Reputation: 2439
I have a data frame with weekdays. I need to highlight weekends ('Saturday' & 'Sunday') with a different color on my bar chart. I found some solutions where I can set a different color by index.get_indexer. But how can I do it more efficiently by setting a condition? Will appreciate your help!
# create an example of my df
dates = pd.DataFrame({'dates': ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday',
'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday'],
'stats':[10,20,30,40,50,60,70,10,20,30,40,50,60,70],
'other':[44,55,66,88,33,22,11,44,55,66,88,33,22,11]})
# And plot it...
ax = dates.plot(x='dates', y='stats', kind='bar', color='b')
ax.patches[dates.index.get_indexer([5])[0]].set_facecolor('orange')
ax.patches[dates.index.get_indexer([6])[0]].set_facecolor('orange')
# etc...
ax.legend()
plt.show()
Upvotes: 0
Views: 436
Reputation: 339240
You may loop over the dataframe and set those patches matching "Saturday" or "Sunday" to orange.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# create an example of my df
dates = pd.DataFrame({'dates': ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday',
'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday'],
'stats':[10,20,30,40,50,60,70,10,20,30,40,50,60,70],
'other':[44,55,66,88,33,22,11,44,55,66,88,33,22,11]})
ax = dates.plot(x='dates', y='stats', kind='bar', color='b')
weekend = (dates['dates']=='Sunday') | (dates['dates']=='Saturday')
for i,b in enumerate(weekend):
if b:
ax.patches[i].set_facecolor('orange')
ax.legend()
plt.show()
Not sure if this is the most efficient way.
Upvotes: 1