{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Earth temperature over time" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Is global temperature rising? How much? This is a question of burning importance in today's world!\n", "\n", "Data about global temperatures are available from several sources: NASA, the National Climatic Data Center (NCDC) and the University of East Anglia in the UK. Check out the [University Corporation for Atmospheric Research](https://www2.ucar.edu/climate/faq/how-much-has-global-temperature-risen-last-100-years) (UCAR) for an in-depth discussion.\n", "\n", "The [NASA Goddard Space Flight Center](https://svs.gsfc.nasa.gov/cgi-bin/details.cgi?aid=3901) is one of our sources of global climate data. They produced this video showing a color map of the changing global surface **temperature anomalies** from 1880 to 2015.\n", "\n", "The term [global temperature anomaly](https://www.ncdc.noaa.gov/monitoring-references/faq/anomalies.php) means the difference in temperature with respect to a reference value or a long-term average. It is a very useful way of looking at the problem and in many ways better than absolute temperature. For example, a winter month may be colder than average in Washington DC, and also in Miami, but the absolute temperatures will be different in both places." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "image/jpeg": 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aNLNh5qu8R4jzXzz0i9K/HTqpfTzZuYPDdNNoZ9oMmwVqrtO0h+ou/oS8U1tM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\nTPzb/nCfR+64RxmQuxfqYvE3kufj2QGQ5ZO78bmBLzbsDbd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"text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from IPython.display import YouTubeVideo\n", "YouTubeVideo('gGOzHVUQCw0')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "How would we go about understanding the _trends_ from the data on global temperature?\n", "\n", "The first step in analyzing unknown data is to generate some simple plots using **matplotlib**. We are going to look at the temperature-anomaly history, contained in a file, and make our first plot to explore this data. \n", "\n", "We are going to plot the data and then we'll fit a line to it to find a trend.\n", "\n", "Let's get started!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 1: Read a data file." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We took the data from the [NOAA](https://www.ncdc.noaa.gov/cag/) (National Oceanic and Atmospheric Administration) webpage. Feel free to play around with the webpage and analyze data on your own, but for now, let's make sure we're working with the same dataset.