7 Pandas Fillna,dropna methos etc.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"weather_data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temperature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/2017</td>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/4/2017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/5/2017</td>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/6/2017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/7/2017</td>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/8/2017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1/9/2017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1/10/2017</td>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1/11/2017</td>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "         day  temperature  windspeed   event\n",
       "0   1/1/2017         32.0        6.0    Rain\n",
       "1   1/4/2017          NaN        9.0   Sunny\n",
       "2   1/5/2017         28.0        NaN    Snow\n",
       "3   1/6/2017          NaN        7.0     NaN\n",
       "4   1/7/2017         32.0        NaN    Rain\n",
       "5   1/8/2017          NaN        NaN   Sunny\n",
       "6   1/9/2017          NaN        NaN     NaN\n",
       "7  1/10/2017         34.0        8.0  Cloudy\n",
       "8  1/11/2017         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temperature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
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       "      <th>1</th>\n",
       "      <td>2017-01-04</td>\n",
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       "      <td>Sunny</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-01-05</td>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Snow</td>\n",
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       "      <th>3</th>\n",
       "      <td>2017-01-06</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>2017-01-07</td>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2017-01-08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2017-01-09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2017-01-10</td>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2017-01-11</td>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         day  temperature  windspeed   event\n",
       "0 2017-01-01         32.0        6.0    Rain\n",
       "1 2017-01-04          NaN        9.0   Sunny\n",
       "2 2017-01-05         28.0        NaN    Snow\n",
       "3 2017-01-06          NaN        7.0     NaN\n",
       "4 2017-01-07         32.0        NaN    Rain\n",
       "5 2017-01-08          NaN        NaN   Sunny\n",
       "6 2017-01-09          NaN        NaN     NaN\n",
       "7 2017-01-10         34.0        8.0  Cloudy\n",
       "8 2017-01-11         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"weather_data.csv\",parse_dates=['day'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2017-01-01 00:00:00')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['day'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas._libs.tslibs.timestamps.Timestamp"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df['day'][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "      <th>temperature</th>\n",
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       "      <th>2017-01-01</th>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>2017-01-07</th>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "day                                       \n",
       "2017-01-01         32.0        6.0    Rain\n",
       "2017-01-04          NaN        9.0   Sunny\n",
       "2017-01-05         28.0        NaN    Snow\n",
       "2017-01-06          NaN        7.0     NaN\n",
       "2017-01-07         32.0        NaN    Rain\n",
       "2017-01-08          NaN        NaN   Sunny\n",
       "2017-01-09          NaN        NaN     NaN\n",
       "2017-01-10         34.0        8.0  Cloudy\n",
       "2017-01-11         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.set_index('day')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.set_index('day',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>temperature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
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       "      <th>2017-01-01</th>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-07</th>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "day                                       \n",
       "2017-01-01         32.0        6.0    Rain\n",
       "2017-01-04          NaN        9.0   Sunny\n",
       "2017-01-05         28.0        NaN    Snow\n",
       "2017-01-06          NaN        7.0     NaN\n",
       "2017-01-07         32.0        NaN    Rain\n",
       "2017-01-08          NaN        NaN   Sunny\n",
       "2017-01-09          NaN        NaN     NaN\n",
       "2017-01-10         34.0        8.0  Cloudy\n",
       "2017-01-11         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# inplace=True>>> modifies original dataframe.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# if inplace=True not given>>>> returns a new dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>temperature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
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       "      <th>2017-01-01</th>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-07</th>\n",
       "      <td>32.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "day                                       \n",
       "2017-01-01         32.0        6.0    Rain\n",
       "2017-01-04          0.0        9.0   Sunny\n",
       "2017-01-05         28.0        0.0    Snow\n",
       "2017-01-06          0.0        7.0       0\n",
       "2017-01-07         32.0        0.0    Rain\n",
       "2017-01-08          0.0        0.0   Sunny\n",
       "2017-01-09          0.0        0.0       0\n",
       "2017-01-10         34.0        8.0  Cloudy\n",
       "2017-01-11         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df = df.fillna(0)\n",
    "new_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 0 doesn't mean anything in event column. so we need to specify by using a dictionary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df = df.fillna(\n",
    "{\n",
    "    'temperature': 0,\n",
    "    'windspeed' : 0,\n",
    "    'event' : 'No event'\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <tbody>\n",
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       "      <th>2017-01-01</th>\n",
       "      <td>32.0</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>0.0</td>\n",
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       "      <th>2017-01-05</th>\n",
       "      <td>28.0</td>\n",
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       "      <th>2017-01-06</th>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>No event</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-07</th>\n",
       "      <td>32.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No event</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed     event\n",
       "day                                         \n",
       "2017-01-01         32.0        6.0      Rain\n",
