To update a column based on a condition in Pandas, you can use boolean indexing. First, you create a boolean mask that specifies the condition. Then, you use this mask to select the rows that meet the condition and update the column for those rows. For example:
1. Create a boolean mask that specifies the condition:
mask = df['column_name'] == 'condition'
2. Select the rows that meet the condition using the mask:
selected_rows = df[mask]
3. Update the column for the selected rows:
selected_rows['column_name'] = new_values
4. Update the original dataframe with the changes:
df.update(selected_rows)
Note that the update() method is used to update the original dataframe with the changes made to the selected rows.