Plotting

Import the LArray library:



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from larray import *

Import the test array population from the demography_eurostat dataset:



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demography_eurostat = load_example_data('demography_eurostat')
population = demography_eurostat.population / 1_000_000

# show the 'population' array
population

Inline matplotlib (required in notebooks):



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%matplotlib inline

In a Python script, add the following import on top of the script:



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import matplotlib.pyplot as plt

Create and show a simple plot (last axis define the different curves to draw):



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population['Belgium'].plot()
# shows the figure
plt.show()

Create a Line plot with grid, title, label on y axis and user-defined xticks.
Save the plot as a png file (using plt.savefig()).
Show the plot:



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population['Belgium'].plot(grid=True, xticks=population.time, title='Belgium')
# add a label aling the y axis
plt.ylabel('population (millions)')
# saves figure in a file (see matplotlib.pyplot.savefig documentation for more details)
plt.savefig('Belgium_population.png')
# WARNING: show() reset the current figure after showing it! Do not call it before savefig
plt.show()

Specify line styles and width:



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# line styles: '-' for solid line, '--' for dashed line, '-.' for dash-dotted line and ':' for dotted line
population['Male'].plot(style=['-', '--', '-.'], linewidth=2, xticks=population.time, title='Male')
plt.ylabel('population (millions)')
plt.show()

Move the legend inside the graph (using plt.legend(loc='position')):



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population['Belgium'].plot(xticks=population.time, title='Male')
plt.ylabel('population (millions)')
# available values for loc are: 
# 'best' (default), 'upper right', 'upper left', 'lower left', 'lower right', 'right',
# center left', 'center right', 'lower center', 'upper center', 'center'
plt.legend(loc='lower right')
plt.show()

Put the legend outside the graph (using plt.legend(bbox_to_anchor=(x, y))):



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population['Belgium'].plot(xticks=population.time, title='Male')
plt.ylabel('population (millions)')
plt.legend(bbox_to_anchor=(1.25, 0.6))
plt.show()

Create a Bar plot:



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population['Belgium'].plot.bar(title='Belgium')
plt.ylabel('population (millions)')
plt.legend(bbox_to_anchor=(1.25, 0.6))
plt.show()

Create a stacked Bar plot:



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population['Belgium'].plot.bar(title='Belgium', stacked=True)
plt.ylabel('population (millions)')
plt.legend(bbox_to_anchor=(1.25, 0.6))
plt.show()

Create a multiplot figure (using plt.subplot(nrows,ncols,index)):



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figure, axes = plt.subplots(nrows=len(population.country), ncols=1, sharex=True, figsize=(5, 15))

for row, c in enumerate(population.country):  
    population[c].plot(ax=axes[row], title=str(c))
    plt.ylabel('population (millions)')
    
plt.xticks(population.time)
plt.show()

See plot for more details and examples.

See pyplot tutorial for a short introduction to matplotlib.pyplot.