%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
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 |
# input data, specifically the second and
# third rows, skipping the first column
x1 = df.ix[1, 1:]
x2 = df.ix[2, 1:]
# Create the bar labels
bar_labels = ['Pre Score', 'Mid Score', 'Post Score']
# Create a figure
fig = plt.figure(figsize=(8,6))
# Set the y position
y_pos = np.arange(len(x1))
y_pos = [x for x in y_pos]
plt.yticks(y_pos, bar_labels, fontsize=10)
# Create a horizontal bar in the position y_pos
plt.barh(y_pos,
# using x1 data
x1,
# that is centered
align='center',
# with alpha 0.4
alpha=0.4,
# and color green
color='#263F13')
# Create a horizontal bar in the position y_pos
plt.barh(y_pos,
# using NEGATIVE x2 data
-x2,
# that is centered
align='center',
# with alpha 0.4
alpha=0.4,
# and color green
color='#77A61D')
# annotation and labels
plt.xlabel('Tina\'s Score: Light Green. Molly\'s Score: Dark Green')
t = plt.title('Comparison of Molly and Tina\'s Score')
plt.ylim([-1,len(x1)+0.1])
plt.xlim([-max(x2)-10, max(x1)+10])
plt.grid()
plt.show()