Code Templates/1.6-communicate-results-practice-solutions.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>week</th>\n",
       "      <th>storeA</th>\n",
       "      <th>storeB</th>\n",
       "      <th>storeC</th>\n",
       "      <th>storeD</th>\n",
       "      <th>storeE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014-05-04</td>\n",
       "      <td>2643</td>\n",
       "      <td>8257</td>\n",
       "      <td>3893</td>\n",
       "      <td>6231</td>\n",
       "      <td>1294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-05-11</td>\n",
       "      <td>6444</td>\n",
       "      <td>5736</td>\n",
       "      <td>5634</td>\n",
       "      <td>7092</td>\n",
       "      <td>2907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-05-18</td>\n",
       "      <td>9646</td>\n",
       "      <td>2552</td>\n",
       "      <td>4253</td>\n",
       "      <td>5447</td>\n",
       "      <td>4736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014-05-25</td>\n",
       "      <td>5960</td>\n",
       "      <td>10740</td>\n",
       "      <td>8264</td>\n",
       "      <td>6063</td>\n",
       "      <td>949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-06-01</td>\n",
       "      <td>7412</td>\n",
       "      <td>7374</td>\n",
       "      <td>3208</td>\n",
       "      <td>3985</td>\n",
       "      <td>3023</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         week  storeA  storeB  storeC  storeD  storeE\n",
       "0  2014-05-04    2643    8257    3893    6231    1294\n",
       "1  2014-05-11    6444    5736    5634    7092    2907\n",
       "2  2014-05-18    9646    2552    4253    5447    4736\n",
       "3  2014-05-25    5960   10740    8264    6063     949\n",
       "4  2014-06-01    7412    7374    3208    3985    3023"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# imports and load data\n",
    "import pandas as pd\n",
    "% matplotlib inline\n",
    "\n",
    "df = pd.read_csv('store_data.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>week</th>\n",
       "      <th>storeA</th>\n",
       "      <th>storeB</th>\n",
       "      <th>storeC</th>\n",
       "      <th>storeD</th>\n",
       "      <th>storeE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>2017-10-15</td>\n",
       "      <td>8556</td>\n",
       "      <td>11984</td>\n",
       "      <td>4792</td>\n",
       "      <td>5995</td>\n",
       "      <td>2508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>2017-10-22</td>\n",
       "      <td>3751</td>\n",
       "      <td>697</td>\n",
       "      <td>3990</td>\n",
       "      <td>4236</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>2017-10-29</td>\n",
       "      <td>4997</td>\n",
       "      <td>9759</td>\n",
       "      <td>4290</td>\n",
       "      <td>4568</td>\n",
       "      <td>2393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>2017-11-05</td>\n",
       "      <td>12785</td>\n",
       "      <td>1800</td>\n",
       "      <td>6163</td>\n",
       "      <td>5157</td>\n",
       "      <td>578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>2017-11-12</td>\n",
       "      <td>137</td>\n",
       "      <td>12261</td>\n",
       "      <td>5455</td>\n",
       "      <td>7695</td>\n",
       "      <td>2599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>2017-11-19</td>\n",
       "      <td>9960</td>\n",
       "      <td>8529</td>\n",
       "      <td>4501</td>\n",
       "      <td>7631</td>\n",
       "      <td>505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>2017-11-26</td>\n",
       "      <td>6866</td>\n",
       "      <td>5011</td>\n",
       "      <td>5401</td>\n",
       "      <td>4736</td>\n",
