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Pandas: How to change value based on condition
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3 min readOct 17, 2021
The values in a DataFrame column can be changed based on a conditional expression. In this tutorial, we will go through several ways in which you create Pandas conditional columns.
Loading a Sample DataFrame
import pandas as pddata = {'Stock': ['AAPL', 'IBM', 'MSFT', 'WMT'],
'Price': [144.8, 141.61, 304.21, 139.5],
'PE': [25, 21, 39, 16],
'TradingExchange': ['NASDAQ', 'NYSE', 'NASDAQ', 'NYSE']}df = pd.DataFrame(data)print(df)
Method1: Using Pandas loc to Create Conditional Column
Pandas’ loc can create a boolean mask, based on condition. It can either just be selecting rows and columns, or it can be used to filter dataframes.
Syntax
example_df.loc[example_df["column_name1"] condition, "column_name2"] = value- column_name1 is the column to evaluate;
- column_name2 is the column to create or change, it could be the same as column_name1
