Matplotlib: Difference between revisions

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Very nice site!
== Project ==
Very nice site!
Learn how to plot data with the matplotlib plotting library. Ditch Excel forever!
== Goals ==
* practice reading data from a file
* practice using the matplotlib Python plotting library to analyze data and generate graphs
== Project setup ==
=== 1. Install the project dependencies ===
Please follow the official matplotlib installation instructions at
The dependencies vary across operating systems. summarizes what you'll need for your operating system. We also give specific recommendations for each platform below.
Installing matplotlib and its dependencies is somewhat involved; please ask for help if you get stuck or don't know where to start!
==== Windows users only ====
# Download and install numpy from
# Download and install matplotlib from
==== Mac OS X users only ====
If you do not already have a C compiler installed, you'll need to install one before you install matplotlib. You have several options depending on your situation:
# Download and install Xcode (1.5 GB) from
# Download and install Command Line Tools for Xcode (175 MB) from This requires an Apple Developer account (free, but you have to sign up).
# Download and install kennethreitz's gcc installer (requires 10.6 or 10.7) from
Please wave over a staff member and we'll help you pick which option is best for you computer.
# Download and install numpy from
# Read and then download and install matplotlib from
==== Linux users only ====
# Install the <code>python-numpy</code> package through your package manager
# Install the <code>python-matplotlib</code> package through your package manager
=== 2. Download and un-archive the Matplotlib project skeleton code ===
Un-archiving will produce a <code>Matplotlib</code> folder containing several Python and text files.
=== 3. Test your setup ===
Run the <code></code> script in your <code>Matplotlib</code> directory. A window with a graph should pop up.
Very nice site!
== Project steps ==
<pre>pyplot.plot([0, 2, 4, 8, 16, 32], "o-")</pre>
and re-run the script. What changed?
y_values = [0, 2, 4, 8, 16, 32]
pyplot.plot(x_values, y_values, "o-")</pre>
and re-run the script. What changed?
Note how matplotlib automatically resizes the graph to fit all of the points in the figure for you.
* What does matplotlib pick as the x values if you don't supply them yourself?
* What options would you pass to <code>pyplot.plot</code> to generate a plot with red triangles and dotted lines?
=== 2. Plotting the world population over time ===
will plot <code>my_data_1</code> in magenta and <code>my_data_2</code> in blue on the same figure.
Supply labels for your plots, like above. Then use <code>pyplot.legend</code> to give your graph a legend. Just plain <code>pyplot.legend()</code> will work, but providing more options may give a better effect.
Your graph should look something like this:
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