{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Project 2: Holiday weather\n", "\n", "by Rob Griffiths, 11 September 2015, updated 11 April 2017, 18 October and 20 December 2017\n", "\n", "This is the project notebook for the second part of The Open University's _Learn to code for Data Analysis_ course.\n", "\n", "There is nothing I like better than taking a holiday. In the winter I like to have a two week break in a country where I can be guaranteed sunny dry days. In the summer I like to have two weeks off relaxing in my garden in London. However I'm often disappointed because I pick a fortnight when the weather is dull and it rains. So in this project I am going to use the historic weather data from the Weather Underground for London to try to predict two good weather weeks to take off as holiday next summer. Of course the weather in the summer of 2016 may be very different to 2014 but it should give me some indication of when would be a good time to take a summer break.\n", "\n", "## Getting the data\n", "\n", "Weather Underground keeps historical weather data collected in many airports around the world. Right-click on the following URL and choose 'Open Link in New Window' (or similar, depending on your browser):\n", "\n", "http://www.wunderground.com/history\n", "\n", "When the new page opens start typing 'LHR' in the 'Location' input box and when the pop up menu comes up with the option 'LHR, United Kingdom' select it and then click on 'Submit'. \n", "\n", "When the next page opens with London Heathrow data, click on the 'Custom' tab and select the time period From: 1 January 2014 to: 31 December 2014 and then click on 'Get History'. The data for that year should then be displayed further down the page. \n", "\n", "You can copy each month's data directly from the browser to a text editor like Notepad or TextEdit, to obtain a single file with as many months as you wish.\n", "\n", "Weather Underground has changed in the past the way it provides data and may do so again in the future. \n", "I have therefore collated the whole 2014 data in the provided 'London_2014.csv' file. \n", "\n", "Now load the CSV file into a dataframe making sure that any extra spaces are skipped:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import warnings\n", "warnings.simplefilter('ignore', FutureWarning)\n", "\n", "from pandas import *\n", "london = read_csv('London_2014.csv', skipinitialspace=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Cleaning the data\n", "First we need to clean up the data. I'm not going to make use of `'WindDirDegrees'` in my analysis, but you might in yours so we'll rename `'WindDirDegrees< br />'` to `'WindDirDegrees'`. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "london = london.rename(columns={'WindDirDegrees
' : 'WindDirDegrees'})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "remove the `< br />` html line breaks from the values in the `'WindDirDegrees'` column. " ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "london['WindDirDegrees'] = london['WindDirDegrees'].str.rstrip('
')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "and change the values in the `'WindDirDegrees'` column to `float64`:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "london['WindDirDegrees'] = london['WindDirDegrees'].astype('float64') " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We definitely need to change the values in the `'GMT'` column into values of the `datetime64` date type." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": true }, "outputs": [], "source": [ "london['GMT'] = to_datetime(london['GMT'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We also need to change the index from the default to the `datetime64` values in the `'GMT'` column so that it is easier to pull out rows between particular dates and display more meaningful graphs: " ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": true }, "outputs": [], "source": [ "london.index = london['GMT']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Finding a summer break\n", "\n", "According to meteorologists, summer extends for the whole months of June, July, and August in the northern hemisphere and the whole months of December, January, and February in the southern hemisphere. So as I'm in the northern hemisphere I'm going to create a dataframe that holds just those months using the `datetime` index, like this:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": true }, "outputs": [], "source": [ "summer = london.loc[datetime(2014,6,1) : datetime(2014,8,31)]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "I now look for the days with warm temperatures." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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GMTMax TemperatureCMean TemperatureCMin TemperatureCDew PointCMeanDew PointCMin DewpointCMax HumidityMean HumidityMin Humidity...Max VisibilityKmMean VisibilityKmMin VisibilitykMMax Wind SpeedKm/hMean Wind SpeedKm/hMax Gust SpeedKm/hPrecipitationmmCloudCoverEventsWindDirDegrees
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" ], "text/plain": [ "Empty DataFrame\n", "Columns: [GMT, Max TemperatureC, Mean TemperatureC, Min TemperatureC, Dew PointC, MeanDew PointC, Min DewpointC, Max Humidity, Mean Humidity, Min Humidity, Max Sea Level PressurehPa, Mean Sea Level PressurehPa, Min Sea Level PressurehPa, Max VisibilityKm, Mean VisibilityKm, Min VisibilitykM, Max Wind SpeedKm/h, Mean Wind SpeedKm/h, Max Gust SpeedKm/h, Precipitationmm, CloudCover, Events, WindDirDegrees]\n", "Index: []\n", "\n", "[0 rows x 23 columns]" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "summer[summer['Mean TemperatureC'] >= 25]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Summer 2014 was rather cool in London: there are no days with temperatures of 25 Celsius or higher. Best to see a graph of the temperature and look for the warmest period.\n", "\n", "So next we tell Jupyter to display any graph created inside this notebook:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": true }, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "Now let's plot the `'Mean TemperatureC'` for the summer:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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vd9aiUUx7l4p+wj7SZ4JOrdhSwaU/nECzRgmdOn+Rc49JD8YKBVNJtBcpMCbF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\nAQAA+EAwBQAA4APBFAAAgA//D/DDSrCWMYpHAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "summer['Mean TemperatureC'].plot(grid=True, figsize=(10,5))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Well looking at the graph the second half of July looks good for mean temperatures over 20 degrees C so let's also put precipitation on the graph too:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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ei/3Hydw+fvArfJujVS1TdLWJqT4qvc/DbHcNm1Ua3vrvARaO1V91u7heg0aG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+AAAN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\nwzBF8P8B/eXWazRbgbEAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "summer[['Mean TemperatureC', 'Precipitationmm']].plot(grid=True, figsize=(10,5))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The second half of July is still looking good, with just a couple of peaks showing heavy rain. Let's have a closer look by just plotting mean temperature and precipitation for July. " ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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ir9s5eSbTITGVlJIpERcyfUUMbobBmJ6NLvp8LX8fXruuNQse6UOXxtV5489o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\nluSGwA7uC0lilslURelUQVcyJfFYcmcoNnf2W6K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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "july = summer.loc[datetime(2014,7,1) : datetime(2014,7,31)]\n", "july[['Mean TemperatureC', 'Precipitationmm']].plot(grid=True, figsize=(10,5))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Yes, second half of July looks pretty good, just two days that have significant rain, the 25th and the 28th and just one day when the mean temperature drops below 20 degrees, also the 28th." ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## Conclusions\n", "\n", "The graphs have shown the volatility of a British summer, but a couple of weeks were found when the weather wasn't too bad in 2014. Of course this is no guarantee that the weather pattern will repeat itself in future years. To make a sensible prediction we would need to analyse the summers for many more years. By the time you have finished this course you should be able to do that." ] } ], "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": 1 }