Convert DataFrame Column Values to Absolute Values

To convert DataFrame column values to absolute values:

df['column_name'] = df['column_name'].abs()

Example of Converting DataFrame Column Values to Absolute Values

To start, create a DataFrame with a column that contains negative values.

Here, the ‘price‘ column contains two negative values:

import pandas as pd

data = {'product_name': ['laptop', 'printer', 'tablet', 'desk', 'chair'],
        'price': [1200, -200, -400, 300, 150]
        }

df = pd.DataFrame(data)
print(df)

As highlighted in yellow, there are two values under the ‘price’ column which are negative:

  product_name  price
0       laptop   1200
1      printer   -200
2       tablet   -400
3         desk    300
4        chair    150

Next, add the following syntax df[‘price’] = df[‘price’].abs() in order to convert the values under the ‘price’ column to absolute values:

import pandas as pd

data = {'product_name': ['laptop', 'printer', 'tablet', 'desk', 'chair'],
        'price': [1200, -200, -400, 300, 150]
        }

df = pd.DataFrame(data)

df['price'] = df['price'].abs()
print(df)

As you can see, the values under the ‘price’ column are now in absolute terms:

  product_name  price
0       laptop   1200
1      printer    200
2       tablet    400
3         desk    300
4        chair    150

You can read more about this topic by visiting the Pandas Documentation.