converting to dask dataframe.ipynb

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  {
   "cell_type": "code",
   "execution_count": 12,
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   "outputs": [],
   "source": [
    "# to suppress future warnings\n",
    "import warnings\n",
    "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
    "\n",
    "import pandas as pd\n",
    "import dask.dataframe as dd\n",
    "\n",
    "dt = pd.DataFrame(data)\n",
    "dt = pd.DataFrame(data[1:], columns=data[0][:12]) #Formatting the header\n",
    "df = dd.from_pandas(dt,npartitions=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        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>Country,Other</th>\n",
       "      <th>TotalCases</th>\n",
       "      <th>NewCases</th>\n",
       "      <th>TotalDeaths</th>\n",
       "      <th>NewDeaths</th>\n",
       "      <th>TotalRecovered</th>\n",
       "      <th>ActiveCases</th>\n",
       "      <th>Serious,Critical</th>\n",
       "      <th>Tot Cases/1M pop</th>\n",
       "      <th>Deaths/1M pop</th>\n",
       "      <th>TotalTests</th>\n",
       "      <th>Tests/</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>World</td>\n",
       "      <td>2,632,532</td>\n",
       "      <td>+76,772</td>\n",
       "      <td>183,866</td>\n",
       "      <td>+6,407</td>\n",
       "      <td>716,877</td>\n",
       "      <td>1,731,789</td>\n",
       "      <td>56,678</td>\n",
       "      <td>338</td>\n",
       "      <td>23.6</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>USA</td>\n",
       "      <td>846,294</td>\n",
       "      <td>+27,550</td>\n",
       "      <td>47,524</td>\n",
       "      <td>+2,206</td>\n",
       "      <td>83,917</td>\n",
       "      <td>714,853</td>\n",
       "      <td>14,014</td>\n",
       "      <td>2,557</td>\n",
       "      <td>144</td>\n",
       "      <td>4,319,358</td>\n",
       "      <td>13,049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Spain</td>\n",
       "      <td>208,389</td>\n",
       "      <td>+4,211</td>\n",
       "      <td>21,717</td>\n",
       "      <td>+435</td>\n",
       "      <td>85,915</td>\n",
       "      <td>100,757</td>\n",
       "      <td>7,705</td>\n",
       "      <td>4,457</td>\n",
       "      <td>464</td>\n",
       "      <td>930,230</td>\n",
       "      <td>19,896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Italy</td>\n",
       "      <td>187,327</td>\n",
       "      <td>+3,370</td>\n",
       "      <td>25,085</td>\n",
       "      <td>+437</td>\n",
       "      <td>54,543</td>\n",
       "      <td>107,699</td>\n",
       "      <td>2,384</td>\n",
       "      <td>3,098</td>\n",
       "      <td>415</td>\n",
       "      <td>1,513,251</td>\n",
       "      <td>25,028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>France</td>\n",
       "      <td>159,877</td>\n",
       "      <td>+1,827</td>\n",
       "      <td>21,340</td>\n",
       "      <td>+544</td>\n",
       "      <td>40,657</td>\n",
       "      <td>97,880</td>\n",
       "      <td>5,218</td>\n",
       "      <td>2,449</td>\n",
       "      <td>327</td>\n",
       "      <td>463,662</td>\n",
       "      <td>7,103</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Country,Other TotalCases NewCases TotalDeaths NewDeaths TotalRecovered  \\\n",
       "0         World  2,632,532  +76,772     183,866    +6,407        716,877   \n",
       "1           USA    846,294  +27,550     47,524     +2,206         83,917   \n",
       "2         Spain    208,389   +4,211     21,717       +435         85,915   \n",
       "3         Italy    187,327   +3,370     25,085       +437         54,543   \n",
       "4        France    159,877   +1,827     21,340       +544         40,657   \n",
       "\n",
       "  ActiveCases Serious,Critical Tot Cases/1M pop Deaths/1M pop TotalTests  \\\n",
       "0   1,731,789           56,678              338          23.6              \n",
       "1     714,853           14,014            2,557           144  4,319,358   \n",
       "2     100,757            7,705            4,457           464    930,230   \n",
       "3     107,699            2,384            3,098           415  1,513,251   \n",
       "4      97,880            5,218            2,449           327    463,662   \n",
       "\n",
       "   Tests/  \n",
       "0          \n",
       "1  13,049  \n",
       "2  19,896  \n",
       "3  25,028  \n",
       "4   7,103  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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