notebooks/06_grouping_methods_solutions.ipynb

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    "<center>\n",
    "    <h1>DatatableTon</h1>\n",
    "    💯 datatable exercises\n",
    "    <br>\n",
    "    <br>\n",
    "    <a href='https://github.com/vopani/datatableton/blob/master/LICENSE'>\n",
    "        <img src='https://img.shields.io/badge/license-Apache%202.0-blue.svg?logo=apache'>\n",
    "    </a>\n",
    "    <a href='https://github.com/vopani/datatableton'>\n",
    "        <img src='https://img.shields.io/github/stars/vopani/datatableton?color=yellowgreen&logo=github'>\n",
    "    </a>\n",
    "    <a href='https://twitter.com/vopani'>\n",
    "        <img src='https://img.shields.io/twitter/follow/vopani'>\n",
    "    </a>\n",
    "</center>"
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   "source": [
    "<center>\n",
    "    This is Set 6: Grouping Methods (Exercises 51-60) of <b>DatatableTon</b>: <i>💯 datatable exercises</i>\n",
    "    <br>\n",
    "    You can find all the exercises and solutions on <a href=\"https://github.com/vopani/datatableton#exercises-\">GitHub</a>\n",
    "</center>"
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   "source": [
    "**Prerequisites**\n",
    "* The `datatable` package should be upgraded to the latest version (or v1.0.0+).\n",
    "* The sample dataset [penguins](https://github.com/mwaskom/seaborn-data/blob/master/penguins.csv) from seaborn will be used for the exercises."
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      "Requirement already satisfied: pip in /opt/conda/lib/python3.7/site-packages (21.1.2)\r\n",
      "Collecting pip\r\n",
      "  Downloading pip-21.1.3-py3-none-any.whl (1.5 MB)\r\n",
      "\u001b[K     |████████████████████████████████| 1.5 MB 874 kB/s \r\n",
      "\u001b[?25hInstalling collected packages: pip\r\n",
      "  Attempting uninstall: pip\r\n",
      "    Found existing installation: pip 21.1.2\r\n",
      "    Uninstalling pip-21.1.2:\r\n",
      "      Successfully uninstalled pip-21.1.2\r\n",
      "Successfully installed pip-21.1.3\r\n",
      "\u001b[33mWARNING: Running pip as root will break packages and permissions. You should install packages reliably by using venv: https://pip.pypa.io/warnings/venv\u001b[0m\r\n",
      "Requirement already satisfied: datatable in /opt/conda/lib/python3.7/site-packages (1.0.0)\r\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\r\n",
      "Requirement already satisfied: seaborn in /opt/conda/lib/python3.7/site-packages (0.11.1)\r\n",
      "Requirement already satisfied: pandas>=0.23 in /opt/conda/lib/python3.7/site-packages (from seaborn) (1.2.4)\r\n",
      "Requirement already satisfied: numpy>=1.15 in /opt/conda/lib/python3.7/site-packages (from seaborn) (1.19.5)\r\n",
      "Requirement already satisfied: scipy>=1.0 in /opt/conda/lib/python3.7/site-packages (from seaborn) (1.6.3)\r\n",
      "Requirement already satisfied: matplotlib>=2.2 in /opt/conda/lib/python3.7/site-packages (from seaborn) (3.4.2)\r\n",
      "Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (0.10.0)\r\n",
      "Requirement already satisfied: pillow>=6.2.0 in /opt/conda/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (8.2.0)\r\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (1.3.1)\r\n",
      "Requirement already satisfied: pyparsing>=2.2.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (2.4.7)\r\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /opt/conda/lib/python3.7/site-packages (from matplotlib>=2.2->seaborn) (2.8.1)\r\n",
      "Requirement already satisfied: six in /opt/conda/lib/python3.7/site-packages (from cycler>=0.10->matplotlib>=2.2->seaborn) (1.15.0)\r\n",