       "      <td>3232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>2017-12-03</td>\n",
       "      <td>5179</td>\n",
       "      <td>3850</td>\n",
       "      <td>6121</td>\n",
       "      <td>6778</td>\n",
       "      <td>113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>2017-12-10</td>\n",
       "      <td>9348</td>\n",
       "      <td>5624</td>\n",
       "      <td>5446</td>\n",
       "      <td>5448</td>\n",
       "      <td>227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>2017-12-17</td>\n",
       "      <td>5310</td>\n",
       "      <td>8647</td>\n",
       "      <td>5680</td>\n",
       "      <td>7049</td>\n",
       "      <td>3578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>2017-12-24</td>\n",
       "      <td>8976</td>\n",
       "      <td>9503</td>\n",
       "      <td>6240</td>\n",
       "      <td>3882</td>\n",
       "      <td>2890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>2017-12-31</td>\n",
       "      <td>11875</td>\n",
       "      <td>1527</td>\n",
       "      <td>6711</td>\n",
       "      <td>5265</td>\n",
       "      <td>1701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>8978</td>\n",
       "      <td>11312</td>\n",
       "      <td>4158</td>\n",
       "      <td>5019</td>\n",
       "      <td>3842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>6963</td>\n",
       "      <td>4014</td>\n",
       "      <td>4215</td>\n",
       "      <td>7153</td>\n",
       "      <td>3097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>5553</td>\n",
       "      <td>3971</td>\n",
       "      <td>3761</td>\n",
       "      <td>6255</td>\n",
       "      <td>3071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>282</td>\n",
       "      <td>6351</td>\n",
       "      <td>7759</td>\n",
       "      <td>5558</td>\n",
       "      <td>1028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>4853</td>\n",
       "      <td>6503</td>\n",
       "      <td>4187</td>\n",
       "      <td>5956</td>\n",
       "      <td>1458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>9202</td>\n",
       "      <td>3677</td>\n",
       "      <td>4540</td>\n",
       "      <td>6186</td>\n",
       "      <td>243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>2018-02-18</td>\n",
       "      <td>3512</td>\n",
       "      <td>7511</td>\n",
       "      <td>4151</td>\n",
       "      <td>5596</td>\n",
       "      <td>3501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>2018-02-25</td>\n",
       "      <td>7560</td>\n",
       "      <td>6904</td>\n",
       "      <td>3569</td>\n",
       "      <td>5045</td>\n",
       "      <td>2585</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           week  storeA  storeB  storeC  storeD  storeE\n",
       "180  2017-10-15    8556   11984    4792    5995    2508\n",
       "181  2017-10-22    3751     697    3990    4236     360\n",
       "182  2017-10-29    4997    9759    4290    4568    2393\n",
       "183  2017-11-05   12785    1800    6163    5157     578\n",
       "184  2017-11-12     137   12261    5455    7695    2599\n",
       "185  2017-11-19    9960    8529    4501    7631     505\n",
       "186  2017-11-26    6866    5011    5401    4736    3232\n",
       "187  2017-12-03    5179    3850    6121    6778     113\n",
       "188  2017-12-10    9348    5624    5446    5448     227\n",
       "189  2017-12-17    5310    8647    5680    7049    3578\n",
       "190  2017-12-24    8976    9503    6240    3882    2890\n",
       "191  2017-12-31   11875    1527    6711    5265    1701\n",
       "192  2018-01-07    8978   11312    4158    5019    3842\n",