       "2017-01-04          0.0        9.0     Sunny\n",
       "2017-01-05         28.0        0.0      Snow\n",
       "2017-01-06          0.0        7.0  No event\n",
       "2017-01-07         32.0        0.0      Rain\n",
       "2017-01-08          0.0        0.0     Sunny\n",
       "2017-01-09          0.0        0.0  No event\n",
       "2017-01-10         34.0        8.0    Cloudy\n",
       "2017-01-11         40.0       12.0     Sunny"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Rain</td>\n",
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       "      <th>2017-01-08</th>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "day                                       \n",
       "2017-01-01         32.0        6.0    Rain\n",
       "2017-01-04          NaN        9.0   Sunny\n",
       "2017-01-05         28.0        NaN    Snow\n",
       "2017-01-06          NaN        7.0     NaN\n",
       "2017-01-07         32.0        NaN    Rain\n",
       "2017-01-08          NaN        NaN   Sunny\n",
       "2017-01-09          NaN        NaN     NaN\n",
       "2017-01-10         34.0        8.0  Cloudy\n",
       "2017-01-11         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df = df.fillna(method='ffill')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>7.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>32.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Sunny</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>32.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "day                                       \n",
       "2017-01-01         32.0        6.0    Rain\n",
       "2017-01-04         32.0        9.0   Sunny\n",
       "2017-01-05         28.0        9.0    Snow\n",
       "2017-01-06         28.0        7.0    Snow\n",
       "2017-01-07         32.0        7.0    Rain\n",
       "2017-01-08         32.0        7.0   Sunny\n",
       "2017-01-09         32.0        7.0   Sunny\n",
       "2017-01-10         34.0        8.0  Cloudy\n",
       "2017-01-11         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df = df.fillna(method='bfill')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>32.0</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>34.0</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "day                                       \n",
       "2017-01-01         32.0        6.0    Rain\n",
       "2017-01-04         28.0        9.0   Sunny\n",
       "2017-01-05         28.0        7.0    Snow\n",
       "2017-01-06         32.0        7.0    Rain\n",
       "2017-01-07         32.0        8.0    Rain\n",
       "2017-01-08         34.0        8.0   Sunny\n",
       "2017-01-09         34.0        8.0  Cloudy\n",
       "2017-01-10         34.0        8.0  Cloudy\n",
       "2017-01-11         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>Sunny</td>\n",
       "      <td>Sunny</td>\n",
       "      <td>Sunny</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34</td>\n",
       "      <td>8</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40</td>\n",
       "      <td>12</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           temperature windspeed   event\n",
       "day                                     \n",
       "2017-01-01          32         6    Rain\n",
       "2017-01-04           9         9   Sunny\n",
       "2017-01-05          28      Snow    Snow\n",
       "2017-01-06           7         7     NaN\n",
       "2017-01-07          32      Rain    Rain\n",
       "2017-01-08       Sunny     Sunny   Sunny\n",
       "2017-01-09         NaN       NaN     NaN\n",
       "2017-01-10          34         8  Cloudy\n",
       "2017-01-11          40        12   Sunny"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df = df.fillna(method='bfill',axis='columns')\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
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       "      <th>event</th>\n",
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       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-01</th>\n",
       "      <td>32</td>\n",
       "      <td>6</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-07</th>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34</td>\n",
       "      <td>8</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40</td>\n",
       "      <td>12</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           temperature windspeed   event\n",
       "day                                     \n",
       "2017-01-01          32         6    Rain\n",
       "2017-01-04         NaN         9   Sunny\n",
       "2017-01-05          28        28    Snow\n",
       "2017-01-06         NaN         7       7\n",
       "2017-01-07          32        32    Rain\n",
       "2017-01-08         NaN       NaN   Sunny\n",
       "2017-01-09         NaN       NaN     NaN\n",
       "2017-01-10          34         8  Cloudy\n",
       "2017-01-11          40        12   Sunny"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df = df.fillna(method='ffill',axis='columns')\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>temperature</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-01</th>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>32.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>28.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Snow</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>28.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Snow</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-07</th>\n",
       "      <td>32.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "day                                       \n",
       "2017-01-01         32.0        6.0    Rain\n",
       "2017-01-04         32.0        9.0   Sunny\n",
       "2017-01-05         28.0        9.0    Snow\n",
       "2017-01-06         28.0        7.0    Snow\n",
       "2017-01-07         32.0        7.0    Rain\n",
       "2017-01-08         32.0        NaN   Sunny\n",
       "2017-01-09          NaN        NaN   Sunny\n",
       "2017-01-10         34.0        8.0  Cloudy\n",
       "2017-01-11         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df = df.fillna(method='ffill',limit=1)\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>windspeed</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-01</th>\n",
       "      <td>32.000000</td>\n",
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       "      <td>Rain</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>9.00</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>28.000000</td>\n",
       "      <td>8.00</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>7.00</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-07</th>\n",
       "      <td>32.000000</td>\n",
       "      <td>7.25</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>32.666667</td>\n",
       "      <td>7.50</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>33.333333</td>\n",
       "      <td>7.75</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.000000</td>\n",
       "      <td>8.00</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.000000</td>\n",
