Creating a Pandas DataFrame from a List

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Creating a Pandas DataFrame from a List

Author：JIYIK Last Updated：2025/05/02 Views：

Pandas allows us pd.DataFrame()to create a Pandas DataFrame from a list using the from method. We can do this with single lists, multiple lists, and multidimensional lists.

Creating a Pandas DataFrame from a Single List

This is the most basic way to create a DataFrame from a single list. We simply pass the list to d.DataFrame(), and the result is a single-column Dataframe.

example:

import pandas as pd
import numpy as np

lst = ["Jay", "Raj", "Jack"]
df = pd.DataFrame(lst, columns=["Name"])

print(df)

Output:

   Name
0   Jay
1   Raj
2  Jack

Creating a Pandas DataFrame from Multiple Lists

To create a Pandas DataFrame from multiple lists, we have to use zip()the function. zip()The function returns an zipobject of type with the elements in the first position paired together, the elements in the second position paired together, and so on. Here each list acts as a different column.

example:

import pandas as pd
import numpy as np

lst1 = ["Jay", "Raj", "Jack"]
lst2 = [12, 15, 14]
df = pd.DataFrame(list(zip(lst1, lst2)), columns=["Name", "Age"])
print(df)

Output:

   Name  Age
0   Jay   12
1   Raj   15
2  Jack   14

Creating a Pandas DataFrame from a Multidimensional List

A list that contains another list is called a multidimensional list. In this case, each list nested in the main list is treated as a row of the DataFrame. The following example shows how to do it.

import pandas as pd
import numpy as np

lst = [["Jay", 12, "BBA"], ["Jack", 15, "BSc"]]
df = pd.DataFrame(lst, columns=["Name", "Age", "Course"])
print(df)

Output:

   Name  Age Course
0   Jay   12    BBA
1  Jack   15    BSc

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