Pandas is an open-source Python library. It provides us with some new data structures, such as Series and DataFrame. A pandas Series is a one-dimensional data structure. It is similar to NumPy one-dimensional array or a Python list. But, the main difference is it is labeled. And the pandas DataFrame is a two-dimensional data structure. It can contain tabular data. In this article, we will discuss how to create a Pandas DataFrame.

We can use the pandas.DataFrame() constructor to create a pandas DataFrame.

import pandas

list1 = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
df1 = pandas.DataFrame(list1)
print(df1)

df2 = pandas.DataFrame(list1, index=["Row 1", "Row 2", "Row 3"], columns=["Column 1", "Column 2", "Column 3"])
print(df2)

dict1 = {“Column 1”: [1, 2, 3], "Column 2": [4, 5, 6], "Column 3": [7, 8, 9]}
df3 = pandas.DataFrame(dict1)
print(df3)

Here, list1 is a Python list that has three rows and three columns. We are using this list to create a DataFrame df1. So, df1 contains three rows and three columns. When we print df1, it shows the following:

   0  1  2
0  1  2  3
1  4  5  6
2  7  8  9

Please note that pandas DataFrame is a …