An extension library for creating strip plots or dot charts w/ matplotlib + seaboard
Project description
Great things come in tiny packages. A bare minimum extension library for creating tree dot plots, strip plots or dot charts w/ matplotlib or seaborn in Python
- Designed to work with
matplotlib
andseaborn
in Python - Fully customizable
installation
pip install dotplotlib
basic usage
dotplotlib
can be used to generate dot charts with minimal code. Here are some basic examples:
Example 1: Simple Dot Chart
.dotchart
returns x
and y
lists that can be inputted straight into matplotlib
or seaborn
scatterplots.
from dotplotlib import dotchart
import matplotlib.pyplot as plt
data = {'size': [1, 2, 2, 3, 3, 3, 4]}
# Generate dot chart data
x, y = dotchart(data['size'])
# Plot
plt.scatter(x, y)
plt.show()
Example 2: Dot Chart with Color Mapping
Pass the data you would like to color by with the color_by=
argument.
Returns an extra c
list that should be passed into the c=
parameter if using matplotlib
or hue=
if using seaborn
.
from dotplotlib import dotchart
import matplotlib.pyplot as plt
data = {'size': [1, 2, 2, 3, 3, 3, 4], 'rating': [3, 2, 5, 4, 3, 6, 4]}
# Generate dot chart data with color mapping
x, y, c = dotchart(data['size'], color_by=data['rating'])
# Plot with color mapping
plt.scatter(x, y, c=c, cmap='viridis')
plt.colorbar()
plt.xlabel('Size')
plt.ylabel('Number')
plt.title('Mushroom Size Count Colored by Rating')
plt.show()
Example 3: Using make_dotchart
for Simplified Plotting
Instead of just giving you x, y
lists to make the plot yourself, make_dotplot()
actually generates the plot.
from dotplotlib import make_dotchart
df = {'size': [1, 2, 2, 3, 3, 3, 4], 'rating': [3, 2, 5, 4, 3, 6, 7]}
# Create a dot chart with optional arguments (only the first one is mandatory)
make_dotchart(df['size'],
color_by=df['rating'], # list to color by
reverse=False, # inverts the color mapping
theme='gnuplot2', # scroll down to see all themes
colorbar=True,
xlabel='Sizes',
ylabel='Size Count',
title='Mushroom Sizes Colored by Rating',
dot_size=40):
Example 4: If plotting in a Jupyter Notebook
If plotting inline, use the default .dotchart()
to obtain x
and y
lists, and then adjust as necessary with one of the following:
plt.figure(figsize=(12,6))
plt.figure().set_figwidth(12)
plt.figure().set_figheight(12)
preset themes
custom:lavender
cmap
Any cmap value supported by matplotlib (see here) will work when passed into theme='viridis'
.
viridis:
gnuplot:
features
- generate strip plots/dot charts by exploiting
matplotlib/seaborn
scatterplots - supports any cmap color profile
- the data can be automatically sorted for better visualization, especially when using color mapping.
- accepts both list and pandas.Series as input data.
- set custom labels, titles, and dot sizes for your charts.
- works with Jupyter Notebook
attribution
- pjarzabek
- m3
- ddlegal
feature requests
- apply to become a contributor (pls help)
- open an issue on our GitHub repository
- email me: justinkhlee27[at]gmail.com
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