You can use the following syntax to convert a NumPy array into a pandas DataFrame:
#create NumPy array data = np.array([[1, 7, 6, 5, 6], [4, 4, 4, 3, 1]]) #convert NumPy array to pandas DataFrame df = pd.DataFrame(data=data)
The following example shows how to use this syntax in practice.
Example: Convert NumPy Array to Pandas DataFrame
Suppose we have the following NumPy array:
import numpy as np #create NumPy array data = np.array([[1, 7, 6, 5, 6], [4, 4, 4, 3, 1]]) #print class of NumPy array type(data) numpy.ndarray
We can use the following syntax to convert the NumPy array into a pandas DataFrame:
import pandas as pd #convert NumPy array to pandas DataFrame df = pd.DataFrame(data=data) #print DataFrame print(df) 0 1 2 3 4 0 1 7 6 5 6 1 4 4 4 3 1 #print class of DataFrame type(df) pandas.core.frame.DataFrame
Specify Row & Column Names for Pandas DataFrame
We can also specify row names and column names for the DataFrame by using the index and columns arguments, respectively.
#convert array to DataFrame and specify rows & columns
df = pd.DataFrame(data=data, index=["r1", "r2"], columns=["A", "B", "C", "D", "E"])
#print the DataFrame
print(df)
A B C D E
r1 1 7 6 5 6
r2 4 4 4 3 1
Additional Resources
How to Add a Numpy Array to a Pandas DataFrame
How to Drop the Index Column in Pandas
Pandas: Select Rows Where Value Appears in Any Column