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susanli2016/Toronto-Weather.ipynb

Created December 9, 2016 07:03
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Toronto-Weather.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## I downloaded the data for October 2016, and let's look back what the temperature was like."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\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>Time</th>\n",
" <th>Data Quality</th>\n",
" <th>Temp (°C)</th>\n",
" <th>Temp Flag</th>\n",
" <th>Dew Point Temp (°C)</th>\n",
" <th>Dew Point Temp Flag</th>\n",
" <th>Rel Hum (%)</th>\n",
" <th>...</th>\n",
" <th>Wind Spd Flag</th>\n",
" <th>Visibility (km)</th>\n",
" <th>Visibility Flag</th>\n",
" <th>Stn Press (kPa)</th>\n",
" <th>Stn Press Flag</th>\n",
" <th>Hmdx</th>\n",
" <th>Hmdx Flag</th>\n",
" <th>Wind Chill</th>\n",
" <th>Wind Chill Flag</th>\n",
" <th>Weather</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date/Time</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2016-10-01 0:00</th>\n",
" <td>2016</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>0:00</td>\n",
" <td></td>\n",
" <td>14.1</td>\n",
" <td>NaN</td>\n",
" <td>11.3</td>\n",
" <td>NaN</td>\n",
" <td>83.0</td>\n",
" <td>...</td>\n",
" <td>M</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>100.99</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016-10-01 1:00</th>\n",
" <td>2016</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>1:00</td>\n",
" <td></td>\n",
" <td>14.2</td>\n",
" <td>NaN</td>\n",
" <td>10.9</td>\n",
" <td>NaN</td>\n",
" <td>81.0</td>\n",
" <td>...</td>\n",
" <td>M</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>100.98</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016-10-01 2:00</th>\n",
" <td>2016</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>2:00</td>\n",
" <td></td>\n",
" <td>13.8</td>\n",
" <td>NaN</td>\n",
" <td>10.7</td>\n",
" <td>NaN</td>\n",
" <td>82.0</td>\n",
" <td>...</td>\n",
" <td>M</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>100.92</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016-10-01 3:00</th>\n",
" <td>2016</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>3:00</td>\n",
" <td></td>\n",
" <td>13.6</td>\n",
" <td>NaN</td>\n",
" <td>10.8</td>\n",
" <td>NaN</td>\n",
" <td>83.0</td>\n",
" <td>...</td>\n",
" <td>M</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>100.86</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016-10-01 4:00</th>\n",
" <td>2016</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>4:00</td>\n",
" <td></td>\n",
" <td>13.8</td>\n",
" <td>NaN</td>\n",
" <td>11.1</td>\n",
" <td>NaN</td>\n",
" <td>84.0</td>\n",
" <td>...</td>\n",
" <td>M</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>100.84</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 24 columns</p>\n",
"</div>"
],
"text/plain": [
" Year Month Day Time Data Quality Temp (°C) Temp Flag \\\n",
"Date/Time \n",
"2016-10-01 0:00 2016 10 1 0:00 14.1 NaN \n",
"2016-10-01 1:00 2016 10 1 1:00 14.2 NaN \n",
"2016-10-01 2:00 2016 10 1 2:00 13.8 NaN \n",
"2016-10-01 3:00 2016 10 1 3:00 13.6 NaN \n",
"2016-10-01 4:00 2016 10 1 4:00 13.8 NaN \n",
"\n",
" Dew Point Temp (°C) Dew Point Temp Flag Rel Hum (%) \\\n",
"Date/Time \n",
"2016-10-01 0:00 11.3 NaN 83.0 \n",
"2016-10-01 1:00 10.9 NaN 81.0 \n",
"2016-10-01 2:00 10.7 NaN 82.0 \n",
"2016-10-01 3:00 10.8 NaN 83.0 \n",
"2016-10-01 4:00 11.1 NaN 84.0 \n",
"\n",
" ... Wind Spd Flag Visibility (km) Visibility Flag \\\n",
"Date/Time ... \n",
"2016-10-01 0:00 ... M NaN NaN \n",
"2016-10-01 1:00 ... M NaN NaN \n",
"2016-10-01 2:00 ... M NaN NaN \n",
"2016-10-01 3:00 ... M NaN NaN \n",
"2016-10-01 4:00 ... M NaN NaN \n",
"\n",
" Stn Press (kPa) Stn Press Flag Hmdx Hmdx Flag Wind Chill \\\n",
"Date/Time \n",
"2016-10-01 0:00 100.99 NaN NaN NaN NaN \n",
