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kashyapchhatbar/global_temperature.ipynb

Created September 16, 2016 14:35
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An attempt to recreate global temperature plot from Earth Observatory, NASA in Python
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global_temperature.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plotting global temparature rise (again) in Python\n",
"\n",
"Earth Observatory recently showcased the visualization of warmest August in 136 years [here](http://earthobservatory.nasa.gov/blogs/earthmatters/2016/09/12/heres-how-the-warmest-august-in-136-years-looks-in-chart-form/)\n",
"\n",
"This is an attempt to replicate the animation showcasing the warmest August that we have had yet. Also, I have shamelessly ripped off [@BioMickWatson](https://twitter.com/BioMickWatson) from his [blog post](http://www.opiniomics.org/how-to-produce-an-animated-gif-of-rise-in-global-temperature-in-r/) so as to minimize URL hunting. This is very similar but implemented in Python as compared to R.\n",
"\n",
"Here's the [gif](http://imgur.com/a/JOclo)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#Import all the good stuff\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.animation as animation\n",
"\n",
"#Use seaborn to set matplotlib theme\n",
"sns.set_context(\"paper\", font_scale=2)\n",
"sns.set_style(\"ticks\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#Download data\n",
"data = pd.read_csv(\"http://data.giss.nasa.gov/gistemp/tabledata_v3/GLB.Ts.csv\", \n",
" skiprows=1, usecols=range(0, 13), index_col=0)\n",
"\n",
"#Get months' list\n",
"months = list(data.columns)\n",
"\n",
"#Replace months' names to int for plotting purposes\n",
"data.columns = list(range(1,13))\n",
"\n",
"#Replace data from Sep '2016 \n",
"data.replace(\"***\", 0, inplace=True)\n",
"\n",
"#Remove rows with any NaNs if found\n",
"data.dropna(inplace=True)\n",
"\n",
"#Convert values to float\n",
"data = data.copy().astype(float)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#Anomalies recommended to add to the values\n",
"anomalies = pd.read_csv(\"http://data.giss.nasa.gov/gistemp/faq/merra2_seas_anom.txt\", \n",
" skiprows=3, sep=r\"\\s+\", usecols=[0,2], index_col=0)\n",
"anomalies = list(anomalies.seas_anom.values)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"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>1</th>\n",
" <th>2</th>\n",
" <th>3</th>\n",
" <th>4</th>\n",
" <th>5</th>\n",
" <th>6</th>\n",
" <th>7</th>\n",
" <th>8</th>\n",
" <th>9</th>\n",
" <th>10</th>\n",
" <th>11</th>\n",
" <th>12</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Year</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>1880</th>\n",
" <td>-0.84</td>\n",
" <td>-0.42</td>\n",
" <td>-0.50</td>\n",
" <td>-0.68</td>\n",
" <td>-0.38</td>\n",
" <td>-0.51</td>\n",
" <td>-0.50</td>\n",
" <td>0.05</td>\n",
" <td>-0.52</td>\n",
" <td>-0.70</td>\n",
" <td>-0.54</td>\n",
" <td>-0.56</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1881</th>\n",
" <td>-0.80</td>\n",
" <td>-0.65</td>\n",
" <td>-0.39</td>\n",
" <td>-0.29</td>\n",
" <td>-0.06</td>\n",
" <td>-1.15</td>\n",
" <td>-0.56</td>\n",
" <td>-0.28</td>\n",
" <td>-0.38</td>\n",
" <td>-0.52</td>\n",
" <td>-0.60</td>\n",
" <td>-0.18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1882</th>\n",
" <td>0.08</td>\n",
" <td>-0.15</td>\n",
" <td>-0.11</td>\n",
" <td>-0.60</td>\n",
" <td>-0.40</td>\n",
" <td>-1.05</td>\n",
" <td>-0.73</td>\n",
" <td>-0.14</td>\n",
" <td>-0.11</td>\n",
" <td>-0.35</td>\n",
" <td>-0.42</td>\n",
" <td>-0.70</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1883</th>\n",
" <td>-0.70</td>\n",
" <td>-0.97</td>\n",
" <td>-0.48</td>\n",
" <td>-0.33</td>\n",
" <td>-0.37</td>\n",
" <td>0.42</td>\n",
" <td>-0.04</td>\n",
" <td>-0.18</td>\n",
" <td>-0.49</td>\n",
" <td>-0.60</td>\n",
" <td>-0.72</td>\n",
" <td>-0.41</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1884</th>\n",
" <td>-0.62</td>\n",