       "193  2018-01-14    6963    4014    4215    7153    3097\n",
       "194  2018-01-21    5553    3971    3761    6255    3071\n",
       "195  2018-01-28     282    6351    7759    5558    1028\n",
       "196  2018-02-04    4853    6503    4187    5956    1458\n",
       "197  2018-02-11    9202    3677    4540    6186     243\n",
       "198  2018-02-18    3512    7511    4151    5596    3501\n",
       "199  2018-02-25    7560    6904    3569    5045    2585"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# explore data\n",
    "df.tail(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5I8lxwMXAnoF7kqQ1a1VsOVTV80muAG4B1gG7qur+gduSpDVrVYQDQFXtBfYO3ccCrZpd\nXKuAYzHmWIw5FmNTNRar4oC0JGl1WS3HHCRJq4jhIEnqGA7LIMkrhu5BkpbTqjkgPW2SBHgP8EvA\nPwROHrajlZXkx4EfVNVTSbYA7wL+oqq+OHBrKyrJP2F07O4Pj6j/M0bj80fDdDaMJOsZXSPtJ1vp\nAeBPq+r54bpaXZKsn4bx8ID0AiU5h1EgvB94HXA5sKeqnh60sRWU5N8AvwwUo+tg/TzwNeAc4L9W\n1ccGa26FJbkL+NmqeuaI+o8BX6uqdwzT2cpL8ibgNuBx4C4gwNuANwLvqarui60vV0m+XlXvao//\nsKo+NPHat6vq7cN1Nz9uOcxTkquAXwS+A3wO+CQwU1W7B21sGJcAbwFezWg83lhVz7b/Nd49aGcr\nb92RwQBQVc+swd2N/w7YWVW/O1lM8i+B3wS2DdLVMF4z8fitR7yWlWxksQyH+dvO6FpOO4EvVdVf\nJ1mrm11/3a6e+1ySv6iqZ+H/f5nxuYF7W2mvSPKaqvrBZLFtORw3UE9D2VJVv3xksaquSTL0ddBW\n2tHWDVOx3jAc5u+NwLmM/tf8u0luA141LfsPl9kJSX6B0f+Ajm+Pac//1nBtDeI64PNJPlpVjwAk\n2cjo90muG66tQfyfo7z27Ip1sTqckOT9jE76OWEa/414zGERkvwo8A8YBcW7gFur6peG7WrlJPmD\no71eVR9eqV5WgyT/HPg48NpW+t/A1VW1c7iuVl6Sh4F/PdtLwL+vqjevcEuDeTn8GzEclqjtPviF\nNXrsQROSvJbRv6nuGMRa8HJYIWrM3UoLlORkRgfe3lRV5zO61PiaHMcjx6L9tOvPVNVa253yorEA\n1uRYuPLvTfO/Eb8Et3DXM7p67Jva8/8OrJlTN49wPY7FYdfjWACjFWKS65J8pT0/M8llQ/c1kOuZ\n0uXCcFi4k6rqJuCHMDpDB3hh2JYG41iMORZj1zOlK8RjYGqXC8Nh4X6Q5PW009Hat4O/N2xLg3Es\nxhyLsaldIR4DU7tcrMl95Uv0rxj9St2bk/wXYAPwgWFbGoxjMeZYjE3tCvEYmNrlwnBYgCQ/Avwo\n8PeAn2B0it6DVfV/B21sAI7FmGPRmdoV4nKa9uXCU1kXKMk3qupnhu5jNXAsxhyLkbZC3AJ8iylc\nIS63aV4uPOawcF9N8o/bVVnXOsdizLEAquqHwKer6vmqur+q7lurwdBM7XLhlsMCJXmG0UW1XmB0\nuYAAVVXHD9rYAByLMcdiLMm/Be4BvlBrfAUzzcuF4SBpWU3zClFjhsMiJPlHwM+2p1+rqi8N2c+Q\nHIsxx0KzmdblwnBYoCRXA38X+GwrXQLcWVU7hutqGI7FmGPxYtO6Qlxu07xcGA4LlOQe4Kx24I0k\n64C7qurvDNvZynMsxhyLsWleIS63aV4u/J7D4pwAHGqPp+La7MeQYzHmWIxcwItXiLsZ/WzomguH\nZiqXC8Nh4X4TuKv92E8YbTp/YtiWBuNYjDkWLzaVK8RjYGqXC3crLUKSUxhtNge4var+58AtDcax\nGHMsRpJcAlwNvGiFWFWfG7SxgUzrcmE4LFCSW6vqvXPV1gLHYsyxeLFpXSEut2leLtytNE/tp0Ff\nDZyU5ERGCz3A8YwvTbwmOBZjjkVvYuW3Z5bamvByWC4Mh/n7CKNr0r8JuJP2xR7gGeA/DtjXEByL\nMceieTmsEJfR1C8XXltpnqrqP1TVGcBVjM7EOAP4A+Bh4BuDNrfCHIsxx+JFPsJoRfiT7f5OYAa4\nmSlZIS6Xl8NyYTgs3Aeq6vtJ3gX8fUa/erVz2JYG41iMrfmxeDmsEI+BqV0uDIeFO/yLVu8D/lNV\n3QwcN2A/Q3IsxhyLsaldIR4DU7tcGA4L990k/xn4RWBvkleydsfRsRhzLMamdoV4DEztcuGprAuU\n5NXAVuDeqnqonbL3t6vqqwO3tuIcizHHYizJl4DvAj8PvIPRlVm/VVU/PWhjA5jm5cJwkLSspnmF\nqDHDQZLUmYp9X5KklWU4SJI6hoMkqWM4SJI6hoMkqfP/AIPLDb0UT4b8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f86831243c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sales for the last month\n",
    "df.iloc[196:, 1:].sum().plot(kind='bar');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8681049978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# average sales\n",
    "df.mean().plot(kind='pie');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f86810057f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sales for the week of March 13th, 2016\n",
    "sales = df[df['week'] == '2016-03-13']\n",
    "sales.iloc[0, 1:].plot(kind='bar');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f86810015c0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8680fdc588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sales for the lastest 3-month periods\n",
    "last_three_months = df[df['week'] >= '2017-12-01']\n",
    "last_three_months.iloc[:, 1:].sum().plot(kind='pie')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}