How to Create a Dataframe From Arrays in Python

October 03, 2024

To create a dataframe from arrays in Python, you can use the numpy array.

The following example shows how to create a dataframe from arrays in Python using the numpy array.

Using numpy Array

We can use the numpy array to create a dataframe.

Suppose we have the following arrays:

import pandas as pd
import numpy as np

# Define arrays
date = np.array(['01-03-2023', '01-03-2023', '01-03-2023', '01-03-2023', '02-03-2023', '02-03-2023'])
product_code = np.array(['A-101', 'A-102', 'A-103', 'B-101', 'B-102', 'B-104'])
product_name = np.array(['Laptop', 'Mobile', 'Printer', 'Keyboard', 'Scanner', 'Mouse'])
price = np.array([4500, 550, 250, 50, 350, 50])
status = np.array([1, 1, 1, 0, 1, 1])

# Create dataframe
df = pd.DataFrame({"Date": date, "Product_code": product_code, "Product_Name": product_name, "Price": price, "Status": status})

# Show dataframe
print(df)

Output: 👇️

         Date Product_code Product_Name  Price  Status
0  01-03-2023        A-101       Laptop   4500       1
1  01-03-2023        A-102       Mobile    550       1
2  01-03-2023        A-103      Printer    250       1
3  01-03-2023        B-101     Keyboard     50       0
4  02-03-2023        B-102      Scanner    350       1
5  02-03-2023        B-104        Mouse     50       1

In this example, we use the numpy array to create a dataframe df. The output shows the dataframe created from the numpy arrays.

Conclusion

We can use the numpy array to create a dataframe from arrays in Python.