      "Requirement already satisfied: pytz>=2017.3 in /opt/conda/lib/python3.7/site-packages (from pandas>=0.23->seaborn) (2021.1)\r\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\r\n"
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    "!python3 -m pip install -U pip\n",
    "!python3 -m pip install -U datatable\n",
    "!python3 -m pip install seaborn"
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       "    <tr><td class='row_index'>0</td><td>Adelie</td><td>Torgersen</td><td>39.1</td><td>18.7</td><td>181</td><td>3750</td><td>Male</td></tr>\n",
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       "    <tr><td class='row_index'>13</td><td>Adelie</td><td>Torgersen</td><td>38.6</td><td>21.2</td><td>191</td><td>3800</td><td>Male</td></tr>\n",
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   "source": [
    "import datatable as dt\n",
    "from seaborn import load_dataset\n",
    "\n",
    "data = dt.Frame(load_dataset('penguins'))\n",
    "data.replace('NA', None)\n",
    "data"
   ]
  },
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   "source": [
    "**Exercise 51: Calculate the number of rows of each `species` in `data`**"
   ]
  },
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       "    <tr><td class='row_index'>0</td><td>Adelie</td><td>152</td></tr>\n",
       "    <tr><td class='row_index'>1</td><td>Chinstrap</td><td>68</td></tr>\n",
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   "source": [
    "data[:, dt.count(), dt.by(dt.f.species)]"
   ]
  },
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   "source": [
    "**Exercise 52: Calculate the sum of `body_mass_g` by `island` in `data`**"
   ]
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    "data[:, dt.sum(dt.f.body_mass_g), dt.by(dt.f.island)]"
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   },
   "source": [
    "**Exercise 53: Calculate the mean of `body_mass_g` by non-null `sex` in `data`**"
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   "source": [
    "**Exercise 54: Calculate the maximum and minimum of `flipper_length_mm` together by `species` in `data`**"
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    "**Exercise 55: Calculate the median of `body_mass_g` by `species` and `sex` in `data`**"
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    "**Exercise 56: Calculate the standard deviation of `bill_depth_mm` in cm instead of mm by `island` in `data`**"
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   "source": [
    "**Exercise 57: Calculate the covariance between `flipper_length_mm` and `body_mass_g` by `species` and `island` in `data`**"
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    "**Exercise 58: Calculate the absolute correlation between `bill_length_mm` and `bill_depth_mm` by `species` and `sex` in `data`**"
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   "source": [
    "**Exercise 59: Calculate the number of null values in `sex` by `island` in `data`**"
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     "start_time": "2021-07-22T05:38:09.124381",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "**Exercise 60: Sort `data` on `bill_depth_mm` grouped by `sex` and assign it to `data_gs`**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7254a518",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-07-22T05:38:09.231519Z",
     "iopub.status.busy": "2021-07-22T05:38:09.230658Z",
     "iopub.status.idle": "2021-07-22T05:38:09.234888Z",
     "shell.execute_reply": "2021-07-22T05:38:09.235395Z",
     "shell.execute_reply.started": "2021-07-18T20:03:28.055063Z"
    },
    "papermill": {
     "duration": 0.049358,
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     "exception": false,
     "start_time": "2021-07-22T05:38:09.186230",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class='datatable'>\n",
