How to give multiple conditions in loc() in Pandas

How to give multiple conditions in loc() in Pandas

To give multiple conditions in the loc() function in Pandas, you can use the & (and) or | (or) operator to combine multiple conditions.

This allows you to select rows from a dataframe that meet multiple criteria, rather than just one criterion.

Example

Here's an example of using the loc() function with multiple conditions in Pandas:

import pandas as pd

# create a sample dataframe
df = pd.DataFrame({"A": [1, 2, 3, 4, 5],
                   "B": [6, 7, 8, 9, 10]})

# select rows where column A is greater than 2 and column B is less than 9
df_selected = df.loc[(df["A"] > 2) & (df["B"] < 9)]

# display the result
print(df_selected)

This will select rows from the dataframe where the value in column A is greater than 2 and the value in column B is less than 9. The & operator is used to combine the two conditions, so that only rows that meet both conditions will be selected.

The output will be:

   A  B
2  3  8

You can also use the | (or) operator to combine multiple conditions in the loc() function. For example:

# select rows where column A is greater than 2 or column B is less than 9
df_selected = df.loc[(df["A"] > 2) | (df["B"] < 9)]

# display the result
print(df_selected)

   A   B
0  1   6
1  2   7
2  3   8
3  4   9
4  5  10

This will select rows from the dataframe where the value in column A is greater than 2 or the value in column B is less than 9.