When working with pandas data frames, the .loc method can be used to filter the data based on one or more conditions. Here’s how to use .loc with multiple conditions:
Suppose you have a data frame named df and you want to select only the rows where the value in column A is greater than 5 and the value in column B is less than 10.
You can achieve this using the & operator to join the two conditions:
df.loc[(df['A'] > 5) & (df['B'] < 10)]
In this example, the .loc method filters the rows of df where column A is greater than 5 and column B is less than 10.
If you want to use an “or” condition instead of “and”, you can use the | operator:
df.loc[(df['A'] > 5) | (df['B'] < 10)]
This will return the rows where either column A is greater than 5 or column B is less than 10.
You can also use other operators like ==, >=, <=, != as per your requirement.
Note that when using .loc with multiple conditions, you need to enclose each condition in parentheses and join them with the & or | operator.