"2016-10-01 1:00 100.98 NaN NaN NaN NaN \n",
"2016-10-01 2:00 100.92 NaN NaN NaN NaN \n",
"2016-10-01 3:00 100.86 NaN NaN NaN NaN \n",
"2016-10-01 4:00 100.84 NaN NaN NaN NaN \n",
"\n",
" Wind Chill Flag Weather \n",
"Date/Time \n",
"2016-10-01 0:00 NaN NaN \n",
"2016-10-01 1:00 NaN NaN \n",
"2016-10-01 2:00 NaN NaN \n",
"2016-10-01 3:00 NaN NaN \n",
"2016-10-01 4:00 NaN NaN \n",
"\n",
"[5 rows x 24 columns]"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weather_oct2016=pd.read_csv(\"Toronto-Weather-Oct2016.csv\", skiprows=16, index_col=\"Date/Time\", encoding=\"latin1\")\n",
"weather_oct2016.head()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 744 entries, 2016-10-01 0:00 to 2016-10-31 23:00\n",
"Data columns (total 24 columns):\n",
"Year 744 non-null int64\n",
"Month 744 non-null int64\n",
"Day 744 non-null int64\n",
"Time 744 non-null object\n",
"Data Quality 742 non-null object\n",
"Temp (°C) 742 non-null float64\n",
"Temp Flag 0 non-null float64\n",
"Dew Point Temp (°C) 742 non-null float64\n",
"Dew Point Temp Flag 0 non-null float64\n",
"Rel Hum (%) 742 non-null float64\n",
"Rel Hum Flag 0 non-null float64\n",
"Wind Dir (10s deg) 0 non-null float64\n",
"Wind Dir Flag 742 non-null object\n",
"Wind Spd (km/h) 0 non-null float64\n",
"Wind Spd Flag 742 non-null object\n",
"Visibility (km) 0 non-null float64\n",
"Visibility Flag 0 non-null float64\n",
"Stn Press (kPa) 742 non-null float64\n",
"Stn Press Flag 0 non-null float64\n",
"Hmdx 21 non-null float64\n",
"Hmdx Flag 0 non-null float64\n",
"Wind Chill 0 non-null float64\n",
"Wind Chill Flag 0 non-null float64\n",
"Weather 0 non-null float64\n",
"dtypes: float64(17), int64(3), object(4)\n",
"memory usage: 145.3+ KB\n"
]
}
],
"source": [
"weather_oct2016.info()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x251f06b3400>"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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moZBsk61gKyhwbpwtLTIX3QknJH/f4uLYFWjr1sm41Tx3W7dK6BA5F1G8+xO5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MtfGGbedhtw7738XjxMwHbzzawWdNPTTwNPPcVW3gkT2KaW6Mxa8Y4CNnvMRWyzEEmkgA3g69mY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\nP08C1gJfb1Jvy3iLiK2BG4Eng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RMlbAa8muEl2GpnER2Ohm0bgbolSZJGTaQ0EsdCkiRJ\n6nURcRRwTkpp9/FuiyRJUi9xBJskSZKGPAJ8aLwbIUmS1GscwSZJkiRJkiR1wRFskiRJkiRJUhdM\nsEmSJEmSJEldMMEmSZIkSZIkdcEEmyRJkiRJktQFE2ySJEmSJElSF0ywSZIkSZIkSV0wwSZJkiRJ\nkiR1wQSbJEmSJEmS1AUTbJIkSZIkSVIX/h9/TqtkjZGebwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x251f06c0128>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"weather_oct2016[u\"Temp (\\xb0C)\"].plot(figsize=(15,5))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Yeah, we had warmer than normal conditions, Oct 18 reached almost 25 degrees. We did not feel anything like fall on that day."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Now let's look at the temperature for the whole year in 2015. I downloaded it one month at a time, then combine the 12 months together, then plot it."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import os\n",
"import glob\n",
"\n",
"path =r'C:/users/susan/desktop/Extracted' \n",
"allFiles = glob.glob(path + \"/*.csv\")\n",
"weather_2015 = pd.DataFrame()\n",
"list_ = []\n",
"for file_ in allFiles:\n",
" df = pd.read_csv(file_,skiprows=16, encoding=\"latin1\")\n",
" list_.append(df)\n",
"weather_2015 = pd.concat(list_)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Date/Time</th>\n",
" <th>Year</th>\n",
" <th>Month</th>\n",
" <th>Day</th>\n",
" <th>Time</th>\n",
" <th>Data Quality</th>\n",
" <th>Temp (°C)</th>\n",
" <th>Temp Flag</th>\n",
" <th>Dew Point Temp (°C)</th>\n",
" <th>Dew Point Temp Flag</th>\n",
" <th>...</th>\n",
" <th>Wind Spd Flag</th>\n",
" <th>Visibility (km)</th>\n",
