42_Pandas.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "af9d77df",
   "metadata": {},
   "source": [
    "# Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "30af79ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ff1f9439",
   "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>EST</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>DewPoint</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Sea Level PressureIn</th>\n",
       "      <th>VisibilityMiles</th>\n",
       "      <th>WindSpeedMPH</th>\n",
       "      <th>PrecipitationIn</th>\n",
       "      <th>CloudCover</th>\n",
       "      <th>Events</th>\n",
       "      <th>WindDirDegrees</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/2016</td>\n",
       "      <td>38</td>\n",
       "      <td>23</td>\n",
       "      <td>52</td>\n",
       "      <td>30.03</td>\n",
       "      <td>10</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2016</td>\n",
       "      <td>36</td>\n",
       "      <td>18</td>\n",
       "      <td>46</td>\n",
       "      <td>30.02</td>\n",
       "      <td>10</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/3/2016</td>\n",
       "      <td>40</td>\n",
       "      <td>21</td>\n",
       "      <td>47</td>\n",
       "      <td>29.86</td>\n",
       "      <td>10</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2016</td>\n",
       "      <td>25</td>\n",
       "      <td>9</td>\n",
       "      <td>44</td>\n",
       "      <td>30.05</td>\n",
       "      <td>10</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/5/2016</td>\n",
       "      <td>20</td>\n",
       "      <td>-3</td>\n",
       "      <td>41</td>\n",
       "      <td>30.57</td>\n",
       "      <td>10</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/6/2016</td>\n",
       "      <td>33</td>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "      <td>30.50</td>\n",
       "      <td>10</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1/7/2016</td>\n",
       "      <td>39</td>\n",
       "      <td>11</td>\n",
       "      <td>33</td>\n",
       "      <td>30.28</td>\n",
       "      <td>10</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1/8/2016</td>\n",
       "      <td>39</td>\n",
       "      <td>29</td>\n",
       "      <td>64</td>\n",
       "      <td>30.20</td>\n",
       "      <td>10</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1/9/2016</td>\n",
       "      <td>44</td>\n",
       "      <td>38</td>\n",
       "      <td>77</td>\n",
       "      <td>30.16</td>\n",
       "      <td>9</td>\n",
       "      <td>8.0</td>\n",
       "      <td>T</td>\n",
       "      <td>8</td>\n",
       "      <td>Rain</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1/10/2016</td>\n",
       "      <td>50</td>\n",
       "      <td>46</td>\n",
       "      <td>71</td>\n",
       "      <td>29.59</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.8</td>\n",
       "      <td>7</td>\n",
       "      <td>Rain</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1/11/2016</td>\n",
       "      <td>33</td>\n",
       "      <td>8</td>\n",
       "      <td>37</td>\n",
       "      <td>29.92</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1/12/2016</td>\n",
       "      <td>35</td>\n",
       "      <td>15</td>\n",
       "      <td>53</td>\n",
       "      <td>29.85</td>\n",
       "      <td>10</td>\n",
       "      <td>6.0</td>\n",
       "      <td>T</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1/13/2016</td>\n",
       "      <td>26</td>\n",
       "      <td>4</td>\n",
       "      <td>42</td>\n",
       "      <td>29.94</td>\n",
       "      <td>10</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1/14/2016</td>\n",
       "      <td>30</td>\n",
       "      <td>12</td>\n",
       "      <td>47</td>\n",
       "      <td>29.95</td>\n",
       "      <td>10</td>\n",
       "      <td>5.0</td>\n",
       "      <td>T</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1/15/2016</td>\n",
       "      <td>43</td>\n",
       "      <td>31</td>\n",
       "      <td>62</td>\n",
       "      <td>29.82</td>\n",
       "      <td>9</td>\n",
       "      <td>5.0</td>\n",
       "      <td>T</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1/16/2016</td>\n",
       "      <td>47</td>\n",
       "      <td>37</td>\n",
       "      <td>70</td>\n",
       "      <td>29.52</td>\n",
       "      <td>8</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.24</td>\n",
       "      <td>7</td>\n",
       "      <td>Rain</td>\n",
       "      <td>340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1/17/2016</td>\n",
       "      <td>36</td>\n",
       "      <td>23</td>\n",
       "      <td>66</td>\n",
       "      <td>29.78</td>\n",
       "      <td>8</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.05</td>\n",
       "      <td>6</td>\n",
       "      <td>Fog-Snow</td>\n",
       "      <td>345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1/18/2016</td>\n",
       "      <td>25</td>\n",
       "      <td>6</td>\n",
       "      <td>53</td>\n",
       "      <td>29.83</td>\n",
       "      <td>9</td>\n",
       "      <td>12.0</td>\n",
       "      <td>T</td>\n",
       "      <td>2</td>\n",
       "      <td>Snow</td>\n",
       "      <td>293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1/19/2016</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>42</td>\n",
       "      <td>30.03</td>\n",
       "      <td>10</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1/20/2016</td>\n",
       "      <td>32</td>\n",
       "      <td>15</td>\n",
       "      <td>49</td>\n",
       "      <td>30.13</td>\n",
       "      <td>10</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1/21/2016</td>\n",
