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Assignment09-PartB-PandasSQL-Answer-Fall2017
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Assignment09-PartB-PandasSQL-Answer-Fall2017.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Part B"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is the version that will work on Ubuntu ans assumes that mysql server and pymysql is installed, using\n",
"- sudo apt-get install mysql-server\n",
"- conda install pymysql"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"import pymysql as myDB\n",
"import pandas as pd"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Establish the connection and create the cursor"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"conn = myDB.connect(host='localhost', user='root', password='root') \n",
"cursor = conn.cursor()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### See what databases exist"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('information_schema',)\n",
"('classwork',)\n",
"('mysql',)\n",
"('performance_schema',)\n",
"('sys',)\n"
]
}
],
"source": [
"sql = ' SHOW DATABASES; '\n",
"cursor.execute(sql)\n",
"for row in cursor:\n",
" print (row)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Delete the MYFLTDATA database, if it exists"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/drk/anaconda3/lib/python3.6/site-packages/pymysql/cursors.py:166: Warning: (1008, \"Can't drop database 'MYFLTDATA'; database doesn't exist\")\n",
" result = self._query(query)\n"
]
},
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sql = ' DROP DATABASE IF EXISTS MYFLTDATA; ' \n",
"cursor.execute(sql)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Now create a database named MYFLTDATA"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"1"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sql = ' CREATE DATABASE MYFLTDATA; ' \n",
"cursor.execute(sql)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Start using the MYFLTDATA database"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sql = ' USE MYFLTDATA; ' \n",
"cursor.execute(sql)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Now close the connection"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"cursor.close()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Read the flights.csv and weather.csv as pandas data frames"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"flights = pd.read_csv('flights.csv')\n",
"weather = pd.read_csv('weather.csv')"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
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"\n",
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" text-align: left;\n",
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" .dataframe tbody tr th {\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>Unnamed: 0</th>\n",
" <th>year</th>\n",
" <th>month</th>\n",
" <th>day</th>\n",
" <th>dep_time</th>\n",
" <th>sched_dep_time</th>\n",
" <th>dep_delay</th>\n",
" <th>arr_time</th>\n",
" <th>sched_arr_time</th>\n",
" <th>arr_delay</th>\n",
" <th>carrier</th>\n",
" <th>flight</th>\n",
" <th>tailnum</th>\n",
" <th>origin</th>\n",
" <th>dest</th>\n",
" <th>air_time</th>\n",
" <th>distance</th>\n",
" <th>hour</th>\n",
" <th>minute</th>\n",
" <th>time_hour</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>517.0</td>\n",
" <td>515</td>\n",
" <td>2.0</td>\n",
" <td>830.0</td>\n",
" <td>819</td>\n",
" <td>11.0</td>\n",
" <td>UA</td>\n",
" <td>1545</td>\n",
" <td>N14228</td>\n",
" <td>EWR</td>\n",
" <td>IAH</td>\n",
" <td>227.0</td>\n",
" <td>1400</td>\n",
" <td>5</td>\n",
" <td>15</td>\n",
" <td>2013-01-01 05:00:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>533.0</td>\n",
" <td>529</td>\n",
" <td>4.0</td>\n",
" <td>850.0</td>\n",
" <td>830</td>\n",
