Create barplot from string data using groupby and multiple columns in pandas dataframe

Question

I'd like to make a bar plot in python with multiple x-categories from counts of data either "yes" or "no". I've started on some code but I believe the track I'm on in a slow way of getting to the solution I want. I'd be fine with a solution that uses either seaborn, Matplotlib, or pandas but not Bokeh because I'd like to make publication-quality figures that scale.

Ultimately what I want is:

• bar plot with the categories "canoe", "cruise", "kayak" and "ship" on the x-axis
• grouped-by "color", so either Green or Red
• showing the proportion of "yes" responses: so number of yes rows divided by the count of "red" and "greens" which in this case is 4 red and 4 green, but that could change.

Here's the dataset I'm working with:

import pandas as pd
data = [{'ship': 'Yes','canoe': 'Yes', 'cruise': 'Yes', 'kayak': 'No','color': 'Red'},{'ship': 'Yes', 'cruise': 'Yes', 'kayak': 'Yes','canoe': 'No','color': 'Green'},{'ship': 'Yes', 'cruise': 'Yes', 'kayak': 'No','canoe': 'No','color': 'Green'},{'ship': 'Yes', 'cruise': 'Yes', 'kayak': 'No','canoe': 'No','color': 'Red'},{'ship': 'Yes', 'cruise': 'Yes', 'kayak': 'Yes','canoe': 'No','color': 'Red'},{'ship': 'No', 'cruise': 'Yes', 'kayak': 'No','canoe': 'Yes','color': 'Green'},{'ship': 'No', 'cruise': 'No', 'kayak': 'No','canoe': 'No','color': 'Green'},{'ship': 'No', 'cruise': 'No', 'kayak': 'No','canoe': 'No','color': 'Red'}]
df = pd.DataFrame(data)

This is what I've started with:

print(df['color'].value_counts())

red = 4 # there must be a better way to code this rather than manually. Perhaps using len()?
green = 4

# get count per type
ca = df['canoe'].value_counts()
cr = df['cruise'].value_counts()
ka = df['kayak'].value_counts()
sh = df['ship'].value_counts()
print(ca, cr, ka, sh)

# group by color
cac = df.groupby(['canoe','color'])
crc = df.groupby(['cruise','color'])
kac = df.groupby(['kayak','color'])
shc = df.groupby(['ship','color'])

# make plots 
cac2 = cac['color'].value_counts().unstack()
cac2.plot(kind='bar', title = 'Canoe by color')

But really what I want is all of the x-categories to be on one plot, only showing the result for "Yes" responses, and taken as the proportion of "Yes" rather than just counts. Help?

Answer 1

Not exactly sure if I understand the question correctly. It looks like it would make more sense to look at the proportion of answers per boat type and color.

import matplotlib.pyplot as plt
import pandas as pd
data = [{'ship': 'Yes','canoe': 'Yes', 'cruise': 'Yes', 'kayak': 'No','color': 'Red'},{'ship': 'Yes', 'cruise': 'Yes', 'kayak': 'Yes','canoe': 'No','color': 'Green'},{'ship': 'Yes', 'cruise': 'Yes', 'kayak': 'No','canoe': 'No','color': 'Green'},{'ship': 'Yes', 'cruise': 'Yes', 'kayak': 'No','canoe': 'No','color': 'Red'},{'ship': 'Yes', 'cruise': 'Yes', 'kayak': 'Yes','canoe': 'No','color': 'Red'},{'ship': 'No', 'cruise': 'Yes', 'kayak': 'No','canoe': 'Yes','color': 'Green'},{'ship': 'No', 'cruise': 'No', 'kayak': 'No','canoe': 'No','color': 'Green'},{'ship': 'No', 'cruise': 'No', 'kayak': 'No','canoe': 'No','color': 'Red'}]
df = pd.DataFrame(data)

ax = df.replace(["Yes","No"],[1,0]).groupby("color").mean().transpose().plot.bar(color=["g","r"])
ax.set_title('Proportion "Yes" answers per of boat type and color')
plt.show()

This means e.g. that 25% of all green canoes answered "yes".