       "      <td>31</td>\n",
       "      <td>11</td>\n",
       "      <td>45</td>\n",
       "      <td>30.15</td>\n",
       "      <td>10</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1/22/2016</td>\n",
       "      <td>26</td>\n",
       "      <td>6</td>\n",
       "      <td>41</td>\n",
       "      <td>30.21</td>\n",
       "      <td>9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.01</td>\n",
       "      <td>3</td>\n",
       "      <td>Snow</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1/23/2016</td>\n",
       "      <td>26</td>\n",
       "      <td>21</td>\n",
       "      <td>78</td>\n",
       "      <td>29.77</td>\n",
       "      <td>1</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2.31</td>\n",
       "      <td>8</td>\n",
       "      <td>Fog-Snow</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1/24/2016</td>\n",
       "      <td>28</td>\n",
       "      <td>11</td>\n",
       "      <td>53</td>\n",
       "      <td>29.92</td>\n",
       "      <td>8</td>\n",
       "      <td>6.0</td>\n",
       "      <td>T</td>\n",
       "      <td>3</td>\n",
       "      <td>Snow</td>\n",
       "      <td>327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1/25/2016</td>\n",
       "      <td>34</td>\n",
       "      <td>18</td>\n",
       "      <td>54</td>\n",
       "      <td>30.25</td>\n",
       "      <td>10</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1/26/2016</td>\n",
       "      <td>43</td>\n",
       "      <td>29</td>\n",
       "      <td>56</td>\n",
       "      <td>30.03</td>\n",
       "      <td>10</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1/27/2016</td>\n",
       "      <td>41</td>\n",
       "      <td>22</td>\n",
       "      <td>45</td>\n",
       "      <td>30.03</td>\n",
       "      <td>10</td>\n",
       "      <td>7.0</td>\n",
       "      <td>T</td>\n",
       "      <td>3</td>\n",
       "      <td>Rain</td>\n",
       "      <td>311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1/28/2016</td>\n",
       "      <td>37</td>\n",
       "      <td>20</td>\n",
       "      <td>51</td>\n",
       "      <td>29.90</td>\n",
       "      <td>10</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1/29/2016</td>\n",
       "      <td>36</td>\n",
       "      <td>21</td>\n",
       "      <td>50</td>\n",
       "      <td>29.58</td>\n",
       "      <td>10</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1/30/2016</td>\n",
       "      <td>34</td>\n",
       "      <td>16</td>\n",
       "      <td>46</td>\n",
       "      <td>30.01</td>\n",
       "      <td>10</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1/31/2016</td>\n",
       "      <td>46</td>\n",
       "      <td>28</td>\n",
       "      <td>52</td>\n",
       "      <td>29.90</td>\n",
       "      <td>10</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>241</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          EST  Temperature  DewPoint  Humidity  Sea Level PressureIn  \\\n",
       "0    1/1/2016           38        23        52                 30.03   \n",
       "1    1/2/2016           36        18        46                 30.02   \n",
       "2    1/3/2016           40        21        47                 29.86   \n",
       "3    1/4/2016           25         9        44                 30.05   \n",
       "4    1/5/2016           20        -3        41                 30.57   \n",
       "5    1/6/2016           33         4        35                 30.50   \n",
       "6    1/7/2016           39        11        33                 30.28   \n",
       "7    1/8/2016           39        29        64                 30.20   \n",
       "8    1/9/2016           44        38        77                 30.16   \n",
       "9   1/10/2016           50        46        71                 29.59   \n",
       "10  1/11/2016           33         8        37                 29.92   \n",
       "11  1/12/2016           35        15        53                 29.85   \n",
       "12  1/13/2016           26         4        42                 29.94   \n",
       "13  1/14/2016           30        12        47                 29.95   \n",
       "14  1/15/2016           43        31        62                 29.82   \n",
       "15  1/16/2016           47        37        70                 29.52   \n",
       "16  1/17/2016           36        23        66                 29.78   \n",
       "17  1/18/2016           25         6        53                 29.83   \n",
       "18  1/19/2016           22         3        42                 30.03   \n",
       "19  1/20/2016           32        15        49                 30.13   \n",
       "20  1/21/2016           31        11        45                 30.15   \n",
       "21  1/22/2016           26         6        41                 30.21   \n",
       "22  1/23/2016           26        21        78                 29.77   \n",
       "23  1/24/2016           28        11        53                 29.92   \n",
       "24  1/25/2016           34        18        54                 30.25   \n",
       "25  1/26/2016           43        29        56                 30.03   \n",
       "26  1/27/2016           41        22        45                 30.03   \n",
       "27  1/28/2016           37        20        51                 29.90   \n",
       "28  1/29/2016           36        21        50                 29.58   \n",
       "29  1/30/2016           34        16        46                 30.01   \n",
       "30  1/31/2016           46        28        52                 29.90   \n",
       "\n",
       "    VisibilityMiles  WindSpeedMPH PrecipitationIn  CloudCover    Events  \\\n",
       "0                10           8.0               0           5       NaN   \n",
