I have a plot in ggplot2 (R) that I want to replicate using matplotlib (Python):
ggplot(data = sca, aes(x = Total_Value)) + geom_density() + facet_wrap(~Era) + theme_minimal()
How can I recreate this using matplotlib, and additionally, how could I overlay the density plots over one another (color coded) in either language/library?
Thank you.
The simplest way to recreate ggplot2 facets is using seaborn:
pip install seaborn
Depending on the plot type, use one of seaborn's figure-level functions:
seaborn.relplot for relational facets (scatter, line)seaborn.displot for distribution facets (hist, kde, ecdf)seaborn.catplot for categorical facets (bar, count, point, strip, swarm, box, boxen, violin)So for density facets, use seaborn.displot with kind='kde':
Sample data
import pandas as pd
import numpy as np
df = pd.DataFrame({'Era': np.random.choice(range(1960, 2180, 20), 200), 'Total_Value': np.random.random(200)})
# Era Total_Value
# 0 2140 0.479988
# 1 2100 0.232373
# 2 2060 0.801881
# .. ... ...
# 199 2140 0.823781
Set col='Era' for a grid
import seaborn as sns
sns.displot(data=df, kind='kde', x='Total_Value', col='Era', col_wrap=4)
Set hue='Era' for overlays
import seaborn as sns
sns.displot(data=df, kind='kde', x='Total_Value', hue='Era', palette='Purples')