" <th>Visibility Flag</th>\n",
" <th>Stn Press (kPa)</th>\n",
" <th>Stn Press Flag</th>\n",
" <th>Hmdx</th>\n",
" <th>Hmdx Flag</th>\n",
" <th>Wind Chill</th>\n",
" <th>Wind Chill Flag</th>\n",
" <th>Weather</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2015-04-01 0:00</td>\n",
" <td>2015</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>0:00</td>\n",
" <td></td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>-13.3</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>M</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>100.13</td>\n",
" <td>NaN</td>\n",
" <td>NaN</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>2015-04-01 1:00</td>\n",
" <td>2015</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>1:00</td>\n",
" <td></td>\n",
" <td>-0.3</td>\n",
" <td>NaN</td>\n",
" <td>-13.3</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>M</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>100.16</td>\n",
" <td>NaN</td>\n",
" <td>NaN</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>2015-04-01 2:00</td>\n",
" <td>2015</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>2:00</td>\n",
" <td></td>\n",
" <td>-0.1</td>\n",
" <td>NaN</td>\n",
" <td>-13.3</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>M</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>100.19</td>\n",
" <td>NaN</td>\n",
" <td>NaN</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>2015-04-01 3:00</td>\n",
" <td>2015</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>3:00</td>\n",
" <td></td>\n",
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" <td>NaN</td>\n",
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" <td>M</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>100.24</td>\n",
" <td>NaN</td>\n",
" <td>NaN</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>2015-04-01 4:00</td>\n",
" <td>2015</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>4:00</td>\n",
" <td></td>\n",
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" <td>-10.2</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>M</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>100.33</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 25 columns</p>\n",
"</div>"
],
"text/plain": [
" Date/Time Year Month Day Time Data Quality Temp (°C) Temp Flag \\\n",
"0 2015-04-01 0:00 2015 4 1 0:00 0.0 NaN \n",
"1 2015-04-01 1:00 2015 4 1 1:00 -0.3 NaN \n",
"2 2015-04-01 2:00 2015 4 1 2:00 -0.1 NaN \n",
"3 2015-04-01 3:00 2015 4 1 3:00 -0.7 NaN \n",
"4 2015-04-01 4:00 2015 4 1 4:00 -1.2 NaN \n",
"\n",
" Dew Point Temp (°C) Dew Point Temp Flag ... Wind Spd Flag \\\n",
"0 -13.3 NaN ... M \n",
"1 -13.3 NaN ... M \n",
"2 -13.3 NaN ... M \n",
"3 -11.4 NaN ... M \n",
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"\n",
" Visibility (km) Visibility Flag Stn Press (kPa) Stn Press Flag Hmdx \\\n",
"0 NaN NaN 100.13 NaN NaN \n",
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"2 NaN NaN 100.19 NaN NaN \n",
"3 NaN NaN 100.24 NaN NaN \n",
"4 NaN NaN 100.33 NaN NaN \n",
"\n",
" Hmdx Flag Wind Chill Wind Chill Flag Weather \n",
"0 NaN NaN NaN NaN \n",
"1 NaN NaN NaN NaN \n",
"2 NaN NaN NaN NaN \n",
"3 NaN NaN NaN NaN \n",
"4 NaN NaN NaN NaN \n",
"\n",
"[5 rows x 25 columns]"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weather_2015.head()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"weather_2015 = weather_2015.sort_values(by = \"Date/Time\")"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
},
"outputs": [
{
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" Date/Time Year Month Day Time Data Quality Temp (°C) \\\n",
"0 2015-01-01 0:00 2015 1 1 0:00 -6.7 \n",
"10 2015-01-01 10:00 2015 1 1 10:00 -4.9 \n",
"11 2015-01-01 11:00 2015 1 1 11:00 -4.2 \n",
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"13 2015-01-01 13:00 2015 1 1 13:00 -3.4 \n",
"\n",
