# Counting the frequency of words in a pandas dataframe

Given a pandas dataframe, we have to count the Frequency of words in a pandas dataframe.
By Pranit Sharma Last updated : September 03, 2023

Pandas is a special tool that allows us to perform complex manipulations of data effectively and efficiently. Inside pandas, we mostly deal with a dataset in the form of DataFrame. DataFrames are 2-dimensional data structures in pandas. DataFrames consist of rows, columns, and data.

## Problem statement

Suppose, we are given a DataFrame with all the columns of string type, we need to count the frequency of each column.

## Count the frequency of words in a pandas dataframe

For this purpose, you can use .split(expand=True).stack().value_counts() with the specified column whose word frequency is to be counted. The statement expand=True expands out the split elements into separate columns and .stack().value_counts() returns a Series with the values as the index and the counts as the values.

Let us understand with the help of an example,

## Python program to count the frequency of words in a pandas dataframe

# Importing pandas package
import pandas as pd

# Creating two dictionaries
d = {
'code':['A24','B13','M88','F90'],
}

# Creating DataFrame
df = pd.DataFrame(d)

# Display Original DataFrame
print("Created DataFrame:\n",df,"\n")

# Calculating the frequency of each word

# Display result
print("Result:\n",res)

## Output

The output of the above program is: