Make a Pandas DataFrame with two-dimensional list | Python

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.

Python3

# 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:

Python3

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.

Python3

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’. The specified data types for all columns are set to float using the dtype parameter.

Python3

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, dtype=float)

# Displaying the DataFrame
print(df)

Output :

  FName     LName   Age
0  Geek1   Reacher  25.0
1  Geek2      Pete  30.0
2  Geek3    Wilson  26.0
3  Geek4  Williams  22.0