       "1                10           7.0               0           3       NaN   \n",
       "2                10           8.0               0           1       NaN   \n",
       "3                10           9.0               0           3       NaN   \n",
       "4                10           5.0               0           0       NaN   \n",
       "5                10           4.0               0           0       NaN   \n",
       "6                10           2.0               0           3       NaN   \n",
       "7                10           4.0               0           8       NaN   \n",
       "8                 9           8.0               T           8      Rain   \n",
       "9                 4           NaN             1.8           7      Rain   \n",
       "10               10           NaN               0           1       NaN   \n",
       "11               10           6.0               T           4       NaN   \n",
       "12               10          10.0               0           0       NaN   \n",
       "13               10           5.0               T           7       NaN   \n",
       "14                9           5.0               T           2       NaN   \n",
       "15                8           7.0            0.24           7      Rain   \n",
       "16                8           6.0            0.05           6  Fog-Snow   \n",
       "17                9          12.0               T           2      Snow   \n",
       "18               10          11.0               0           1       NaN   \n",
       "19               10           6.0               0           2       NaN   \n",
       "20               10           6.0               0           1       NaN   \n",
       "21                9           NaN            0.01           3      Snow   \n",
       "22                1          16.0            2.31           8  Fog-Snow   \n",
       "23                8           6.0               T           3      Snow   \n",
       "24               10           3.0               0           2       NaN   \n",
       "25               10           7.0               0           2       NaN   \n",
       "26               10           7.0               T           3      Rain   \n",
       "27               10           5.0               0           1       NaN   \n",
       "28               10           8.0               0           4       NaN   \n",
       "29               10           7.0               0           0       NaN   \n",
       "30               10           5.0               0           0       NaN   \n",
       "\n",
       "    WindDirDegrees  \n",
       "0              281  \n",
       "1              275  \n",
       "2              277  \n",
       "3              345  \n",
       "4              333  \n",
       "5              259  \n",
       "6              293  \n",
       "7               79  \n",
       "8               76  \n",
       "9              109  \n",
       "10             289  \n",
       "11             235  \n",
       "12             284  \n",
       "13             266  \n",
       "14             101  \n",
       "15             340  \n",
       "16             345  \n",
       "17             293  \n",
       "18             293  \n",
       "19             302  \n",
       "20             312  \n",
       "21              34  \n",
       "22              42  \n",
       "23             327  \n",
       "24             286  \n",
       "25             244  \n",
       "26             311  \n",
       "27             234  \n",
       "28             298  \n",
       "29             257  \n",
       "30             241  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('nyc_weather.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "aea42a85",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4bf501cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# help(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0d79f67a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     38\n",
       "1     36\n",
       "2     40\n",
       "3     25\n",
       "4     20\n",
       "5     33\n",
       "6     39\n",
       "7     39\n",
       "8     44\n",
       "9     50\n",
       "10    33\n",
       "11    35\n",
       "12    26\n",
       "13    30\n",
       "14    43\n",
       "15    47\n",
       "16    36\n",
       "17    25\n",
       "18    22\n",
       "19    32\n",
       "20    31\n",
       "21    26\n",
       "22    26\n",
       "23    28\n",
       "24    34\n",
       "25    43\n",
       "26    41\n",
       "27    37\n",
       "28    36\n",
       "29    34\n",
       "30    46\n",
       "Name: Temperature, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Temperature']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f091be9b",
   "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>Temperature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Temperature\n",
       "0            38\n",
       "1            36\n",
       "2            40\n",
       "3            25\n",
       "4            20\n",
       "5            33\n",
       "6            39\n",
       "7            39\n",
       "8            44\n",
       "9            50\n",
       "10           33\n",
       "11           35\n",
       "12           26\n",
       "13           30\n",
       "14           43\n",
       "15           47\n",
       "16           36\n",
       "17           25\n",
       "18           22\n",
       "19           32\n",
       "20           31\n",
       "21           26\n",
       "22           26\n",
       "23           28\n",
       "24           34\n",
       "25           43\n",
       "26           41\n",
       "27           37\n",
       "28           36\n",