" <td>-0.37</td>\n",
" <td>-0.41</td>\n",
" <td>-0.96</td>\n",
" <td>-1.22</td>\n",
" <td>-0.84</td>\n",
" <td>-0.87</td>\n",
" <td>0.13</td>\n",
" <td>-0.39</td>\n",
" <td>-0.81</td>\n",
" <td>-0.85</td>\n",
" <td>-1.01</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 1 2 3 4 5 6 7 8 9 10 11 12\n",
"Year \n",
"1880 -0.84 -0.42 -0.50 -0.68 -0.38 -0.51 -0.50 0.05 -0.52 -0.70 -0.54 -0.56\n",
"1881 -0.80 -0.65 -0.39 -0.29 -0.06 -1.15 -0.56 -0.28 -0.38 -0.52 -0.60 -0.18\n",
"1882 0.08 -0.15 -0.11 -0.60 -0.40 -1.05 -0.73 -0.14 -0.11 -0.35 -0.42 -0.70\n",
"1883 -0.70 -0.97 -0.48 -0.33 -0.37 0.42 -0.04 -0.18 -0.49 -0.60 -0.72 -0.41\n",
"1884 -0.62 -0.37 -0.41 -0.96 -1.22 -0.84 -0.87 0.13 -0.39 -0.81 -0.85 -1.01"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#This is how the data looks\n",
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#Initialize the figure\n",
"fig = plt.figure(figsize=(10, 6))\n",
"ax = plt.axes(xlim=(.5, 12.5), ylim=(-3, 3.5))\n",
"\n",
"#Generate the list of colors\n",
"colors = sns.color_palette(\"PuRd\", len(data))\n",
"\n",
"#Create line objects which are the less pronounced\n",
"lines = []\n",
"for i in range(len(data)):\n",
" lobj = ax.plot([], [], lw=.75, marker=\"o\", ms=2, color=colors[i], alpha=0.25)[0]\n",
" lines.append(lobj)\n",
"\n",
"#Main line object which will be pronounced\n",
"mainline = ax.plot([], [], lw=3, marker=\"o\", ms=8, color=colors[0])[0]\n",
"\n",
"#X-axis data\n",
"x = list(range(1, 13))\n",
"\n",
"#Text representing the year (initially blank)\n",
"text = ax.text(6.75, 0.5, '', fontsize=24)\n",
"\n",
"#Figure aesthetics, labels, titles etc.\n",
"ax.set_xticks(range(1, 13))\n",
"ax.set_xticklabels(months)\n",
"ax.set_title(\"Temperature Anomaly (\" r\"$\\mathrm{^\\circ}$\" \"C)\\n\"\n",
" \"(Difference from 1980-2015 annual mean)\")\n",
"ax.yaxis.grid(lw=1, linestyle=':', color='grey')\n",
"sns.despine()\n",
"\n",
"#Animate function\n",
"def animate(i):\n",
" if i[1] == 2016:\n",
" mainline.set_data(x[:8], i[2]) \n",
" mainline.set_color(colors[-1])\n",
" text.set_text(\"2016\") \n",
" else:\n",
" mainline.set_data(x, i[2])\n",
" mainline.set_color(colors[i[0]])\n",
" for lnum, line in enumerate(lines): \n",
" if lnum == i[0]:\n",
" line.set_data(x, i[2])\n",
" text.set_text(str(i[1]))\n",
" return tuple(lines) + (text,) + (mainline,)\n",
"\n",
"# Init only required for blitting to give a clean slate.\n",
"def init():\n",
" for line in lines:\n",
" line.set_data([],[])\n",
" return lines\n",
"\n",
"#Convert dataframe to a list for easy iteration\n",
"rows = []\n",
"for ii, (i, j) in enumerate(data.iterrows()):\n",
" row = [l for k,l in j.items()]\n",
" for m, n in enumerate(row): \n",
" row[m] += anomalies[m] \n",
" if i == 2016:\n",
" #Don't know how to pause in matplotlib.animation so just shamelessly iterating the same thing\n",
" #over and over to let it stay\n",
" for jjj in range(100):\n",
" rows.append([ii, i, row[:8]])\n",
" else:\n",
" rows.append([ii, i, row])\n",
"\n",
"#The main animation function\n",
"ani = animation.FuncAnimation(fig, animate, rows, init_func=init, interval=100, repeat=False, blit=True)\n",
"\n",
"#Need this if you want to save a mp4\n",
"Writer = animation.writers['ffmpeg']\n",
"writer = Writer(fps=10, metadata=dict(artist='Kashyap Chhatbar'), bitrate=1800)\n",
"\n",
"#Always good to have if you are making changes to labels and stuff\n",
"plt.tight_layout()\n",
"\n",
"#Uncomment below to save a gif\n",
"#ani.save('global_temperature.gif', writer='imagemagick', fps=10, dpi=100)\n",
"\n",
"#Uncomment below to save a mp4 (recommended!!)\n",
"#ani.save('global_temperature.mp4', writer=writer, dpi=300)\n",
"\n",
"#Uncomment below to view it locally\n",
"#plt.show()"
]
}
],
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"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
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"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
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