How to Get Frequency Counts of a Column in Pandas Dataframe: Pandas Tutorial

Often while working with pandas dataframe you might have a column with categorical variables, string/characters, and you want to find the frequency counts of each unique elements present in the column. Pandas’ value_counts() easily let you get the frequency counts.

Let us get started with an example from a real world data set.

Load gapminder data set

# import pandas as pd
import pandas as pd
# software carpentry url for gapminder data
gapminder_csv_url ='http://bit.ly/2cLzoxH'
# load the data with pd.read_csv
gapminder = pd.read_csv(gapminder_csv_url)

Frequency Counts of the column “continent”

Let us say we want to find the frequency counts of column ‘continent’ in the data frame. We can use pandas’ function value_counts on the column of interest. It will return NumPy array with unique items and the frequency of it.

>gapminder['continent'].value_counts()
Africa      624
Asia        396
Europe      360
Americas    300
Oceania      24

If you just want the unique values from a pandas dataframe column, it is pretty simple. Check here