       "29           34\n",
       "30           46"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['Temperature']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1a962b91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df['Temperature'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9910ee60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df['Temperature'][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "93c89292",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "38"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Temperature'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1a1ce3d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Temperature'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "211a8d63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.892857142857143"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['WindSpeedMPH'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "068b145a",
   "metadata": {},
   "source": [
    "## creating a DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a5f100d6",
   "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>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/2022</td>\n",
       "      <td>32</td>\n",
       "      <td>6</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2022</td>\n",
       "      <td>35</td>\n",
       "      <td>7</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/3/2022</td>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2022</td>\n",
       "      <td>24</td>\n",
       "      <td>4</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/5/2022</td>\n",
       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/6/2022</td>\n",
       "      <td>31</td>\n",
       "      <td>7</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  temprature  windspeed  event\n",
       "0  1/1/2022          32          6   Rain\n",
       "1  1/2/2022          35          7  Sunny\n",
       "2  1/3/2022          28          2   Snow\n",
       "3  1/4/2022          24          4   Rain\n",
       "4  1/5/2022          32          2  Sunny\n",
       "5  1/6/2022          31          7   Snow"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_data = {\n",
    "    'day':['1/1/2022','1/2/2022','1/3/2022','1/4/2022','1/5/2022','1/6/2022'],\n",
    "    'temprature': [32,35,28,24,32,31],\n",
    "    'windspeed':[6,7,2,4,2,7],\n",
    "    'event':['Rain','Sunny','Snow','Rain','Sunny', 'Snow']\n",
    "}\n",
    "#             str()\n",
    "df = pd.DataFrame(weather_data)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "76f10113",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6, 4)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5d9c7695",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7097520c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.ndim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f836dbd0",
   "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>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/2022</td>\n",
       "      <td>32</td>\n",
       "      <td>6</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2022</td>\n",
       "      <td>35</td>\n",
       "      <td>7</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/3/2022</td>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2022</td>\n",
       "      <td>24</td>\n",
       "      <td>4</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/5/2022</td>\n",
       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  temprature  windspeed  event\n",
       "0  1/1/2022          32          6   Rain\n",
       "1  1/2/2022          35          7  Sunny\n",
       "2  1/3/2022          28          2   Snow\n",
       "3  1/4/2022          24          4   Rain\n",
       "4  1/5/2022          32          2  Sunny"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()  # default starting 5 rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ee2f9c5c",
   "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>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/2022</td>\n",
       "      <td>32</td>\n",
       "      <td>6</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2022</td>\n",
       "      <td>35</td>\n",
       "      <td>7</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/3/2022</td>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  temprature  windspeed  event\n",
       "0  1/1/2022          32          6   Rain\n",
       "1  1/2/2022          35          7  Sunny\n",
       "2  1/3/2022          28          2   Snow"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "82a4ad80",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/2022</td>\n",
       "      <td>32</td>\n",
       "      <td>6</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2022</td>\n",
       "      <td>35</td>\n",
       "      <td>7</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  temprature  windspeed  event\n",
       "0  1/1/2022          32          6   Rain\n",
       "1  1/2/2022          35          7  Sunny"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "60ff3cef",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2022</td>\n",
       "      <td>35</td>\n",
       "      <td>7</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/3/2022</td>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2022</td>\n",
       "      <td>24</td>\n",
       "      <td>4</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/5/2022</td>\n",
       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/6/2022</td>\n",
       "      <td>31</td>\n",
       "      <td>7</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  temprature  windspeed  event\n",
       "1  1/2/2022          35          7  Sunny\n",
       "2  1/3/2022          28          2   Snow\n",
