Group Bar Plot In MatPlotLib

Based on: Sebastian Raschka.

Want to learn more? I recommend these Python books: Python for Data Analysis, Python Data Science Handbook, and Introduction to Machine Learning with Python.

Preliminaries

```%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
```

Create dataframe

```raw_data = {'first_name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'],
'pre_score': [4, 24, 31, 2, 3],
'mid_score': [25, 94, 57, 62, 70],
'post_score': [5, 43, 23, 23, 51]}
df = pd.DataFrame(raw_data, columns = ['first_name', 'pre_score', 'mid_score', 'post_score'])
df
```
first_name pre_score mid_score post_score
0 Jason 4 25 5
1 Molly 24 94 43
2 Tina 31 57 23
3 Jake 2 62 23
4 Amy 3 70 51

Make plot

```# Setting the positions and width for the bars
pos = list(range(len(df['pre_score'])))
width = 0.25

# Plotting the bars
fig, ax = plt.subplots(figsize=(10,5))

# Create a bar with pre_score data,
# in position pos,
plt.bar(pos,
#using df['pre_score'] data,
df['pre_score'],
# of width
width,
# with alpha 0.5
alpha=0.5,
# with color
color='#EE3224',
# with label the first value in first_name
label=df['first_name'][0])

# Create a bar with mid_score data,
# in position pos + some width buffer,
plt.bar([p + width for p in pos],
#using df['mid_score'] data,
df['mid_score'],
# of width
width,
# with alpha 0.5
alpha=0.5,
# with color
color='#F78F1E',
# with label the second value in first_name
label=df['first_name'][1])

# Create a bar with post_score data,
# in position pos + some width buffer,
plt.bar([p + width*2 for p in pos],
#using df['post_score'] data,
df['post_score'],
# of width
width,
# with alpha 0.5
alpha=0.5,
# with color
color='#FFC222',
# with label the third value in first_name
label=df['first_name'][2])

# Set the y axis label
ax.set_ylabel('Score')

# Set the chart's title
ax.set_title('Test Subject Scores')

# Set the position of the x ticks
ax.set_xticks([p + 1.5 * width for p in pos])

# Set the labels for the x ticks
ax.set_xticklabels(df['first_name'])

# Setting the x-axis and y-axis limits
plt.xlim(min(pos)-width, max(pos)+width*4)
plt.ylim([0, max(df['pre_score'] + df['mid_score'] + df['post_score'])] )

# Adding the legend and showing the plot
plt.legend(['Pre Score', 'Mid Score', 'Post Score'], loc='upper left')
plt.grid()
plt.show()
```