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Pandas series to dataframe using series indexes as columns

Given a pandas series, we have to convert it into a dataframe using series indexes as column? By Pranit Sharma Last updated : September 30, 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.

A Series in pandas contains a single list that can store heterogeneous types of data, because of this, a series is also considered a 1-dimensional data structure.

When we analyze a series, each value can be considered as a separate row of a single column, both series and DataFrame can be created either with a list or with the help of a dictionary, in the case of series, there will be only one key in the dictionary but there may be multiple keys in case of DataFrame.

Converting pandas series to dataframe using series indexes as columns

For this purpose, we will first create a pandas Series and then we will use apply the typecasting method to it. We will typecast series into DataFrame, this method will convert the rows into columns and hence convert the series into DataFrame.

Let us understand with the help of an example,

Python program to convert pandas series to dataframe using series indexes as columns

# Importing pandas package
import pandas as pd

# Creating a dictionary
s = {'A':['This', 'is','a','series']}

# Creating series
df = pd.Series(s)

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

# framing this series
df = pd.DataFrame(s)

# Display modified DataFrame
print("Modified DataFrame:\n",df)

Output

The output of the above program is:

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