Convert a NumPy array to Pandas dataframe with headers
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 :
import numpy as npimport pandas as pd arr = np.random.rand(4, 3)print("Numpy array:")print(arr) # convert numpy array to dataframedf = pd.DataFrame(arr, columns =['A', 'B', 'C'])print("\nPandas DataFrame: ")df |
Output:
Example 2 :
import numpy as npimport pandas as pd arr = np.random.rand(6).reshape(2, 3)print("Numpy array:")print(arr) # convert numpy array to dataframedf = pd.DataFrame(arr, columns =['C1', 'C2', 'C3'])print("\nPandas DataFrame: ")df |
Output:
Example 3 :
import numpy as npimport pandas as pd arr = np.array([[1, 2], [4, 5]])print("Numpy array:")print(arr) # convert numpy array to dataframedf = pd.DataFrame(data = arr, index =["row1", "row2"], columns =["col1", "col2"]) print("\nPandas DataFrame: ")df |
Output:
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