Create pandas DataFrame from NumPy Array in Python (2 Examples)

In this tutorial you’ll learn how to create a pandas DataFrame from a NumPy array in the Python programming language.

Setting up the Examples

import numpy as np                      # Load NumPy library
npa = np.array([['a', 'b', 'c'],        # Constructing a NumPy array
                ['d', 'e', 'f'],
                ['g', 'h', 'i'],
                ['j', 'k', 'l'],
                ['m', 'n', 'o']])
# [['a' 'b' 'c']
#  ['d' 'e' 'f']
#  ['g' 'h' 'i']
#  ['j' 'k' 'l']
#  ['m' 'n' 'o']]

Example 1: Creating a pandas DataFrame from the Rows of a NumPy Array

import pandas as pd                     # Load pandas
pdf1 = pd.DataFrame({'A': npa[0, :],    # Constructing a pandas DataFrame
                     'B': npa[1, :],
                     'C': npa[2, :],
                     'D': npa[3, :],
                     'E': npa[4, :]})
#    A  B  C  D  E
# 0  a  d  g  j  m
# 1  b  e  h  k  n
# 2  c  f  i  l  o

Example 2: Creating a pandas DataFrame from the Columns of a NumPy Array

pdf2 = pd.DataFrame({'A': npa[:, 0],    # Constructing a pandas DataFrame
                     'B': npa[:, 1],
                     'C': npa[:, 2]})
#    A  B  C
# 0  a  b  c
# 1  d  e  f
# 2  g  h  i
# 3  j  k  l
# 4  m  n  o

Related Articles & Further Resources

You may find some further Python programming tutorials on topics such as data conversion and lists in the following list:

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