\" >0.020305</td>\n",
" <td id=\"T_2394e_row25_col14\" class=\"data row25 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row25_col15\" class=\"data row25 col15\" >0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_2394e_level0_row26\" class=\"row_heading level0 row26\" >Velocity Risk Underwriters, LLC</th>\n",
" <td id=\"T_2394e_row26_col0\" class=\"data row26 col0\" >0.226562</td>\n",
" <td id=\"T_2394e_row26_col1\" class=\"data row26 col1\" >0.039062</td>\n",
" <td id=\"T_2394e_row26_col2\" class=\"data row26 col2\" >0.054688</td>\n",
" <td id=\"T_2394e_row26_col3\" class=\"data row26 col3\" >0.070312</td>\n",
" <td id=\"T_2394e_row26_col4\" class=\"data row26 col4\" >0.093750</td>\n",
" <td id=\"T_2394e_row26_col5\" class=\"data row26 col5\" >0.156250</td>\n",
" <td id=\"T_2394e_row26_col6\" class=\"data row26 col6\" >0.031250</td>\n",
" <td id=\"T_2394e_row26_col7\" class=\"data row26 col7\" >0.296875</td>\n",
" <td id=\"T_2394e_row26_col8\" class=\"data row26 col8\" >0.078125</td>\n",
" <td id=\"T_2394e_row26_col9\" class=\"data row26 col9\" >0.054688</td>\n",
" <td id=\"T_2394e_row26_col10\" class=\"data row26 col10\" >0.117188</td>\n",
" <td id=\"T_2394e_row26_col11\" class=\"data row26 col11\" >0.773438</td>\n",
" <td id=\"T_2394e_row26_col12\" class=\"data row26 col12\" >1.000000</td>\n",
" <td id=\"T_2394e_row26_col13\" class=\"data row26 col13\" >0.085938</td>\n",
" <td id=\"T_2394e_row26_col14\" class=\"data row26 col14\" >0.000000</td>\n",
" <td id=\"T_2394e_row26_col15\" class=\"data row26 col15\" >0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n"
],
"text/plain": [
"<pandas.io.formats.style.Styler at 0x28dd3f2d0>"
]
},
"execution_count": 246,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def color_negative_red(val):\n",
" color = 'red' if val < .5 else 'green'\n",
" return 'color: %s' % color\n",
"\n",
"s = scaled_df.style.applymap(color_negative_red)\n",
"s"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "0a3fe628",
"metadata": {},
"source": [
"# Clients who churned on 2023-03"
]
},
{
"cell_type": "code",
"execution_count": 252,
"id": "996ef871",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 1500x700 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"axes = scaled_df.T.plot(rot=0, figsize=(15,7), y=['BrightLine Eating Solutions LLC', 'Casio America Inc', 'Riviera Partners LLC', 'Viveve'])\n",
"# axes.legend(loc=2)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "8ec58c5f",
"metadata": {},
"source": [
"# Clients who churned on 2023-02"
]
},
{
"cell_type": "code",
"execution_count": 254,
"id": "41a333d5",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 1500x700 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"clients = ['connectRN Inc.',\n",
"'Hammer Nutrition',\n",
"'National Campus and Community Radio Association',\n",
"'Portnoy, Messinger, Pearl & Associates, Inc.',\n",
"'Safari Energy',\n",
"'Starwood Pet Travel',\n",
"'Trax Technology Solutions Pte Ltd',\n",
"'Uber London Limited (POOL)']\n",
"\n",
"axes = scaled_df.T.plot(rot=0, figsize=(15,7), y=clients)"
]
},
{
"cell_type": "markdown",
"id": "f49ea1e4",
"metadata": {},
"source": []
},
{
"cell_type": "code",
"execution_count": 215,
"id": "dd4904c4",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"The average percentage decrease in values for each row can be calculated by taking the difference between the maximum and minimum values for each row and dividing it by the maximum value. This will give the average percentage decrease in values for each row."
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"scaled_df.sketch.ask(\"What is the average percentage decrease in values for each row?\")"
]
},
{
"cell_type": "code",
"execution_count": 245,
"id": "d067aa68",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: >"
]
},
"execution_count": 245,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"customer = scaled_df.loc['Kinetica']\n",
"pd.plotting.boxplot(customer, column=['2022-01', '2022-02', '2022-03', '2022-04'])"
]
},
{
"cell_type": "code",
"execution_count": 237,
"id": "ed0635ed",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"axes = pd.plotting.andrews_curves(scaled_df, '2022-04')\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "67c4ad82",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.1"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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