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.