       "3  1/4/2022          24          4   Rain\n",
       "4  1/5/2022          32          2  Sunny\n",
       "5  1/6/2022          31          7   Snow"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "558e69c8",
   "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",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2022</td>\n",
       "      <td>24</td>\n",
       "      <td>4</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/5/2022</td>\n",
       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/6/2022</td>\n",
       "      <td>31</td>\n",
       "      <td>7</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  temprature  windspeed  event\n",
       "3  1/4/2022          24          4   Rain\n",
       "4  1/5/2022          32          2  Sunny\n",
       "5  1/6/2022          31          7   Snow"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c459ec27",
   "metadata": {},
   "source": [
    "## slicing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ed73a5dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2022</td>\n",
       "      <td>35</td>\n",
       "      <td>7</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/3/2022</td>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2022</td>\n",
       "      <td>24</td>\n",
       "      <td>4</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  temprature  windspeed  event\n",
       "1  1/2/2022          35          7  Sunny\n",
       "2  1/3/2022          28          2   Snow\n",
       "3  1/4/2022          24          4   Rain"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[1:4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b7228a8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\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>day</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2022</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/3/2022</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2022</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  event\n",
       "1  1/2/2022  Sunny\n",
       "2  1/3/2022   Snow\n",
       "3  1/4/2022   Rain"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[1:4][['day','event']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "bb1b4007",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>day</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/2022</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2022</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/6/2022</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  event\n",
       "0  1/1/2022   Rain\n",
       "1  1/2/2022  Sunny\n",
       "5  1/6/2022   Snow"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[0:][['day','event']][df['windspeed'] >= 6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "1b64bb2e",
   "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",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\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>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/2022</td>\n",
       "      <td>32</td>\n",
       "      <td>6</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2022</td>\n",
       "      <td>35</td>\n",
       "      <td>7</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/6/2022</td>\n",
       "      <td>31</td>\n",
       "      <td>7</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  temprature  windspeed  event\n",
       "0  1/1/2022          32          6   Rain\n",
       "1  1/2/2022          35          7  Sunny\n",
       "5  1/6/2022          31          7   Snow"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[0:][df['windspeed'] >= 6]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d35ac003",
   "metadata": {},
   "source": [
    "## columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ee0d5df6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['day', 'temprature', 'windspeed', 'event'], dtype='object')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "a08ddc76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1/1/2022\n",
       "1    1/2/2022\n",
       "2    1/3/2022\n",
       "3    1/4/2022\n",
       "4    1/5/2022\n",
       "5    1/6/2022\n",
       "Name: day, dtype: object"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['day']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "25c664c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1/1/2022\n",
       "1    1/2/2022\n",
       "2    1/3/2022\n",
       "3    1/4/2022\n",
       "4    1/5/2022\n",
       "5    1/6/2022\n",
       "Name: day, dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.day"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1612071",
   "metadata": {},
   "source": [
    "## operations on dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "1f95a4cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['temprature'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "bd8a843b",
   "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",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2022</td>\n",
       "      <td>35</td>\n",
       "      <td>7</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  temprature  windspeed  event\n",
       "1  1/2/2022          35          7  Sunny"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['temprature'] > 32]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "4cdcbfde",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2022</td>\n",
       "      <td>35</td>\n",
       "      <td>7</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  temprature  windspeed  event\n",
       "1  1/2/2022          35          7  Sunny"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['temprature'] == df['temprature'].max()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "cb9f5282",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/2022</td>\n",