" Temp Flag Dew Point Temp (°C) Dew Point Temp Flag ... \\\n",
"0 NaN -15.5 NaN ... \n",
"10 NaN -11.8 NaN ... \n",
"11 NaN -11.2 NaN ... \n",
"12 NaN -11.2 NaN ... \n",
"13 NaN -11.0 NaN ... \n",
"\n",
" Wind Spd Flag Visibility (km) Visibility Flag Stn Press (kPa) \\\n",
"0 M NaN NaN 100.18 \n",
"10 M NaN NaN 99.84 \n",
"11 M NaN NaN 99.73 \n",
"12 M NaN NaN 99.63 \n",
"13 M NaN NaN 99.54 \n",
"\n",
" Stn Press Flag Hmdx Hmdx Flag Wind Chill Wind Chill Flag Weather \n",
"0 NaN NaN NaN NaN NaN NaN \n",
"10 NaN NaN NaN NaN NaN NaN \n",
"11 NaN NaN NaN NaN NaN NaN \n",
"12 NaN NaN NaN NaN NaN NaN \n",
"13 NaN NaN NaN NaN NaN NaN \n",
"\n",
"[5 rows x 25 columns]"
]
},
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"metadata": {},
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"source": [
"weather_2015.head()"
]
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{
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"metadata": {
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{
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" Date/Time Year Month Day Time Data Quality Temp (°C) \\\n",
"725 2015-12-31 5:00 2015 12 31 5:00 1.6 \n",
"726 2015-12-31 6:00 2015 12 31 6:00 1.7 \n",
"727 2015-12-31 7:00 2015 12 31 7:00 1.6 \n",
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"729 2015-12-31 9:00 2015 12 31 9:00 1.8 \n",
"\n",
" Temp Flag Dew Point Temp (°C) Dew Point Temp Flag ... \\\n",
"725 NaN -0.6 NaN ... \n",
"726 NaN -0.7 NaN ... \n",
"727 NaN -0.8 NaN ... \n",
"728 NaN -0.9 NaN ... \n",
"729 NaN -3.1 NaN ... \n",
"\n",
" Wind Spd Flag Visibility (km) Visibility Flag Stn Press (kPa) \\\n",
"725 M NaN NaN 100.50 \n",
"726 M NaN NaN 100.54 \n",
"727 M NaN NaN 100.58 \n",
"728 M NaN NaN 100.57 \n",
"729 M NaN NaN 100.58 \n",
"\n",
" Stn Press Flag Hmdx Hmdx Flag Wind Chill Wind Chill Flag Weather \n",
"725 NaN NaN NaN NaN NaN NaN \n",
"726 NaN NaN NaN NaN NaN NaN \n",
"727 NaN NaN NaN NaN NaN NaN \n",
"728 NaN NaN NaN NaN NaN NaN \n",
"729 NaN NaN NaN NaN NaN NaN \n",
"\n",
"[5 rows x 25 columns]"
]
},
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"metadata": {},
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}
],
"source": [
"weather_2015.tail()"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"weather_2015=weather_2015.set_index(\"Date/Time\")"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
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},
"outputs": [
{
"data": {
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]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
},
{
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MUKdnCdR82w4JADpVhaO1YhbROirYpCuepgOWM88st4+6yQX8K6+YKjYgfex1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\nt7XFFuZWnlfZgM01BlvRSQ6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Bm65gq3PSICIa3UZLoevPAbwVwPZ5K4aYNm0aVpVvcK+a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RMiqqIaZXkKbGmMv3Kp1++EYRiGyRe1yAGFiOb54GxKn5EEW4VPW3J/lTQTWb7HqJNnqo3Uty+w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\nnvXcZBMhIB51lPQkbGwUn3/HH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soqcn2XXeR6Hh5svtSCxyvDMAzDMAzDMNkwZgzw3HPR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\ni2iapCBNSv4si7QZvm7hwmLvf8AB2c9XXcG2+ur+1iy7i2hUN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"text/plain": [
"<matplotlib.figure.Figure at 0x251f1e92ac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"weather_2015[u\"Temp (\\xb0C)\"].plot(figsize=(15,6))"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"## Here it is! The temperature every hour for 2015 in Toronto."
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python [default]",
"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": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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