[FIXED] How to create a bar plot of the number of unique values within each group

Issue

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

## the following is the data set

gm = pd.read_csv('https://raw.githubusercontent.com/gerberl/6G7V0026-2223/main/datasets/gapminder.tsv', sep='\t')

the command that I have been using, which counts each country multiple times.

sns.countplot(x=gm.continent)
plt.show 

I can get the plot graph by making a new data frame, however there must be a way to get the graph without making a new dataframe.

The bars would be for the total number of countries in each continent, where the x-axis will be continents.

Solution

• The most direct way is to use pandas to get the number of unique countries for each continent, and then plot directly with pandas.DataFrame.plot.
  • pandas uses matplotlib as the default plotting backend, and seaborn is just an API for matplotlib.
• This answer shows how to use pd.DataFrame.pivot_table to get the number of unique values for each group.
  • gm.groupby('continent')['country'].nunique() can also be used.
• If the link to the Gapminder data no longer works, it can also be found here.

import pandas as pd

# load the dataset
gm = pd.read_csv('https://raw.githubusercontent.com/gerberl/6G7V0026-2223/main/datasets/gapminder.tsv', sep='\t')

# create a pivot table with continent and the number of unique countires
pt = gm.pivot_table(index='continent', values='country', aggfunc='nunique')

# plot the bar cart
ax = pt.plot(kind='bar', rot=0, ylabel='Number of Countires', xlabel='Continent', legend=False)

pt DataFrame

           country
continent         
Africa          52
Americas        25
Asia            33
Europe          30
Oceania          2

Answered By - Trenton McKinney