In this example, we check of the variable is in a list and use if condition if present. Similarly, we can create complex conditionals. Instead we can use Panda’s apply function with lambda function. How to Create a Column Using A Condition in Pandas using apply and Lambda functionsĪctually we don’t have to rely on NumPy to create new column using condition on another column.
Gapminder = np.where(gapminder.lifeExp >= 50, True, False) # np.where assigns True if gapminder.lifeExp>=50 # Create a new column called based on the value of another column We will use NumPy’s where function on the lifeExp column to create the new Boolean column. Let us use the lifeExp column to create another column such that the new column will have True if the lifeExp >= 50 False otherwise.
How to Create a Column Using A Condition in Pandas using NumPy? Next we will use Pandas’ apply function to do the same. In this post we will see two different ways to create a column based on values of another column using conditional statements.įirst we will use NumPy’s little unknown function where to create a column in Pandas using If condition on another column’s values. Often while cleaning data, one might want to create a new variable or column based on the values of another column using conditions.
0 kommentar(er)