       "  <table class='frame'>\n",
       "  <thead>\n",
       "    <tr class='colnames'><td class='row_index'></td><th>sex</th><th>species</th><th>island</th><th>bill_length_mm</th><th>bill_depth_mm</th><th>flipper_length_mm</th><th>body_mass_g</th></tr>\n",
       "    <tr class='coltypes'><td class='row_index'></td><td class='str' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='str' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='str' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='float' title='float64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='float' title='float64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='float' title='float64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='float' title='float64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><td class='row_index'>0</td><td><span class=na>NA</span></td><td>Adelie</td><td>Torgersen</td><td><span class=na>NA</span></td><td><span class=na>NA</span></td><td><span class=na>NA</span></td><td><span class=na>NA</span></td></tr>\n",
       "    <tr><td class='row_index'>1</td><td><span class=na>NA</span></td><td>Gentoo</td><td>Biscoe</td><td><span class=na>NA</span></td><td><span class=na>NA</span></td><td><span class=na>NA</span></td><td><span class=na>NA</span></td></tr>\n",
       "    <tr><td class='row_index'>2</td><td><span class=na>NA</span></td><td>Gentoo</td><td>Biscoe</td><td>47.3</td><td>13.8</td><td>216</td><td>4725</td></tr>\n",
       "    <tr><td class='row_index'>3</td><td><span class=na>NA</span></td><td>Gentoo</td><td>Biscoe</td><td>44.5</td><td>14.3</td><td>216</td><td>4100</td></tr>\n",
       "    <tr><td class='row_index'>4</td><td><span class=na>NA</span></td><td>Gentoo</td><td>Biscoe</td><td>46.2</td><td>14.4</td><td>214</td><td>4650</td></tr>\n",
       "    <tr><td class='row_index'>5</td><td><span class=na>NA</span></td><td>Gentoo</td><td>Biscoe</td><td>44.5</td><td>15.7</td><td>217</td><td>4875</td></tr>\n",
       "    <tr><td class='row_index'>6</td><td><span class=na>NA</span></td><td>Adelie</td><td>Torgersen</td><td>37.8</td><td>17.1</td><td>186</td><td>3300</td></tr>\n",
       "    <tr><td class='row_index'>7</td><td><span class=na>NA</span></td><td>Adelie</td><td>Torgersen</td><td>37.8</td><td>17.3</td><td>180</td><td>3700</td></tr>\n",
       "    <tr><td class='row_index'>8</td><td><span class=na>NA</span></td><td>Adelie</td><td>Torgersen</td><td>34.1</td><td>18.1</td><td>193</td><td>3475</td></tr>\n",
       "    <tr><td class='row_index'>9</td><td><span class=na>NA</span></td><td>Adelie</td><td>Dream</td><td>37.5</td><td>18.9</td><td>179</td><td>2975</td></tr>\n",
       "    <tr><td class='row_index'>10</td><td><span class=na>NA</span></td><td>Adelie</td><td>Torgersen</td><td>42</td><td>20.2</td><td>190</td><td>4250</td></tr>\n",
       "    <tr><td class='row_index'>11</td><td>Female</td><td>Gentoo</td><td>Biscoe</td><td>42.9</td><td>13.1</td><td>215</td><td>5000</td></tr>\n",
       "    <tr><td class='row_index'>12</td><td>Female</td><td>Gentoo</td><td>Biscoe</td><td>46.1</td><td>13.2</td><td>211</td><td>4500</td></tr>\n",
       "    <tr><td class='row_index'>13</td><td>Female</td><td>Gentoo</td><td>Biscoe</td><td>44.9</td><td>13.3</td><td>213</td><td>5100</td></tr>\n",
       "    <tr><td class='row_index'>14</td><td>Female</td><td>Gentoo</td><td>Biscoe</td><td>43.3</td><td>13.4</td><td>209</td><td>4400</td></tr>\n",
       "    <tr><td class='row_index'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td></tr>\n",
       "    <tr><td class='row_index'>339</td><td>Male</td><td>Adelie</td><td>Dream</td><td>39.2</td><td>21.1</td><td>196</td><td>4150</td></tr>\n",