       "      <td>32</td>\n",
       "      <td>6</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2022</td>\n",
       "      <td>35</td>\n",
       "      <td>7</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/3/2022</td>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2022</td>\n",
       "      <td>24</td>\n",
       "      <td>4</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/5/2022</td>\n",
       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/6/2022</td>\n",
       "      <td>31</td>\n",
       "      <td>7</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  temprature  windspeed  event\n",
       "0  1/1/2022          32          6   Rain\n",
       "1  1/2/2022          35          7  Sunny\n",
       "2  1/3/2022          28          2   Snow\n",
       "3  1/4/2022          24          4   Rain\n",
       "4  1/5/2022          32          2  Sunny\n",
       "5  1/6/2022          31          7   Snow"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "4c08a93a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.8297084310253524"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['temprature'].std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "4350efe8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Sunny'"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['event'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "83ba44b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "statistics\n",
    "\n",
    "1. Descriptive Statistics\n",
    "2. Infrential Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "5f27931b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>30.333333</td>\n",
       "      <td>4.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.829708</td>\n",
       "      <td>2.338090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>24.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>28.750000</td>\n",
       "      <td>2.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>31.500000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>32.000000</td>\n",
       "      <td>6.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>35.000000</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       temprature  windspeed\n",
       "count    6.000000   6.000000\n",
       "mean    30.333333   4.666667\n",
       "std      3.829708   2.338090\n",
       "min     24.000000   2.000000\n",
       "25%     28.750000   2.500000\n",
       "50%     31.500000   5.000000\n",
       "75%     32.000000   6.750000\n",
       "max     35.000000   7.000000"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "c64a4bf9",
   "metadata": {},
   "outputs": [
    {
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       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
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       "      <td>1/1/2022</td>\n",
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       "    <tr>\n",
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       "      <td>1/2/2022</td>\n",
       "      <td>35</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/3/2022</td>\n",
       "      <td>28</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/6/2022</td>\n",
       "      <td>31</td>\n",
       "      <td>7</td>\n",
       "      <td>Snow</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  temprature  windspeed  event\n",
       "0  1/1/2022          32          6   Rain\n",
       "1  1/2/2022          35          7  Sunny\n",
       "2  1/3/2022          28          2   Snow\n",
       "3  1/4/2022          24          4   Rain\n",
       "4  1/5/2022          32          2  Sunny\n",
       "5  1/6/2022          31          7   Snow"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53d806fc",
   "metadata": {},
   "source": [
    "## write to csv and excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "1dc0d591",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>day</th>\n",
       "      <th>temprature</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>event</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/1/2022</td>\n",
       "      <td>32</td>\n",
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       "      <td>Rain</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/2/2022</td>\n",
       "      <td>35</td>\n",
       "      <td>7</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/3/2022</td>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/4/2022</td>\n",
       "      <td>24</td>\n",
       "      <td>4</td>\n",
       "      <td>Rain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/5/2022</td>\n",
       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "      <td>Sunny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1/6/2022</td>\n",
       "      <td>31</td>\n",
       "      <td>7</td>\n",
       "      <td>Snow</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        day  temprature  windspeed  event\n",
       "0  1/1/2022          32          6   Rain\n",
       "1  1/2/2022          35          7  Sunny\n",
       "2  1/3/2022          28          2   Snow\n",
       "3  1/4/2022          24          4   Rain\n",
       "4  1/5/2022          32          2  Sunny\n",
       "5  1/6/2022          31          7   Snow"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.to_csv(\"indore_weather.csv\", index = True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "462d3c09",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_excel(\"goa.xlsx\", sheet_name='Weather 1' ,index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4c78dc14",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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