" <td>20.0</td>\n",
" <td>UA</td>\n",
" <td>1714</td>\n",
" <td>N24211</td>\n",
" <td>LGA</td>\n",
" <td>IAH</td>\n",
" <td>227.0</td>\n",
" <td>1416</td>\n",
" <td>5</td>\n",
" <td>29</td>\n",
" <td>2013-01-01 05:00:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>542.0</td>\n",
" <td>540</td>\n",
" <td>2.0</td>\n",
" <td>923.0</td>\n",
" <td>850</td>\n",
" <td>33.0</td>\n",
" <td>AA</td>\n",
" <td>1141</td>\n",
" <td>N619AA</td>\n",
" <td>JFK</td>\n",
" <td>MIA</td>\n",
" <td>160.0</td>\n",
" <td>1089</td>\n",
" <td>5</td>\n",
" <td>40</td>\n",
" <td>2013-01-01 05:00:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>544.0</td>\n",
" <td>545</td>\n",
" <td>-1.0</td>\n",
" <td>1004.0</td>\n",
" <td>1022</td>\n",
" <td>-18.0</td>\n",
" <td>B6</td>\n",
" <td>725</td>\n",
" <td>N804JB</td>\n",
" <td>JFK</td>\n",
" <td>BQN</td>\n",
" <td>183.0</td>\n",
" <td>1576</td>\n",
" <td>5</td>\n",
" <td>45</td>\n",
" <td>2013-01-01 05:00:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>554.0</td>\n",
" <td>600</td>\n",
" <td>-6.0</td>\n",
" <td>812.0</td>\n",
" <td>837</td>\n",
" <td>-25.0</td>\n",
" <td>DL</td>\n",
" <td>461</td>\n",
" <td>N668DN</td>\n",
" <td>LGA</td>\n",
" <td>ATL</td>\n",
" <td>116.0</td>\n",
" <td>762</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>2013-01-01 06:00:00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Unnamed: 0 year month day dep_time sched_dep_time dep_delay \\\n",
"0 1 2013 1 1 517.0 515 2.0 \n",
"1 2 2013 1 1 533.0 529 4.0 \n",
"2 3 2013 1 1 542.0 540 2.0 \n",
"3 4 2013 1 1 544.0 545 -1.0 \n",
"4 5 2013 1 1 554.0 600 -6.0 \n",
"\n",
" arr_time sched_arr_time arr_delay carrier flight tailnum origin dest \\\n",
"0 830.0 819 11.0 UA 1545 N14228 EWR IAH \n",
"1 850.0 830 20.0 UA 1714 N24211 LGA IAH \n",
"2 923.0 850 33.0 AA 1141 N619AA JFK MIA \n",
"3 1004.0 1022 -18.0 B6 725 N804JB JFK BQN \n",
"4 812.0 837 -25.0 DL 461 N668DN LGA ATL \n",
"\n",
" air_time distance hour minute time_hour \n",
"0 227.0 1400 5 15 2013-01-01 05:00:00 \n",
"1 227.0 1416 5 29 2013-01-01 05:00:00 \n",
"2 160.0 1089 5 40 2013-01-01 05:00:00 \n",
"3 183.0 1576 5 45 2013-01-01 05:00:00 \n",
"4 116.0 762 6 0 2013-01-01 06:00:00 "
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights.head()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\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>year</th>\n",
" <th>month</th>\n",
" <th>day</th>\n",
" <th>hour</th>\n",
" <th>origin</th>\n",
" <th>arr_delay</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>EWR</td>\n",
" <td>11.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>LGA</td>\n",
" <td>20.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>JFK</td>\n",
" <td>33.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>JFK</td>\n",
" <td>-18.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" <td>LGA</td>\n",
" <td>-25.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" year month day hour origin arr_delay\n",
"0 2013 1 1 5 EWR 11.0\n",
"1 2013 1 1 5 LGA 20.0\n",
"2 2013 1 1 5 JFK 33.0\n",
"3 2013 1 1 5 JFK -18.0\n",
"4 2013 1 1 6 LGA -25.0"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights = flights[['year', 'month', 'day', 'hour', 'origin', 'arr_delay']]\n",
"flights.head()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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" <th>year</th>\n",
" <th>month</th>\n",
" <th>day</th>\n",
" <th>hour</th>\n",
" <th>temp</th>\n",
" <th>dewp</th>\n",
" <th>humid</th>\n",
" <th>wind_dir</th>\n",
" <th>wind_speed</th>\n",
" <th>wind_gust</th>\n",
" <th>precip</th>\n",
" <th>pressure</th>\n",
" <th>visib</th>\n",
" <th>time_hour</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
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" <td>EWR</td>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
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" <td>0</td>\n",
" <td>37.04</td>\n",
" <td>21.92</td>\n",
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" <td>230.0</td>\n",
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" <td>11.918651</td>\n",
" <td>0.0</td>\n",
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" <td>10.0</td>\n",
" <td>2012-12-31 19:00:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>EWR</td>\n",
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" <td>1</td>\n",
" <td>1</td>\n",
" <td>37.04</td>\n",
" <td>21.92</td>\n",
" <td>53.97</td>\n",
" <td>230.0</td>\n",
" <td>13.80936</td>\n",
" <td>15.891535</td>\n",
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" <td>10.0</td>\n",
" <td>2012-12-31 20:00:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>EWR</td>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>37.94</td>\n",
" <td>21.92</td>\n",
" <td>52.09</td>\n",
" <td>230.0</td>\n",
" <td>12.65858</td>\n",
" <td>14.567241</td>\n",
" <td>0.0</td>\n",
" <td>1012.6</td>\n",
" <td>10.0</td>\n",
" <td>2012-12-31 21:00:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>EWR</td>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>37.94</td>\n",
" <td>23.00</td>\n",
" <td>54.51</td>\n",
" <td>230.0</td>\n",
" <td>13.80936</td>\n",
" <td>15.891535</td>\n",
" <td>0.0</td>\n",
" <td>1012.7</td>\n",
" <td>10.0</td>\n",
" <td>2012-12-31 22:00:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>EWR</td>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>37.94</td>\n",
" <td>24.08</td>\n",
" <td>57.04</td>\n",
" <td>240.0</td>\n",
" <td>14.96014</td>\n",
" <td>17.215830</td>\n",
" <td>0.0</td>\n",
" <td>1012.8</td>\n",
" <td>10.0</td>\n",
" <td>2012-12-31 23:00:00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Unnamed: 0 origin year month day hour temp dewp humid wind_dir \\\n",
"0 1 EWR 2013 1 1 0 37.04 21.92 53.97 230.0 \n",
"1 2 EWR 2013 1 1 1 37.04 21.92 53.97 230.0 \n",
"2 3 EWR 2013 1 1 2 37.94 21.92 52.09 230.0 \n",
"3 4 EWR 2013 1 1 3 37.94 23.00 54.51 230.0 \n",
"4 5 EWR 2013 1 1 4 37.94 24.08 57.04 240.0 \n",
"\n",
" wind_speed wind_gust precip pressure visib time_hour \n",
"0 10.35702 11.918651 0.0 1013.9 10.0 2012-12-31 19:00:00 \n",
"1 13.80936 15.891535 0.0 1013.0 10.0 2012-12-31 20:00:00 \n",
"2 12.65858 14.567241 0.0 1012.6 10.0 2012-12-31 21:00:00 \n",
"3 13.80936 15.891535 0.0 1012.7 10.0 2012-12-31 22:00:00 \n",
"4 14.96014 17.215830 0.0 1012.8 10.0 2012-12-31 23:00:00 "
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weather.head()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>EWR</td>\n",
" <td>37.94</td>\n",
" <td>52.09</td>\n",
" <td>12.65858</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>EWR</td>\n",
" <td>37.94</td>\n",
" <td>54.51</td>\n",
" <td>13.80936</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>EWR</td>\n",
" <td>37.94</td>\n",
" <td>57.04</td>\n",
" <td>14.96014</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" year month day hour origin temp humid wind_speed precip\n",
"0 2013 1 1 0 EWR 37.04 53.97 10.35702 0.0\n",
"1 2013 1 1 1 EWR 37.04 53.97 13.80936 0.0\n",
"2 2013 1 1 2 EWR 37.94 52.09 12.65858 0.0\n",
"3 2013 1 1 3 EWR 37.94 54.51 13.80936 0.0\n",
"4 2013 1 1 4 EWR 37.94 57.04 14.96014 0.0"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weather = weather[['year', 'month', 'day', 'hour', 'origin', 'temp', 'humid', 'wind_speed', 'precip']]\n",
"weather.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Clean the two data frames"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"year 0\n",
"month 0\n",
"day 0\n",
"hour 0\n",
"origin 0\n",
"arr_delay 9430\n",
"dtype: int64"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights.isnull().sum() "
