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Make a Pandas DataFrame with two-dimensional list | Python

Last Updated : 08 May, 2024
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In this discussion, we will illustrate the process of creating a Pandas DataFrame with the two-dimensional list. Python is widely recognized for its effectiveness in data analysis, thanks to its robust ecosystem of data-centric packages. Among these packages, Pandas stands out, streamlining the import and analysis of data. There are various methods to achieve a Pandas DataFrame, and in this article, we will focus on creating one using a two-dimensional list.

Pandas DataFrame with Two-dimensional List

There are several methods for creating a Pandas DataFrame with the two-dimensional list. In this context, we will explain some commonly used approaches.

  • Using pd.DataFrame()
  • Using pd.DataFrame.from_records()
  • Using pd.DataFrame.from_dict()
  • Using Specifying Data Types

Create Pandas Dataframe from 2D List using pd.DataFrame()

In this example below code creates a Pandas DataFrame (‘df’) from a two-dimensional list (‘lst’) with specified column names (‘Tag’ and ‘number’) and prints the resulting DataFrame.

# import pandas as pd 
import pandas as pd  
    
# List1  
lst = [['Geek', 25], ['is', 30], 
       ['for', 26], ['Geeksforgeeks', 22]] 

# creating df object with columns specified    
df = pd.DataFrame(lst, columns =['Tag', 'number']) 
print(df )

Output :

             Tag         number
0 Geek 25
1 is 30
2 for 26
3 Geeksforgeeks 22

Create Pandas Dataframe from 2D List using pd.DataFrame.from_records()

In this example below code uses the pandas library in Python to create a DataFrame from a two-dimensional list (data). The DataFrame has columns with names ‘Name’, ‘Age’, and ‘Occupation’. The print(df) statement will display the DataFrame. Here’s the expected output:

import pandas as pd

# Two-dimensional list
data = [['Geek1', 28, 'Analyst'],
        ['Geek2', 35, 'Manager'],
        ['Geek3', 29, 'Developer']]

# Column names
columns = ['Name', 'Age', 'Occupation']

# Creating DataFrame using pd.DataFrame.from_records()
df = pd.DataFrame.from_records(data, columns=columns)

# Displaying the DataFrame
print(df)

Output:

    Name  Age Occupation
0 Geek1 28 Analyst
1 Geek2 35 Manager
2 Geek3 29 Developer

Create Pandas Dataframe from 2D List using pd.DataFrame.from_dict()

In this example below code uses the pandas library in Python to create a DataFrame from a two-dimensional list (data). Instead of using pd.DataFrame.from_records(), this time it uses pd.DataFrame.from_dict() along with the zip function to transpose the data.

import pandas as pd

# Two-dimensional list
data = [['Geek1', 26, 'Scientist'],
        ['Geek2', 31, 'Researcher'],
        ['Geek3', 24, 'Engineer']]

# Column names
columns = ['Name', 'Age', 'Occupation']

# Creating DataFrame using pd.DataFrame.from_dict()
df = pd.DataFrame.from_dict(dict(zip(columns, zip(*data))))

# Displaying the DataFrame
print(df)

Output:

    Name  Age    Occupation
0 Geek1 26 Scientist
1 Geek2 31 Researcher
2 Geek3 24 Engineer

Create Pandas Dataframe from 2D List using Specifying Data Types

In this example below code uses the pandas library in Python to create a DataFrame from a two-dimensional list (data). The DataFrame has columns with names ‘FName’, ‘LName’, and ‘Age’.

import pandas as pd

# Two-dimensional list
data = [['Geek1', 'Reacher', 25],
        ['Geek2', 'Pete', 30],
        ['Geek3', 'Wilson', 26],
        ['Geek4', 'Williams', 22]]

# Column names
columns = ['FName', 'LName', 'Age']

# Creating DataFrame with specified data types
df = pd.DataFrame(data, columns=columns)

# Displaying the DataFrame
print(df)

Output :

  FName     LName   Age
0 Geek1 Reacher 25
1 Geek2 Pete 30
2 Geek3 Wilson 26
3 Geek4 Williams 22


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