       "      <td>12.00</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "day                                       \n",
       "2017-01-01    32.000000       6.00    Rain\n",
       "2017-01-04    30.000000       9.00   Sunny\n",
       "2017-01-05    28.000000       8.00    Snow\n",
       "2017-01-06    30.000000       7.00     NaN\n",
       "2017-01-07    32.000000       7.25    Rain\n",
       "2017-01-08    32.666667       7.50   Sunny\n",
       "2017-01-09    33.333333       7.75     NaN\n",
       "2017-01-10    34.000000       8.00  Cloudy\n",
       "2017-01-11    40.000000      12.00   Sunny"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df = df.interpolate()\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>29.000000</td>\n",
       "      <td>9.00</td>\n",
       "      <td>Sunny</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>28.000000</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>30.000000</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-07</th>\n",
       "      <td>32.000000</td>\n",
       "      <td>7.25</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>32.666667</td>\n",
       "      <td>7.50</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>33.333333</td>\n",
       "      <td>7.75</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.000000</td>\n",
       "      <td>8.00</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.000000</td>\n",
       "      <td>12.00</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "day                                       \n",
       "2017-01-01    32.000000       6.00    Rain\n",
       "2017-01-04    29.000000       9.00   Sunny\n",
       "2017-01-05    28.000000       8.00    Snow\n",
       "2017-01-06    30.000000       7.00     NaN\n",
       "2017-01-07    32.000000       7.25    Rain\n",
       "2017-01-08    32.666667       7.50   Sunny\n",
       "2017-01-09    33.333333       7.75     NaN\n",
       "2017-01-10    34.000000       8.00  Cloudy\n",
       "2017-01-11    40.000000      12.00   Sunny"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df = df.interpolate(method='time')\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
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       "      <th>2017-01-01</th>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "day                                       \n",
       "2017-01-01         32.0        6.0    Rain\n",
       "2017-01-10         34.0        8.0  Cloudy\n",
       "2017-01-11         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df = df.dropna()\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th>2017-01-01</th>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
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       "      <th>2017-01-05</th>\n",
       "      <td>28.0</td>\n",
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       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-07</th>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "day                                       \n",
       "2017-01-01         32.0        6.0    Rain\n",
       "2017-01-04          NaN        9.0   Sunny\n",
       "2017-01-05         28.0        NaN    Snow\n",
       "2017-01-06          NaN        7.0     NaN\n",
       "2017-01-07         32.0        NaN    Rain\n",
       "2017-01-08          NaN        NaN   Sunny\n",
       "2017-01-10         34.0        8.0  Cloudy\n",
       "2017-01-11         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df = df.dropna(how='all')\n",
    "new_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# how='all>> if all values in the row is NaN then drop that.\n",
    "# threshold parameter>> thresh=1>> acts same way, if at least one value in the row then keep the row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>temperature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-01</th>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-07</th>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "day                                       \n",
       "2017-01-01         32.0        6.0    Rain\n",
       "2017-01-04          NaN        9.0   Sunny\n",
       "2017-01-05         28.0        NaN    Snow\n",
       "2017-01-06          NaN        7.0     NaN\n",
       "2017-01-07         32.0        NaN    Rain\n",
       "2017-01-08          NaN        NaN   Sunny\n",
       "2017-01-10         34.0        8.0  Cloudy\n",
       "2017-01-11         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df = df.dropna(thresh=1)\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
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       "      <th>2017-01-01</th>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Rain</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-07</th>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rain</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "day                                       \n",
       "2017-01-01         32.0        6.0    Rain\n",
       "2017-01-04          NaN        9.0   Sunny\n",
       "2017-01-05         28.0        NaN    Snow\n",
       "2017-01-07         32.0        NaN    Rain\n",
       "2017-01-10         34.0        8.0  Cloudy\n",
       "2017-01-11         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df = df.dropna(thresh=2)\n",
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt = pd.date_range(\"01-01-2017\",\"01-11-2017\")\n",
    "idx = pd.DatetimeIndex(dt)\n",
    "df = df.reindex(idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>2017-01-01</th>\n",
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       "    <tr>\n",
       "      <th>2017-01-02</th>\n",
       "      <td>NaN</td>\n",
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       "      <th>2017-01-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
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       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>28.0</td>\n",
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       "      <td>Snow</td>\n",
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       "      <th>2017-01-06</th>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-07</th>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-10</th>\n",
       "      <td>34.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Cloudy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-11</th>\n",
       "      <td>40.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            temperature  windspeed   event\n",
       "2017-01-01         32.0        6.0    Rain\n",
       "2017-01-02          NaN        NaN     NaN\n",
       "2017-01-03          NaN        NaN     NaN\n",
       "2017-01-04          NaN        9.0   Sunny\n",
       "2017-01-05         28.0        NaN    Snow\n",
       "2017-01-06          NaN        7.0     NaN\n",
       "2017-01-07         32.0        NaN    Rain\n",
       "2017-01-08          NaN        NaN   Sunny\n",
       "2017-01-09          NaN        NaN     NaN\n",
       "2017-01-10         34.0        8.0  Cloudy\n",
       "2017-01-11         40.0       12.0   Sunny"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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