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"year 0\n",
"month 0\n",
"day 0\n",
"hour 0\n",
"origin 0\n",
"temp 1\n",
"humid 1\n",
"wind_speed 3\n",
"precip 0\n",
"dtype: int64"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weather.isnull().sum() "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Delete NaNs"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"year 0\n",
"month 0\n",
"day 0\n",
"hour 0\n",
"origin 0\n",
"arr_delay 0\n",
"dtype: int64"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"flights = flights[pd.notnull(flights['arr_delay'])]\n",
"flights.isnull().sum() "
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"year 0\n",
"month 0\n",
"day 0\n",
"hour 0\n",
"origin 0\n",
"temp 0\n",
"humid 0\n",
"wind_speed 0\n",
"precip 0\n",
"dtype: int64"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weather = weather[pd.notnull(weather['temp'])]\n",
"weather = weather[pd.notnull(weather['humid'])]\n",
"weather = weather[pd.notnull(weather['wind_speed'])]\n",
"weather.isnull().sum() "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Save these data frames as csv"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"flights.to_csv('flightsb.csv', index=False, quoting=1)\n",
"weather.to_csv('weatherb.csv', index=False, quoting=1)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"cursor.close()"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"conn = myDB.connect(host='localhost', user='root', password='root', db='MYFLTDATA', local_infile=True) \n",
"cursor = conn.cursor()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/drk/anaconda3/lib/python3.6/site-packages/pymysql/cursors.py:166: Warning: (1051, \"Unknown table 'MYFLTDATA.flights'\")\n",
" result = self._query(query)\n"
]
},
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sql = '''\n",
"DROP TABLE IF EXISTS flights\n",
"'''\n",
"cursor.execute(sql)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Save flights and weather as SQL tables in the MYFLTDATA database"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"sql = '''\n",
" CREATE TABLE flights (\n",
" year CHAR(4),\n",
" month CHAR(4),\n",
" day CHAR(4),\n",
" hour CHAR(2),\n",
" origin CHAR(3),\n",
" arr_delay DECIMAL(10 , 2 )\n",
" );\n",
" '''"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cursor.execute(sql)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Reference for insert -- http://www.mysqltutorial.org/import-csv-file-mysql-table/"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"sql = '''\n",
" LOAD DATA LOCAL INFILE 'flightsb.csv' \n",
" INTO TABLE flights \n",
" FIELDS TERMINATED BY ',' \n",
" ENCLOSED BY '\"'\n",
" LINES TERMINATED BY '\\n'\n",
" IGNORE 1 ROWS;\n",
" '''"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"327346"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cursor.execute(sql)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"sql = '''\n",
" SELECT * FROM flights LIMIT 5\n",
"'''"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('2013', '1', '1', '5', 'EWR', Decimal('11.00'))\n",
"('2013', '1', '1', '5', 'LGA', Decimal('20.00'))\n",
"('2013', '1', '1', '5', 'JFK', Decimal('33.00'))\n",
"('2013', '1', '1', '5', 'JFK', Decimal('-18.00'))\n",
"('2013', '1', '1', '6', 'LGA', Decimal('-25.00'))\n"
]
}
],
"source": [
"cursor.execute(sql)\n",
"for row in cursor.fetchall():\n",
" print (row)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"sql = '''\n",
" CREATE TABLE weather (\n",
" year CHAR(4),\n",
" month CHAR(4),\n",
" day CHAR(4),\n",
" hour CHAR(2),\n",
" origin CHAR(3),\n",
" temp DECIMAL(5 , 2 ),\n",
" humid DECIMAL(5 , 2 ),\n",
" wind_speed DECIMAL(10 , 5 ),\n",
" precip DECIMAL(5 , 2 )\n",
" );\n",
