Set matplotlib style following UNHCR's Data Visualization Guidelines
Project description
unhcrpyplotstyle
The unhcrpyplotstyle
package provides Matplotlib styles following UNHCR Data Visualization Guidelines which ensures charts are professional and brand–compliant. The porpose of this package is to ease and speed up the chart creation process using Matplotlib custom stylesheets.
Getting started
The easiest way to install unhcrpyplostyle
package is by using pip
:
# to install the lastest PyPI release
pip install unhcrpyplotstyle
# to install the latest Github commit
pip install git+https://github.com/leichen88/unhcrpyplotstyle
The pip installation will automatically download and store all Matplotlib custom style files (*.mplstyle) in the appropriate local directory of your computer.
Use the styles
unhcrpyplotstyle
is the base style of this package. It provides basic styles to the chart elements such as color, font, fontsize, and position. To use the base style you can simply call it from your local style directory after importing matplotlib
library.
import matplotlib.pyplot as plt
plt.style.use('unhcrpyplotstyle')
Once the base style is applied then you can add a specific style related to the type of chart that you want to use by simply combining two styles together:
import matplotlib.pyplot as plt
plt.style.use('unhcrpyplotstyle','column')
In this case, thecolumn
style will add some of the parameters to the base style unhcrpyplostyle
in order to align all styles of chart elements with a standard UNHCR style column chart.
See the full list of styles based on chart types below:
area
bar
bubble
column
connected_scatterplot
donut
dotplot
heatmap
histogram
line
linecolumn
map
pie
population_pyramid
scatterplot
slope
streamgraph
treemap
Example
The chart with unhcrpyplotstyle
+ column
styles:
Find code example for column chart here.
The chart with unhcrpyplotstyle
+ bar
styles:
Find code example for bar chart here.
The chart with unhcrpyplotstyle
+ line
styles:
Find code example for line chart here.
The chart with unhcrpyplotstyle
+ scatterplot
styles:
Find code example for scatterplot here.
Project details
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