\n", "\n", "We have some sample data in the folder called `data` on the tutorial repository: [Caminos](http://go.gwu.edu/caminos). \n", "The file contains the year on the first column, and averages of land temperature anomaly listed sequentially on the second column, from 1880 to 2016. We will read the file, then make an initial plot to see what it looks like.\n", "\n", "Like in Lesson 2, we're assuming that you have all the files from this tutorial, or are working on the lesson after launching Binder. Executing the following cell will save the data in two arrays, one for each column.\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import numpy" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "year, temp_anomaly = numpy.loadtxt(fname='data/land_global_temperature_anomaly-1880-2016.csv', delimiter=',', \n", " skiprows=5, unpack=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Exercise** Inspect the data by printing `year` and `temp_anomaly`" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 2: Plot the data." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's first load our plotting library: the `pyplot` module of Matplotlib. To get the plots inside the notebook (rather than as popups), we use a special \"magic\" command, `%matplotlib inline`:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from matplotlib import pyplot\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can add a semicolon at the end of the plotting command to avoid that stuff that appeared on top of the figure, that `Out[x]: [< ...>]` ugliness. Try it." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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uSvposUVQ+Xo9plvonS/cBMCPz0ylvV4ZjZHNa7a3BYrOKQy6VotYOmu7xyyL\nYMK0ZiKm9RFLZfF7nCileNHmJu7d3Uajf6ZbyOJz797PR1+/x/4+6DHaVcZSWUaiKSkvsQIQIRBW\nHVMWgTHB3P/SLWRyeT7304t8/9QA9+xuo77WxZ+8fg9eVw1/9Za9/M49O+yslia/m9FpFoHWmn9/\n+gqf/Ml5PvmT81wseGMvx/Bkym6nODFL8LnbdAvdvrmRXe3BojjBuUHjXttbi3P0q501lM3lSWby\nBL0uvC6HHSOYbhFEUzl8bsPV86l33MLf/9ItFa/rqnEU1R+y6g2979+OoDXsXldX7lRhiZBQvbDq\n6J9I4nE67LfULS0BXrm7nX/86UXyGl5j+rNfuaede/6kzc7CsWjwubkyGi/ad/DCKH/0jZP296f7\nI3xylglweDLF+oZa4unsrK6h7nHjfp2NPu7a2crnfnrRbvj+/NAkSsHWlmKLIFjlYLHVp9jvqcHv\nnnI7zYgRpLIEPMZ6genPbi5YgeP/Oj/CR163u6JbSVgaxCIQVh294QQdoVr7DR/gfXdtJa+NyfMl\nO5rt/aUmsqaAe0YF0odP9FPrquH4n97La17QzjEz+FyJkWialoCbUK1rVtdQ91iCWlcNTX43L9/Z\nQjavefLCKADPD0XZ2Oij1l28WMvvcRJNZstWCZ0vVuVRv8eJz1NDwqxAOmFbBFNNaxbTO2BHW5D2\nOi//8M5bec+LNy9+4MKiqYoQKKVepZQ6q5Q6r5T6UInPPUqpB8zPn1ZKdVXjvoJQir7wzGqW+zpD\n3Levg3e8aBMeZ02ZMw0afG7G42l7gs3lNd87NcArdrVS53Vxc2cDPeMJRmZJMR2eTNES9FDvc8/J\nIuhsNMTr5