" '''"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cursor.execute(sql)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"sql = '''\n",
" LOAD DATA LOCAL INFILE 'weatherb.csv' \n",
" INTO TABLE weather \n",
" FIELDS TERMINATED BY ',' \n",
" ENCLOSED BY '\"'\n",
" LINES TERMINATED BY '\\n'\n",
" IGNORE 1 ROWS;\n",
" '''"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"cursor.execute(sql)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"sql = '''\n",
" SELECT * FROM weather LIMIT 5\n",
"'''"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('2013', '1', '1', '0', 'EWR', Decimal('37.04'), Decimal('53.97'), Decimal('10.35702'), Decimal('0.00'))\n",
"('2013', '1', '1', '1', 'EWR', Decimal('37.04'), Decimal('53.97'), Decimal('13.80936'), Decimal('0.00'))\n",
"('2013', '1', '1', '2', 'EWR', Decimal('37.94'), Decimal('52.09'), Decimal('12.65858'), Decimal('0.00'))\n",
"('2013', '1', '1', '3', 'EWR', Decimal('37.94'), Decimal('54.51'), Decimal('13.80936'), Decimal('0.00'))\n",
"('2013', '1', '1', '4', 'EWR', Decimal('37.94'), Decimal('57.04'), Decimal('14.96014'), Decimal('0.00'))\n"
]
}
],
"source": [
"cursor.execute(sql)\n",
"for row in cursor.fetchall():\n",
" print (row)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Now to join on year, month, day, hour and origin\n",
"- This command sequence creates a temporary table\n",
"- The temporary table will be valid as long as the connection exists\n",
"- Depending on your installation and setup, this may or may not work and in any case may take a long time.\n",
"- So the next five cells are a little shaky"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sql = '''\n",
" CREATE TEMPORARY TABLE fltweather AS ( \n",
" SELECT flights.year, flights.month, flights.day, flights.hour, flights.origin,\n",
" weather.temp, weather.humid, weather.wind_speed, weather.precip\n",
" FROM flights\n",
" LEFT JOIN weather on flights.year = weather.year \n",
" AND flights.month = weather.month\n",
" AND flights.day = weather.day\n",
" AND flights.hour = weather.hour\n",
" AND flights.origin = weather.origin\n",
" );\n",
"'''"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"cursor.execute(sql)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sql = '''\n",
" SELECT * FROM fltweather LIMIT 5\n",
"'''"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"cursor.execute(sql)\n",
"for row in cursor.fetchall():\n",
" print (row)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"cursor.close()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Do the join in pandas, if the last step did not work"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"fltweather = pd.merge(flights, weather, how='left', on=['year', 'month', 'day', 'hour', 'origin'])"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>year</th>\n",
" <th>month</th>\n",
" <th>day</th>\n",
" <th>hour</th>\n",
" <th>origin</th>\n",
" <th>arr_delay</th>\n",
" <th>temp</th>\n",
" <th>humid</th>\n",
" <th>wind_speed</th>\n",
" <th>precip</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>EWR</td>\n",
" <td>11.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>LGA</td>\n",
" <td>20.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>JFK</td>\n",
" <td>33.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>JFK</td>\n",
" <td>-18.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" <td>LGA</td>\n",
" <td>-25.0</td>\n",
" <td>39.92</td>\n",
" <td>57.33</td>\n",
" <td>13.80936</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" year month day hour origin arr_delay temp humid wind_speed precip\n",
"0 2013 1 1 5 EWR 11.0 NaN NaN NaN NaN\n",
"1 2013 1 1 5 LGA 20.0 NaN NaN NaN NaN\n",
"2 2013 1 1 5 JFK 33.0 NaN NaN NaN NaN\n",
"3 2013 1 1 5 JFK -18.0 NaN NaN NaN NaN\n",
