Can't plot comparative (double) histogram from Pandas table

Question

Here's the table from the dataframe:

	Points_groups	Qty Contracts	Qty Gones
1	350+	108	275
2	300-350	725	1718
3	250-300	885	3170
4	200-250	2121	10890
5	150-200	3120	7925
6	100-150	653	1318
7	50-100	101	247
8	0-50	45	137

I'd like to get something like this out of it:

But that the columns correspond to the 'x' axis, which was built from the 'Scores_groups' column like this

I tried a bunch of options already, but I couldn't get it.

For example:

df.plot(kind ='hist')
plt.xlabel('Points_groups')
plt.ylabel("Number Of Students");

or

sns.distplot(df['Кол-во Ушедшие'])
sns.distplot(df['Кол-во Контракт'])
plt.show()

or

df.hist(column='Баллы_groups', by= ['Кол-во Контракт', 'Кол-во Ушедшие'], bins=2, grid=False, rwidth=0.9,color='purple', sharex=True);

Answer 1

Since you already have the distribution in your pandas dataframe, the plot you need can be achieved with the following code:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

Df = pd.DataFrame({'key': ['red', 'green', 'blue'], 'A': [1, 2, 1], 'B': [2, 4, 3]})

X_axis = np.arange(len(Df['key']))

plt.bar(X_axis - 0.2, Df['A'], 0.4, label = 'A')
plt.bar(X_axis + 0.2, Df['B'], 0.4, label = 'B')

X_label = list(Df['key'].values)
plt.xticks(X_axis, X_label)
plt.legend()
plt.show()

Since I don't have access to your data, I made some mock dataframe. This results in the following figure: