Matplotlib bar chart - overlay bars similar to stacked

Question

I want to create a matplotlib bar plot that has the look of a stacked plot without being additive from a multi-index pandas dataframe.

The below code gives the basic behaviour

%matplotlib notebook
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import io

data = io.StringIO('''Fruit,Color,Price
Apple,Red,1.5
Apple,Green,1.0
Pear,Red,2.5
Pear,Green,2.3
Lime,Green,0.5
Lime, Red, 3.0
''')
df_unindexed = pd.read_csv(data)
df_unindexed
df = df_unindexed.set_index(['Fruit', 'Color'])
df.unstack().plot(kind='bar')

The plot command df.unstack().plot(kind='bar') shows all the apple prices grouped next to each other. If you choose the option df.unstack().plot(kind='bar',stacked=True) - it adds the prices for Red and Green together and stacks them.

I am wanting a plot that is halfway between the two - it shows each group as a single bar, but overlays the values so you can see them all. The below figure (done in powerpoint) shows what behaviour I am looking for -> I want the image on the right.

Short of calculating all the values and then using the stacked option, is this possible?

Answer 1

This seems (to me) like a bad idea, since this representation leads to several problem. Will a reader understand that those are not staked bars? What happens when the front bar is taller than the ones behind?

In any case, to accomplish what you want, I would simply repeatedly call plot() on each subset of the data and using the same axes so that the bars are drawn on top of each other. In your example, the "Red" prices are always higher, so I had to adjust the order to plot them in the back, or they would hide the "Green" bars.

fig,ax = plt.subplots()

my_groups = ['Red','Green']
df_group = df_unindexed.groupby("Color")

for color in my_groups:
    temp_df = df_group.get_group(color)
    temp_df.plot(kind='bar', ax=ax, x='Fruit', y='Price', color=color, label=color)