Grouping is a kind of data aggregation operation. The grouping term is taken from a relational database. Relational database software uses the group by keyword to group similar kinds of values in a column. We can apply aggregate functions on groups such as mean, min, max, count, and sum. The pandas DataFrame also offers similar kinds of capabilities. Grouping operations are based on the split-apply-combine strategy. It first divides data into groups and applies the aggregate operation, such as mean, min, max, count, and sum, on each group and combines results from each group:
# Group By DataFrame on the basis of Continent column
df.groupby('Continent').mean()
This results in the following output:
Let's now group the DataFrames based on literacy rates as well:
# Group By DataFrame on the basis of continent and select adult literacy rate(%)
df.groupby('Continent').mean()['Adult literacy rate (%)']
This results in the...