"4 2013 1 1 6 LGA -25.0 39.92 57.33 13.80936 0.0"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fltweather.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Select all flights that departed from JFK that were delayed in departure by more than 10 hours and store them in a separate table called “mydelay”"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [],
"source": [
"mydelay = fltweather[(fltweather['origin'] == 'JFK') & (fltweather['arr_delay'] > 10)]"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>year</th>\n",
" <th>month</th>\n",
" <th>day</th>\n",
" <th>hour</th>\n",
" <th>origin</th>\n",
" <th>arr_delay</th>\n",
" <th>temp</th>\n",
" <th>humid</th>\n",
" <th>wind_speed</th>\n",
" <th>precip</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" <td>JFK</td>\n",
" <td>33.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" <td>JFK</td>\n",
" <td>14.0</td>\n",
" <td>39.02</td>\n",
" <td>59.37</td>\n",
" <td>12.65858</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>52</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" <td>JFK</td>\n",
" <td>11.0</td>\n",
" <td>39.02</td>\n",
" <td>59.37</td>\n",
" <td>12.65858</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>69</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" <td>JFK</td>\n",
" <td>44.0</td>\n",
" <td>39.02</td>\n",
" <td>59.37</td>\n",
" <td>11.50780</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>112</th>\n",
" <td>2013</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" <td>JFK</td>\n",
" <td>12.0</td>\n",
" <td>39.92</td>\n",
" <td>59.50</td>\n",
" <td>14.96014</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" year month day hour origin arr_delay temp humid wind_speed \\\n",
"2 2013 1 1 5 JFK 33.0 NaN NaN NaN \n",
"26 2013 1 1 6 JFK 14.0 39.02 59.37 12.65858 \n",
"52 2013 1 1 6 JFK 11.0 39.02 59.37 12.65858 \n",
"69 2013 1 1 7 JFK 44.0 39.02 59.37 11.50780 \n",
"112 2013 1 1 8 JFK 12.0 39.92 59.50 14.96014 \n",
"\n",
" precip \n",
"2 NaN \n",
"26 0.0 \n",
"52 0.0 \n",
"69 0.0 \n",
"112 0.0 "
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mydelay.head()"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt \n",
"import seaborn as sns\n",
"%matplotlib inline\n",
"import warnings\n",
"warnings.filterwarnings(action='once')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Get rid of all the NaNs"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {},
"outputs": [],
"source": [
"warnings.filterwarnings('ignore')\n",
"mydelay = mydelay.dropna()"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x7fc2a5d56978>"
]
},
"execution_count": 67,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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IprLJOpZ9zRKCOc3WihM0tXdbc5EJKHlp8dZkNA4sIZjTrN1XiwhcYndHMwEk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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fc2a5df07f0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = plt.axes()\n",
"sns.distplot(mydelay['temp'], ax=ax)\n",
"ax.set_title('Temperature')"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x7fc2a5c28da0>"
]
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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F97bXMnd8luYcSMRLjo+hICORLZWRMdJICUE+4nOOZ1btJSU+hnOnjA52OCIj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\ngg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fc2a5cbbd68>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = plt.axes()\n",
"sns.distplot(mydelay['humid'], ax=ax)\n",
"ax.set_title('Humidity')"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x7fc2a5af43c8>"
]
},
"execution_count": 69,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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EVvZo+2K3163Azb2s9xXgK+cY44i1YV8D5YWZ5PUyzU9GppRohLdfUMryDVVU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\nSUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fc2a5b1cf28>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = plt.axes()\n",