o0NeF0ODlpCMDjJ9tbAjHP8HifZClVC54tlAfg9TsMiSGdJZHKkzdRbyyKIphYnBHs7\nQzz1h3eLJbCCWLQQKKVqgE8CrwZ2A29XSu2edth7gXGt9TbgE8BfLPa+glCOvnCiZCP0v33bzXzo\n1btmPb/R7yaX1/Yb8M8ujTESTdsupb2dRvbO8Z7yVkEurxmLpWgJeAjVuuyAazm6x+J0NvgAcDsd\n3NbVyMELo2RyeS6NxNg+rYYPULLb11w5eGGUB4/2Fu2z6v/43TX43DXE07kiASvKGnKLV3k1UQ2L\n4HbgvNb6otY6DXwZuG/aMfcBXzC3vwbcrQrtdmFNkMnl+fh3zzAUKV9Ppxr3GJpMFeXbzxcrtmCt\nLn7kRD+B0eJdAAAgAElEQVRel4OX72oBjAqbDgVHuyfKXmMsliavoSVopFhWsgi01vSMJ+hs9Nn7\n7tjazNnBSY5cGSeT02UtAmBBmUOf+OE5fv9rx4tWPMcLLQIzNbVICOysoZy0lVxlVEMI1gPdBd/3\nmPtKHqO1zgITQFMV7i1cRzx7NcynHr3Awyf6r9k9BiaSaM2iGp3YQhBLkctrvnPScAtZmTI+t5Md\nbcGKcQJrDYEtBBViBOF4hmgqy4aGKfG6wyx+968HrwDMqOoJlGzyUkj3WJw/+9Ypu3mMRT6vOd0X\nIZ3N8+CxKavAuk7A45yyCAosmUgig9aaWHoqWCysDqohBKXe7KdHr+ZyDEqp+5VSh5VSh4eHZy8U\nJlxfWBPn5ZHq9tktpHAx2UKZEoIMhy6PMRJN2W4hi32dIY71hMsGaq01BIYQuJmIZ8oeW5gxZLGn\no46g18l3Tw2UzBiC2YXgn/7rEv/8xOUZgnV1LE40lUUpeODQ1DuclYHkc9fYMQLLYmgOeIgkM2YL\nS8QiWGVUQwh6gM6C7zcAfeWOUUo5gXpgbPqFtNaf1Vrv11rvb2lpqcLQhJXEUdOnfmlaamYlzg1O\n8pEHT/LFg5ftfROJDB/48rMly0tb1SyrIwSpKbfQztaiY/Z2hgjHM1wdK/2zWBZBsxkjSOfyZev7\nd48Z4mXFCACcNQ5euLmJXF6zoaF2RsYQGGmeUDpGkM9rvnPSsLyOThMCq9LqW27dwKm+iN2i03Ix\nBcysoXgqZ1syGxtriSQyRQFlYfVQDSE4BGxXSm1WSrmBtwEPTTvmIeDd5vabgR/rauW8CdcN1pvp\npZHZF2NprXn/l57h3k88zhcPXuHfnrpSdJ0Hj/bxozMzm84UripeKJYQjETTfOfkAHftaJ0x8Vnl\nHqZPshZWRlFzwHANQfkyE1MWQfGYLffQjtaZbiGobBE8c3WcQbP71/Ge4ljGyb4JnA7F771yJ26n\ng68cNqyCwkneZ1oE1pg3NvqYSGSL3EfC6mHRQmD6/N8PfA94DviK1vqUUuqjSqnXm4f9E9CklDoP\n/A4wI8VUWN2MRFP0jCeo8zrpHU/YJY3L8fjzI3z7eD/vuXMzr3lBO+MFk+i4GcQ91TszWHu0O1wy\n534++NxOvC4HPzg9yPBkitfcNLOg2o62AF6Xg2NlAsbDkyn87hr8Hif1tYawlBWCsTghn6uomxfA\nHdsMIdjWNtMtBIXB4plC8PCJftxOBy/Z3syxnpkWwfa2IK1BL6++sZ1vPttrl3wAqHUZWUPJTJ6x\nWAq300Frndd2DRXeW1gdVGUdgdb6Ea31Dq31Vq31/zb3fURr/ZC5ndRav0VrvU1rfbvW+mI17itc\nP1iplq+9aR15TVmXisVnHr1Ae52XD716Fxsb/YQL8vqtcsiWi8Mil9c8dXHUfpNeDI0+N0e7w3ic\nDu7e1Trjc2eNgxesr58xyVpYawiAKYugTAppz3iiyC1ksbMtyAfu3s5bbu0scZZRxRNmWgT5vOY7\nJwZ46fYW7tzWzJXROOPmAjmtNad6J7ixwyjrcPcNbUSSWS4MR4mlc/jdNTgcCr8ZGO+bSBKqdVFf\n6yKdzdsL7fwSLF5VyMpiYVGcH4ryxk89MWvjlaPdEzgUvO6mDqBywPhYd5iDF0d574s343Y6aPC5\nyOS0/TZqFYQ73R8hV9AC8nSf0djlQBWEoMF0D921s6Xs229Xk5/e8UTJz0oJQblnNBqbOrYQpRQf\nvGcH20qkjgL2ZD1dCJ7tHmcgkuS1N7XbLixLsAYjKUZjabuE9A7T2nh+KGoXkwPwmRN9fzhByOey\nm9X0m643v6wjWFXIb3ONo7XmTZ9+kueHDL/9227r5I9eO309YHmevjTKs1fDnOid4MXbm8sed6w7\nzI62oF1g7PJoeSH4zGMXqPM6efsLNwJTE+l4PI3f47TfrOPpHJdHY3ZGzZMXjM5e1RACK04wPVuo\n6JiAUZxOa41SirFYmrd99iC3bGzgymjMXngWslxDZVJII4ks21rm/6dY41DUumpmuIa+fbwfd42D\nu29ow6EUSsGx7gnu2tlqB4b3mBbB5mY/NQ7F+cHJohXDtkUQTrKx0UddrfE76DOD8eIaWl2IRbDG\niaayPHM1zA3r6mjwue36NnNl0JwYrIBnKbTWHOsJs68zRIPfTX2ta0arSIv+iQTfPTXALx/YZAck\nrc5Xlo89HM9glQg6WRAnePLCKNtbA7QGF1/WuDngwe00JtNyNPndZHLabrt4ZiDCucEoDxzupm8i\naTd4mS1YHElm7Il2vhgVSKeykdLZPA8e7ePuG4xyGAGPk+2tAdsiONUXQSm4wRRkj7OGTU0+zg1G\niadztsvHZ8ZYBieT1Ptc9vgsi0CCxasLEYIVRP9Egjs/9mMePTszG+ZaMRo13q5/cX8nt3U1zrtp\n+4C5Sri7gs//ymiccDzDTaaboqvZbwuB1roov757LIHWcGDLlHXRME0IxuNpdrQFcdc4OG3GCdLZ\nPIcuj1UlPgDwG3dt5TPvvKXihNfkt9paGs9sxPz3gfsP8L/feKNdUM3rqsHjdJSMEWitiSQy1HkX\nJgSFbR8BfvjcIGOxNG+9bSqusHdDiGPdxpqHk30TbG72F73Rb28N8PyQaRGYloD1udYQqnXZ4+u3\nLQKJEawmRAhWEP/nkTP0hhNlM1GuBVbd/aaAm6aAm7FYel7VLAfMFMXuMr5ygOPmW/tNGwy/9OYm\nnx0j+J/fPMl7/uWQfayVEWS9RRduWxNpOJ6hJehhZ3uQk33GtY/3hImncxzYWt49NR+2twV5xa7y\n1gAYriHADqCOmGsHtrUGeMcLN7GpyV/0M5SKEcTSOfIa6moX9oYd8BZ3KXvgUDfr6r28dPvUOpy9\nnSFGY2n+6Jsn+enzw7zAjA9YbG8Ncnk0Tth0vcGURWCNvb7WCh5LjGA1IkKwQjh0eYyHjhnr8Iaj\n164Wz3Sst9jmgIcGn5tUNm8HZeeC7RqqYBFcGIqiFHbQc3NzgL6JJOeHJvnyoW5O9E5l/1iTZSkh\nGLddQ2lCPjc3rq/jVF8ErY2SzUrBi7Y0znnsi6XJjCNYC9tGoim71eV0QrWlK5BahdwWahH43U7b\nNdUXTvD488O8+dYN1BSU1755o2GJPXCom1fsauX37t1ZdI3tbQFyec2F4ViBEExN9CGfe8oiCCfx\nmZlFwupBZH0FkMtr/uxbp2iv8+JxORiKLL5f7lyxXENNAbc9sY3F0nMOBlquoZ4KMYJLIzE66mvx\nuoy3zK5mI1Xyj795ilxe26mhSinbIrDcQVAQbDXfvMOJDA0+F9vbgvzHz7p54vwoDxzq5saOejue\nsBQ0FjwvMJ5lk99dcpKs97lsiyaSnHIFWaWd6xcYIwh4nPbv4GtHetCaGemmezrq+ad372fXujrW\nl1hxbXU+y+W1XUOo0CKor52KESQyuZIZTsL1jVgEK4BvHevjZG+ED79mFxsbfQxNLqUQGPdq9Lvt\nlMnxWdoqWiQzOSYSGYIeJyPRtN3YZDqXR2Nsbp5yk1jbBy+O4nU5yOanAq7j8QyuGlU0EbmdDvzu\nGsKJDLm8ZiKRIVTrsnPh3/X5p0lmcvz5G26c50+/OKwYge0aik61ppxOqNaoQPqNZ3vY+2ff54S5\n2tcqdb2YYLHlGvrm0V4ObGliY9PMNQl339BWUgQAtrT47eC7b1qMAAyLzON04DbbTUqgePUhQrDM\naK35zGMX2N4a4Odv6qAl6LHr1CwFo7E0Qa8Tj7PGfsOd3p2rHAOmW+iWTQ3AVAP2QrTWXBqJ2VYA\nGMFii1+5wwioWgueJhKG22d6lfKQ2SxmMpkxApg+N7va66h11dDV7Ocbv3En+8x0zaWi1qzbP1Yo\nBGXelkM+F91jcT78nyfQeip9dtGuITNrKBxPc3E4VtR9ba54XTV2PKNkjKDW+H1YcQwJFK8+RAiW\nmUfPDnNmYJL/9rKtOBzKFoKlKsVU+BZrCcH4XIXAdEnc1mUIQak4wVgszWQyS1dB4LTO62J9qJZX\n7mnj9s0N9nHGvTOlfexmsNWKEzT4XdS6a/jOB17CQ+9/ccm34KWg0e8uEII0zYHSrqmQz00snbO7\no1lWl+UaWmiwOGgGi4+ZFsa+DQsTQyt+Y7mGPE6HHWewYjSWWEmgePUhQrDMfPqxC6yr9/L6vcaK\n29agl3Qub5dRuNZYfm2Y6fOejUFTCPZ3GQHaUkJgvfkWuoYAvvK+A/z1W/fNSA0NJ9JF8QGLkM/F\neDxN2MoqMuMGXc3+ZXVVNPndjEQN4R6u4BpaV+/F6VB85p23AlOxmWoEixOZHEeujKMU3LihfvaT\nSmCtMLZcQ0pNuees+EXQ/FdcQ6sP+Y0uI89cHednl8b4n6+9AbfT0GRrEdLQZGpJAp+jsZQ9Sdd5\nnTgdas5CYLmGdncYLppSKaSXRgxxmC4Elr/amvSte4bjGTY2zny7D/nc9IcjtmAUZhUtJ41+N0OT\nKSZTWdLZfFmL4B0v3MS9e9pZH6qlvtZVYBEY/v2gd2F/ipab5uCFEba2BBYsKFbAuHCS97udTCaz\nBRbBzPiBsDoQi2AZeehoHz53DW+/faO9zxaCJcocGo2maTLfYpVSNBS4OmZjIJLE766hzutiQ0Nt\naYtgJEaNQxU1XSlkeoB6PJ4uOck3mF2+rMybpcwOqkRTwMNYLG2/4ZezCNxOhy1+TX63HYeJJDL4\n3TU4axb2p2hN3M9eDdt1hRbC3s4QTocqKoXt89RQ41D2PayAtsQIVh8i7cvI1bE4m5qKV3m22BbB\n7GsJTvZO0BL00Fa3sJIKubxmLJ4umrwafXMXgsFIkrZ6496djb7SFsFojA0NtbjKTHR1Xic1BVZI\nOJ4p7RqqdROOpxkzC841rBCLwJrUC/sPzEaD323HYRZTXgKm3s6zec2+zoW5hcCw2I788T1Faax+\nt5NQrcsO3FufSYxg9SEWwTLSO54o6lML0GpO6nPJHHrPvxzib3/0/ILvPx5PozVF7ozG+VgEE0na\nzfF2NtTSMxZHa82zV8dt6+DySKwoUDwdpRQNZkZQIp0jlc1TX2KSD/lc5LURh1CKGbX7l4tGv5t0\nNm+vlJ6LEBQ+40giu2B3DkyVogbsIncLZfpahlp3TdHvwg4Wi2to1SFCsExorekNJ2bkdluNw2db\nS5DK5hiaTNl1bhaCvZjMX2AR+N2MzXEdwWAkNSUEjT4mU1kePTvMW//hIPf/6xHyeSN1dHp8YDqN\nfhfjsSm3T+lgsbHv0kiM+lpX0crZ5cQKsJ8bnASgOTi7y6rQ6ppIZBacMQRTriF3jYNd7XULvk4p\ndq+r48aOKSvDGqcEi1cf8htdJiJm27/pFgEYcYLZhMCKIUymFp5dZC0ma1qARZDP6yLX0Aazscpv\n/Psz1DgUz/VH+PozPcTTObpmSe1s8BniY/UZKJU+armCLo/GSgrFcmE9u7ODRhmNxjmMrTHgNq0x\nTSSZscV0IVhumt0ddXbCQbX409fvKfpeLILVi1gEy4RVtrmUELQEPQxFKscIrBz+aLL0at65MBKz\nApxTk1eD381EIkM2V7mV5GgsTTavCywC4+fIa82X7z9AW52Hj33nDFC8gKwUDT7DZ14pEGwFkHvG\nEwsux3AtsKypcwOTNPjccwr6FpavXmyMwHo7X4rFdBIsXr2IECwTVpP19aGZb8utQS/D0coWgZW6\nObkIIbAtggLXUJPfjdblm6hYWGsIrED1luYAO9uCfOxNL2BfZ4j3vniznRmzpbl0hy2LBr/bXCNQ\nPjXUEodcXq+YQDFMuYYGIsmyqaPTsVNmo2kzRrDwN+zWOg97Oup41Y3tC77GXLHGKa6h1YcIwTJh\ntThcX8YiGJ4lfdSaiCOLEoI0NQ5V9IbdMMfVxZYQtZuuoVp3Dd/74Et5480bAHj77RsJep24ahQd\nocquj0a/i/F4xnZJlc4aKqxGuvJcQzC3QDEUlq9OMblIi8DrquHh334JL9pSnT4Mldi9ro6bNtTb\nTW2E1YMIwTUmmsryF989Y1sAFr3hBLWumpJvt611HiZTWRIVykFPWQSLiBHEUjROq5bZNMd6Q5Zr\nqpx/O+h18fuv3Mkbb14/q7ukwecml9e2u6yURVBfJAQrxyLwuZ14XcbPN2chMIWseyxh9CJYIRlQ\ns9Fa5+Wh97+YjjLF64TrFxGCa8wPTg/w6Ucv8MZPPmFXnASjbPOGhtoZxdUAWgKzryWwJuJUNk86\nW9mfX46RgvISFtbb+GwWQf9EAoeiojvkXQe6+Pib9846Dsu9cnE4htflsMtVF+KscdiuCau8xErB\ncq3NWQjMn9cqv7GYrCFBqAYiBNeYM/2TuGscuGocvPUfDvLM1XHAsAhKuYVgai1BpcwhyyKAhVsF\noyVq48ylAmksleVrR3rY1xla8IrYQix31KWRyhlBlkuowb+y3qAt91DTHGMEthCYaw+uF4tAWL2I\nEFxjnhuYZFtrgG/85h14XA7+7eAVwIgRlKsPb5WZqLSobCCStHPpo6mFxQlGY+kZk5c1yVayCD71\n6HkGIyn+6LW7F3Tf6ViT/5XRWMWMIMuNtpJiBDA1sbfM0SLwuY0expdHDVfYYmIEglANRAjmwEe/\ndZqfnFlYQ/mzAxF2rQvSGvRy144WHj03zGTSKKdcziKwy0yUSSHVWjMUSbHJzM9faOaQUXm0ePLy\nOGsIeJxlLYKro3H+8aeXeOPN67nV7EOwWCyfeSanK1oE9eZnpdYZLCeWEMxlMRkYq6kb/e4p15BY\nBMIyI0IwC/F0ls8/ccnuJzwfxmJpBiMpbjBXfL58VytjsTTfOTkATC3Cmk6jz43Tocq6hsZiadK5\nPNvNGvKRBbiGkpkc0VS2pDuj0UznLMXHvvscTofiD161a973LEehq6dSINiyCFbSgjKYCrDPNUYA\nxjO20mUlRiAsNyIEs3DJ9ONWas5ejjMDRlP2ne1Gid+Xbm9BKfj3pwz3UDnXkMOhaA54iuIAhViB\nYqt0cDmLQGvNb37pGb5VQsRGSywmsyhXgfT80CSPnBjg11682U4brQYBj5FmCpXdPpYlsJKyhgC7\neut8hcBCLAJhuZFXkVm4MGwKQYXm7OU4O2DUn9m1zpiwG/xubu4M8czVMFB6VbHFrZsa+PHZIVLZ\nqa5WFtYagu1mM5FyQnDo8jgPH+8nkc7x82bjG4upXsUzJ68mv9u+RyH/8NhFvC4Hv3Ln5rLjXghW\n4TmjB0MFi8CcPFeaELx+bwdaG81n5kqhECy0F4EgVAuxCGbhwlAUMAqsJTPl8/ot/s8jz/GRB08C\nRsZQk99dFER8xa5WwCgSVim4+Jb9GwjHM/zg9OCMzwYmjEl8a4shBNEyrqEHDnUDcKw7PKP1pdVf\nuNRiL6vkQ/E9k3zzaC+/uL+zaBKrFtY1K60aftMtG/hfb7hxxVQetegI1fLrd20tmQpcDsu9tZhe\nBIJQLeR/4CxcNF1DwIxFYaX40Zkh/vWpK1wYjnJmIMLO9mDRBHHXTkMIOkLeooVc03nJ9hY66r32\nZF7IQCSJUrClxajhU8oimExmeOREP/W1LkZj6RmN5a+YGSubSpSIbgq4GYmli8Tj809cIq/h116y\npdKPv2BCc8gI6mz08c4Xbbom919qrLjCSqqbJKxdRAhm4cJQ1P5jnUucYGAiidbwmUcvcG4wOqM0\n8J6OOlqDnrIduyxqHIo337qB/zo/Qs80t9TgRJImvwef24nH6WCyRProt471k8jk+L1X7gTgWE+4\n6POrYzGa/O6SdWM6G2pJZ/MMmmUuUtkcX3r6Kq99wbpZx71QLItgpWUEXSssN5ekjgorARGCCuTz\nmosjUV6yvRmgZAeuQiaTGaKpLAGPk68900Mik7PjAxZKKT79zlv48KtvmPX+b9nfidbwtSM9RfsH\nIkna6w23UtDrKrmg7IHD3exsC/KL+ztxOx0c6y4WgiujcTaWKQ+9xXQ5XRg23GKXRmJEU1l+bnfb\nrGNeKA32YrGVlRF0rbAsAgkUCysBEYIK9EeSJDN5XrSlCbfTQc8sFoGV5fPrd23FcvrcUKJZyK2b\nGtndMXvhrs5GH3dua+JrR3qK3DSDkanOYHVe54zCcxeHoxzrDvOW/RtwOx3s6ajjWPdE0TFXRuNs\nKvN2b8UeLppCcG7Q+HdHW+Uqooth7VoEEigWlp81IQTZXJ7YAlbfWoHiba0BNoRqZ80c6jOF4PbN\njbzupg5cNcrO7Fko9+1bT894guMFdYoGIkm7/HPQ65wRI3j60hgAd99gvMHv3RDiRO+E3WMgnc3T\nP5FgY5kWkm11HvzuGjtj6vzgJA7FrJ3GFkNbndesXTT3FMzrGbEIhJXEmhCCD37lGG/81BPzPs9y\njWxtCbCh0Uf3WGXX0MCE8Xl7nZc/f8ONfPn+AyULqM2He3e34XQoHjnRDxgLwcLxqa5WQa9rRtbQ\noctjNPnddmewfZ0hEpkcz5vC1jMeJ69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LMmcsYMyfA8YLjj280OcsK4sFQRDWONd7sFgQ\nBEFYJCIEgiAIaxwRAkEQhDWOCIEgCMIaR4RAEARhjSNCIAiCsMYRIRAEQVjjiBAIgiCscf5/yZvm\nv2Mz/jkAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pyplot.plot(year, temp_anomaly);" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "Now we have a plot but if I give you this plot without any information you would not be able to figure out what kind of data it is! We need labels on the axis, a title and why not a better color, font and size of the ticks. \n", "**Publication quality** plots should always be your standard for plotting. \n", "How you present your data will allow others (and probably you in the future) to better understand your work. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's make the font of a specific size and type. \n", "We don't want to write this out every time we create a plot. \n", "Instead, the next few lines of code will apply for all the plots we create from now on." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from matplotlib import rcParams\n", "rcParams['font.family'] = 'serif'\n", "rcParams['font.size'] = 16" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We are going to plot the same plot as before but now we will add a few things to make it prettier and **publication quality**." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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+JL4CdoqY2WK8WO8PlDnnGoFbgI+b2RJ/v4uBS4HPjEWcIiIik11razdVVe28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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#You can set the size of the figure by doing:\n", "pyplot.figure(figsize=(10,5))\n", "\n", "#Plotting\n", "pyplot.plot(year, temp_anomaly, color='#2929a3', linestyle='-', linewidth=1) \n", "pyplot.title('Land global temperature anomalies. \\n')\n", "pyplot.xlabel('Year')\n", "pyplot.ylabel('Land temperature anomaly [°C]')\n", "pyplot.grid();" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "Better ah? Feel free to play around with the parameters and see how it changes. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 3: Apply regression" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's now fit a straight line through the temperature-anomaly data, to see the trends. We need to perform a least-squares linear regression to find the slope and intercept of a line \n", "\n", "$$y = mx+b$$\n", "\n", "that fits our data. Thankfully, Python and NumPy are here to help! With [`polyfit()`](https://docs.scipy.org/doc/numpy-1.10.0/reference/generated/numpy.polyfit.html), we get the slope and y-intercept of the line that best fits the data. With [`poly1d()`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.poly1d.html), we can build the linear function from its slope and y-intercept." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true }, "outputs": [], "source": [ "m, b = numpy.polyfit(year, temp_anomaly, 1)\n", "\n", "f_linear = numpy.poly1d((m, b)) " ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " \n", "0.01037 x - 20.15\n" ] } ], "source": [ "print(f_linear)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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yOZ4lMt38D2NMsYjsi3H8dGBVEmJSSiml1BAQCITwegM4nVbS0sL7KUdrYt1R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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pyplot.figure(figsize=(10, 5))\n", "\n", "pyplot.plot(year, temp_anomaly, color='#2929a3', linestyle='-', linewidth=1, alpha=0.5) \n", "pyplot.plot(year, f_linear(year), 'k--', linewidth=2, label='Linear regression')\n", "pyplot.xlabel('Year')\n", "pyplot.ylabel('Land temperature anomaly [°C]')\n", "pyplot.legend(loc='best', fontsize=15)\n", "pyplot.grid();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Split regression" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We have the linear function that best fits our data but this doesn't look like a good approximation. If you look at the plot you might have noticed that around 1970 the data temperature starts increasing faster. \n", "\n", "What if we break the data in two (before and after 1970) and