Hourly heatmap graph using Python’s ggplot2 implementation ‘plotnine’?

Question

I am trying to create an hourly heatmap from within Python. A code example of this graph made in R is available here: r-graph-gallery.com/283-the-hourly-heatmap.html. It relies on ggplot2.

There also is a Python implementation of ggplot2 called plotnine: github.com/has2k1/plotnine

Anybody able to “translate” from R to Python?

Answer 1

Here's a simple recreation in plotnine docs using a small dataset. Most of the geom_* elements from ggplot2 are implemented (mostly with underscores replacing dots in names). If you want to maintain the R flavor of directly calling the geom_* functions, you can just change the first line to from plotnine import *.

import plotnine as p9
import pandas as pd
import numpy as np

#%% Build dataset
df = pd.DataFrame({'Month':pd.Categorical(['Jan','Feb','Mar']*2*3*4,
                                          categories=['Jan','Feb','Mar']),
                   'Year':([2004]*3+[2005]*3)*3*4,
                   'Hour Commencing':([1]*3*2+[2]*3*2+[3]*3*2)*4,
                   'Day':[j for i in range(1,5) for j in [i]*3*2*3]})
# Add the hourly temp as random values
df['Hourly Temps'] = np.random.randint(-10,40,size=df.shape[0])


#%% Build the plot
g = (p9.ggplot(df,p9.aes(x='Day',y='Hour Commencing',fill='Hourly Temps'))
     + p9.geom_tile(color='white',size=.1)
     + p9.facet_grid('Year~Month')
     + p9.labs(title='Hourly Temps - Station T0001')
     + p9.scale_fill_cmap('plasma')
     + p9.theme(legend_position = 'bottom',
               plot_title = p9.element_text(size=14),
               axis_text_y = p9.element_text(size=6)))
print(g)