       "    <tr><td class='row_index'>340</td><td>Male</td><td>Adelie</td><td>Biscoe</td><td>41.3</td><td>21.1</td><td>195</td><td>4400</td></tr>\n",
       "    <tr><td class='row_index'>341</td><td>Male</td><td>Adelie</td><td>Torgersen</td><td>38.6</td><td>21.2</td><td>191</td><td>3800</td></tr>\n",
       "    <tr><td class='row_index'>342</td><td>Male</td><td>Adelie</td><td>Dream</td><td>42.3</td><td>21.2</td><td>191</td><td>4150</td></tr>\n",
       "    <tr><td class='row_index'>343</td><td>Male</td><td>Adelie</td><td>Torgersen</td><td>46</td><td>21.5</td><td>194</td><td>4200</td></tr>\n",
       "  </tbody>\n",
       "  </table>\n",
       "  <div class='footer'>\n",
       "    <div class='frame_dimensions'>344 rows &times; 7 columns</div>\n",
       "  </div>\n",
       "</div>\n"
      ],
      "text/plain": [
       "<Frame#7f3c941acb40 344x7>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_gs = data[:, :, dt.by(dt.f.sex), dt.sort(dt.f.bill_depth_mm)]\n",
    "data_gs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4250cd56",
   "metadata": {
    "papermill": {
     "duration": 0.031344,
     "end_time": "2021-07-22T05:38:09.303077",
     "exception": false,
     "start_time": "2021-07-22T05:38:09.271733",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "✅ This completes Set 6: Grouping Methods (Exercises 51-60) of **DatatableTon**: *💯 datatable exercises*\n",
    "\n",
    "#### Set 07 • Multiple Frames • Intermediate • Exercises 61-70\n",
    "\n",
    "| Style | Colab | Kaggle | Binder | GitHub |\n",
    "| ----- | ----- | ------ | ------ | ------ |\n",
    "| Exercises | [![Open in Colab](https://img.shields.io/static/v1?label=&message=Open%20in%20Colab&labelColor=grey&color=blue&logo=google-colab)](https://colab.research.google.com/github/vopani/datatableton/blob/main/notebooks/07_multiple_frames_exercises.ipynb) | [![Open in Kaggle](https://img.shields.io/static/v1?label=&message=Open%20in%20Kaggle&labelColor=grey&color=blue&logo=kaggle)](https://www.kaggle.com/rohanrao/datatableton-multiple-frames-exercises) | [![Open in Binder](https://img.shields.io/static/v1?label=&message=Open%20in%20Binder&labelColor=grey&color=blue&logo=data:image/png;base64,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)](https://mybinder.org/v2/gh/vopani/datatableton/main?filepath=notebooks%2F07_multiple_frames_exercises.ipynb) | [![Open in GitHub](https://img.shields.io/static/v1?label=&message=Open%20in%20GitHub&labelColor=grey&color=blue&logo=github)](https://github.com/vopani/datatableton/blob/main/notebooks/07_multiple_frames_exercises.ipynb) |\n",
    "| Solutions | [![Open in Colab](https://img.shields.io/static/v1?label=&message=Open%20in%20Colab&labelColor=grey&color=blue&logo=google-colab)](https://colab.research.google.com/github/vopani/datatableton/blob/main/notebooks/07_multiple_frames_solutions.ipynb) | [![Open in Kaggle](https://img.shields.io/static/v1?label=&message=Open%20in%20Kaggle&labelColor=grey&color=blue&logo=kaggle)](https://www.kaggle.com/rohanrao/datatableton-multiple-frames-solutions) | [![Open in Binder](https://img.shields.io/static/v1?label=&message=Open%20in%20Binder&labelColor=grey&color=blue&logo=data:image/png;base64,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)](https://mybinder.org/v2/gh/vopani/datatableton/main?filepath=notebooks%2F07_multiple_frames_solutions.ipynb) | [![Open in GitHub](https://img.shields.io/static/v1?label=&message=Open%20in%20GitHub&labelColor=grey&color=blue&logo=github)](https://github.com/vopani/datatableton/blob/main/notebooks/07_multiple_frames_solutions.ipynb) |\n",
    "\n",
    "You can find all the exercises and solutions on [GitHub](https://github.com/vopani/datatableton#exercises-)"
   ]
  }
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