How to Create 2D Array from Dataframe Column in Python

To create a 2D array from a dataframe column in Python, you can use the to_numpy() function along with the reshape() function.

The following example shows how to create a 2D array from a dataframe column in Python using the to_numpy() and reshape() functions.

Using to_numpy() & reshape() Function

We can use the to_numpy() and reshape() functions to create a 2D array from a dataframe column.

Suppose we have the following dataframe:

# Import pandas library
import pandas as pd

# Create dataframe
df = pd.DataFrame({
    'Date': ['01-03-2023', '01-03-2023', '01-03-2023', '01-03-2023', '02-03-2023', '02-03-2023'],
    'Product_Code': ['A-101', 'A-102', 'A-103', 'B-101', 'B-102', 'B-104'],
    'Product_Name': ['Laptop', 'Mobile', 'Printer', 'Keyboard', 'Scanner', 'Mouse'],
    'Price': [4500, 550, 250, 50, 350, 50],
    'Status': [1, 1, 1, 0, 1, 1]
})

# Create 1D array
array_1d = df["Price"].to_numpy()

# Create 2D array
array_2d = array_1d.reshape(2, 3)

# Show 2D array
print(array_2d)

Output: 👇️

[[4500  550  250]
 [  50  350   50]]

In this example, we use the to_numpy() function to convert the “Price” column of the dataframe df to a 1D array array_1d.

We then use the reshape() function to reshape the 1D array into a 2D array array_2d. The output shows the 2D array created from the dataframe column.

Conclusion

We can use the to_numpy() function along with the reshape() function to create a 2D array from a dataframe column in Python.