"sns.distplot(mydelay['wind_speed'], ax=ax)\n",
"ax.set_title('Wind Speed')"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x7fc2a5f79be0>"
]
},
"execution_count": 70,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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DfkdLGwBPbu73I/LNzJKUbtC3dgDw1ObmYa7EzGx4JRv0O1vaAXhyczMRMczVmJkNn3SD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\ngg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fc2a59b06d8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = plt.axes()\n",
"sns.distplot(mydelay['precip'], ax=ax)\n",
"ax.set_title('Precipitation')"
]
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>count</th>\n",
" <th>mean</th>\n",
" <th>std</th>\n",
" <th>min</th>\n",
" <th>25%</th>\n",
" <th>50%</th>\n",
" <th>75%</th>\n",
" <th>max</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>temp</th>\n",
" <td>29364.0</td>\n",
" <td>57.460664</td>\n",
" <td>18.431927</td>\n",
" <td>12.02</td>\n",
" <td>42.08000</td>\n",
" <td>57.9200</td>\n",
" <td>73.94000</td>\n",
" <td>98.06000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>humid</th>\n",
" <td>29364.0</td>\n",
" <td>65.799070</td>\n",
" <td>20.148121</td>\n",
" <td>15.21</td>\n",
" <td>49.62000</td>\n",
" <td>67.5400</td>\n",
" <td>83.32000</td>\n",
" <td>100.00000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>wind_speed</th>\n",
" <td>29364.0</td>\n",
" <td>12.519808</td>\n",
" <td>6.007467</td>\n",
" <td>0.00</td>\n",
" <td>8.05546</td>\n",
" <td>11.5078</td>\n",
" <td>16.11092</td>\n",
" <td>42.57886</td>\n",
" </tr>\n",
" <tr>\n",
" <th>precip</th>\n",
" <td>29364.0</td>\n",
" <td>0.005089</td>\n",
" <td>0.024952</td>\n",
" <td>0.00</td>\n",
" <td>0.00000</td>\n",
" <td>0.0000</td>\n",
" <td>0.00000</td>\n",
" <td>0.38000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" count mean std min 25% 50% 75% \\\n",
"temp 29364.0 57.460664 18.431927 12.02 42.08000 57.9200 73.94000 \n",
"humid 29364.0 65.799070 20.148121 15.21 49.62000 67.5400 83.32000 \n",
"wind_speed 29364.0 12.519808 6.007467 0.00 8.05546 11.5078 16.11092 \n",
"precip 29364.0 0.005089 0.024952 0.00 0.00000 0.0000 0.00000 \n",
"\n",
" max \n",
"temp 98.06000 \n",
"humid 100.00000 \n",
"wind_speed 42.57886 \n",
"precip 0.38000 "
]
},
"execution_count": 71,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mydelayweather = mydelay[['temp', 'humid', 'wind_speed', 'precip']]\n",
"mydelayweather.describe().transpose()"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.PairGrid at 0x7fc2a5c84550>"
]
},
"execution_count": 74,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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ODo5uilSNFkKyhqp/HMLRUxGLUoTtNuvqcCqkoGDxJty5phZTR/aB/5bhjBt8+6pPMNK/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rZEFZxqiWF2aQWu/dX7SSkRA5/egOHP6xXhJ5qi7KF/rcFxjk5ajzaEmAmHlW99JqpgbcUxU1W/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AtFOhRgTlBBY0sMQb9i6qM1leWQJYL/mv8dQ7YjScj2GdeAkqoNHLfnhBB0wrTlBBV8lrqp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\nSDyJ21Pa6Nuqa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oRXHV5znNfxdhaS7VzU0YV2XmLXutREPc+1z32EA8vMmqF0OCYv/U9j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nXvD/o+aUXeosFLYA+GSF9k4Tkf90Hko8IyInhy1YPHX/2FmkbBYnfXjE4uVEEdniPOj44jQOHWkt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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fc2a58c9860>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.pairplot(mydelayweather)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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