23 Python: plotnine

• Python package plotnine is the Python equivalent of ggplot2

• The package is developed with the same philosophy of grammar of graphics

• Here, we provide some minimal examples of creating plots using plotnine

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23.1 plotnine: Overview

• Python package plotnine is an implementation of R package ggplot2

• plotnine: A Grammar of Graphics for Python

• The package is based on similar principles; the grammar maps data, aesthetics and objects to create plots

• The approach to the plotting are almost identical to R scripts

• Install plotnine from PyPI repository: pip install plotnine

23.2 Steps of plotnine

• Import plotnine; from plotnine import *

• Import other relevant libraries: pandas, numpy, matplotlib

• Start with ggplot()

• Supply a dataset

• Include aesthetic mapping with aes()

• Add layers as needed

• Add on geom objects geom_point() or geom_histogram()

• Add scales like scale_colour_brewer()

• Add faceting specifications like facet_wrap()

• Add coordinate systems (like coord_flip()

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23.3 Essential part

Arguments	Explanation
data =	The DATA that you want to plot
aes()	AESTHETICS of the geometric and statistical objects, such as color, size, shape and position.
geom_	The GEOMETRIC shapes that will represent the data.

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23.4 Advanced part

Arguments	Explanation
stat_	STATISTICAL summaries of the data that can be plotted, such as quantiles, fitted curves (loess, linear models, etc.), sums and so o.
coord_	The transformation used for mapping data COORDINATES into the plane of the data rectangle.
facet_	The arrangement of the data into a grid of plots
theme_	The overall visual THEMES of a plot: background, grids, axe, default typeface, sizes, colors, etc.
scale_	MAP between the data and the aesthetic dimensions, such as data range to plot width or factor values to colors.

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23.5 Geometric functions

Function	Plot	Graphical_parameters
geom_histogram	Histogram	colour, fill, alpha
geom_freqpoly	Frequency polygon	colour, fill, alpha
geom_density	Density plot	colour, fill, alpha, linetype
geom_rug	Rug plot	colour, side
geom_qq	Quantile-Quantile plot	colour, alpha, linetype, size
geom_boxplot	Box plot	colour, fill, alpha, notch, width
geom_violin	Violin plot	colour, fill, alpha, linetype, size
geom_point	Scatter plot	colour, alpha, shape, size
geom_jitter	Jittered points	colour, alpha, shape, size
geom_text	Text	colour, alpha, size, label, family, fontface
geom_bar	Bar chart	colour, fill, alpha
geom_line	Line graph	colour, alpha, linetype, size
geom_hline	Horizontal line	colour, alpha, linetype, size
geom_vline	Vertical line	colour, alpha, linetype, size
geom_smooth	Fitted line	method, formula, colour, fill, linetype, size

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23.6 Load Libraries & Read Data

Import plotnine

from plotnine import *

Import other libraries

import pandas as pd

import numpy as np

import matplotlib.pyplot as plt

Set the working directory to the data folder

Read the iris dataset as a Python object DF

DF = pd.read_csv('iris.csv')

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23.7 Single variable

23.7.1 Histogram

g = ggplot(data = DF, mapping = aes(x = 'SepalLength')) + geom_histogram()
g

<ggplot: (130071266422)>

C:\Users\s02mn9\ANACON~1\lib\site-packages\plotnine\stats\stat_bin.py:95: PlotnineWarning: 'stat_bin()' using 'bins = 8'. Pick better value with 'binwidth'.

23.7.2 Density plot

g = ggplot(data = DF, mapping = aes(x = 'SepalLength')) + geom_density()
g

<ggplot: (130071295591)>

23.7.3 Boxplot

DF[['All Species']] = ''
g = ggplot(data = DF, mapping = aes(x = 'All Species', y = 'SepalLength')) + geom_boxplot()
g

<ggplot: (130071334328)>

23.7.4 Bar plot

g = ggplot(data = DF, mapping = aes(x = 'Species')) + geom_bar()
g

<ggplot: (130071356763)>

23.7.5 Pie chart

• Currently, plotnine does not have the coord_polar function

• Use plot.pie from Matplotlib (see the chapter Python: pandas plot)

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23.8 Multple variables

23.8.1 Scatter plot

g = ggplot(data = DF, mapping = aes(x = 'SepalLength', y = 'PetalLength')) + geom_point()
g

<ggplot: (130071470240)>

23.8.2 Scatter plot with group

g = ggplot(data = DF, mapping = aes(x = 'SepalLength', y = 'PetalLength', color = 'Species')) + geom_point()
g + theme(subplots_adjust={'right': 0.80})

<ggplot: (130064782138)>

23.8.3 Boxplot

g = ggplot(data = DF, mapping = aes(x = 'Species', y = 'SepalLength')) + geom_boxplot()
g

<ggplot: (130071611094)>

g = ggplot(data = DF, mapping = aes(x = 'Species', y = 'SepalLength', colour = 'Species'))
g = g + geom_boxplot() + facet_wrap(' ~ Species')
g + theme(subplots_adjust={'right': 0.80})

<ggplot: (130064540395)>

Note:

• plotnine does not include coord_polar geom; hence pie chart cannot be created

• Scatter plot matrix using plotnine can be created with additional customised codes. Extension of GGally package in Python not yet avaialble.

• The issue of legend clipping in plotnine plots is discussed here_

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