Convert a NumPy array to Pandas dataframe with headers

Last Updated : 01 Oct, 2020
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To convert a numpy array to pandas dataframe, we use pandas.DataFrame() function of Python Pandas library.
Syntax: pandas.DataFrame(data=None, index=None, columns=None) Parameters: data: numpy ndarray, dict or dataframe index: index for resulting dataframe columns: column labels for resulting dataframe
Example 1 : Python3 1==
import numpy as np
import pandas as pd


arr = np.random.rand(4, 3)
print("Numpy array:")
print(arr)

# convert numpy array to dataframe
df = pd.DataFrame(arr, columns =['A', 'B', 'C'])
print("\nPandas DataFrame: ")
df
Output: numpy-array-to-dataframe-1 Example 2 : Python3 1==
import numpy as np
import pandas as pd


arr = np.random.rand(6).reshape(2, 3)
print("Numpy array:")
print(arr)

# convert numpy array to dataframe
df = pd.DataFrame(arr, columns =['C1', 'C2', 'C3'])
print("\nPandas DataFrame: ")
df
Output: numpy-araay-to-dataframe-2 Example 3 : Python3 1==
import numpy as np
import pandas as pd


arr = np.array([[1, 2], [4, 5]])
print("Numpy array:")
print(arr)

# convert numpy array to dataframe
df = pd.DataFrame(data = arr, index =["row1", "row2"], 
                  columns =["col1", "col2"])

print("\nPandas DataFrame: ")
df
Output: numpy-array-to-dataframe-3

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