# Create a figure with a single subplot
f, ax = plt.subplots(1, figsize=(10,5))
# Set bar width at 1
bar_width = 1
# positions of the left bar-boundaries
bar_l = [i for i in range(len(df['pre_score']))]
# positions of the x-axis ticks (center of the bars as bar labels)
tick_pos = [i+(bar_width/2) for i in bar_l]
# Create the total score for each participant
totals = [i+j+k for i,j,k in zip(df['pre_score'], df['mid_score'], df['post_score'])]
# Create the percentage of the total score the pre_score value for each participant was
pre_rel = [i / j * 100 for i,j in zip(df['pre_score'], totals)]
# Create the percentage of the total score the mid_score value for each participant was
mid_rel = [i / j * 100 for i,j in zip(df['mid_score'], totals)]
# Create the percentage of the total score the post_score value for each participant was
post_rel = [i / j * 100 for i,j in zip(df['post_score'], totals)]
# Create a bar chart in position bar_1
ax.bar(bar_l,
# using pre_rel data
pre_rel,
# labeled
label='Pre Score',
# with alpha
alpha=0.9,
# with color
color='#019600',
# with bar width
width=bar_width,
# with border color
edgecolor='white'
)
# Create a bar chart in position bar_1
ax.bar(bar_l,
# using mid_rel data
mid_rel,
# with pre_rel
bottom=pre_rel,
# labeled
label='Mid Score',
# with alpha
alpha=0.9,
# with color
color='#3C5F5A',
# with bar width
width=bar_width,
# with border color
edgecolor='white'
)
# Create a bar chart in position bar_1
ax.bar(bar_l,
# using post_rel data
post_rel,
# with pre_rel and mid_rel on bottom
bottom=[i+j for i,j in zip(pre_rel, mid_rel)],
# labeled
label='Post Score',
# with alpha
alpha=0.9,
# with color
color='#219AD8',
# with bar width
width=bar_width,
# with border color
edgecolor='white'
)
# Set the ticks to be first names
plt.xticks(tick_pos, df['first_name'])
ax.set_ylabel("Percentage")
ax.set_xlabel("")
# Let the borders of the graphic
plt.xlim([min(tick_pos)-bar_width, max(tick_pos)+bar_width])
plt.ylim(-10, 110)
# rotate axis labels
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')
# shot plot
plt.show()