Make a Pandas DataFrame with twodimensional list | Python (original) (raw)

Make a Pandas DataFrame with two-dimensional list | Python

Last Updated : 08 May, 2024

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.

Python `

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:

Python `

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.

Python `

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’.

Python `

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

Make a Pandas DataFrame with twodimensional list | Python (original) (raw)