we do a liear regression in each segment? To do that, we need to find in which position of our `year` array is the year 1970 located. Thanksfully, `numpy` has a function called [`numpy.where()`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.where.html) that can help us. We need to pass a condition and `numpy.where` will tells us where in the array the condition is `True`. \n" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(array([90]),)" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "numpy.where(year==1970)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To split the data, we can use a powerful instrument: the colon notation. A colon between two indices indicates a range of values from a start to an end. The rule is that `[start:end]` includes the element at index `start` but excludes the one at index `end`. For example, to grab the first 3 years in our `year` array, we do:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([ 1880., 1881., 1882.])" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "year[0:3]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we know how to split our data in two sets, to get two regression lines" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": true }, "outputs": [], "source": [ "year_1 , temp_anomaly_1 = year[0:90], temp_anomaly[0:90]\n", "year_2 , temp_anomaly_2 = year[90:], temp_anomaly[90:]\n", "\n", "m1, b1 = numpy.polyfit(year_1, temp_anomaly_1, 1)\n", "m2, b2 = numpy.polyfit(year_2, temp_anomaly_2, 1)\n", "\n", "f_linear_1 = numpy.poly1d((m1, b1))\n", "f_linear_2 = numpy.poly1d((m2, b2))\n", "\n" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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jo9EK5+XLYdQouPZa0JrSjD6k9TfW4ubkpNRvg9OMzZur6N07nRNO6E2/fumY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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pyplot.figure(figsize=(10, 5))\n", "\n", "pyplot.plot(year, temp_anomaly, color='#2929a3', linestyle='-', linewidth=1, alpha=0.5) \n", "pyplot.plot(year_1, f_linear_1(year_1), 'g--', linewidth=2, label='1880-1969')\n", "pyplot.plot(year_2, f_linear_2(year_2), 'r--', linewidth=2, label='1970-2016')\n", "\n", "pyplot.xlabel('Year')\n", "pyplot.ylabel('Land temperature anomaly [°C]')\n", "pyplot.legend(loc='best', fontsize=15)\n", "pyplot.grid();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## We learned:\n", "\n", "* applying linear regression to data\n", "* making our plots more beautiful\n", "* accessing chunks of an array\n", "* The Earth is warming up!!!\n" ] } ], "metadata": { "anaconda-cloud": {}, "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 }