using series to filter dataframe

To filter a DataFrame using a Series, you can use the Series as a boolean mask to select the rows that meet a certain condition.

For example, suppose you have a DataFrame with columns 'Name', 'Age', and 'Gender', and a Series called 'ages' with the ages you want to filter on. You can use the Series to select only the rows where the age column matches one of the ages in the Series:

import pandas as pd

# create DataFrame
data = {'Name': ['Alice', 'Bob', 'Charlie', 'Dave'],
        'Age': [25, 30, 35, 40],
        'Gender': ['F', 'M', 'M', 'M']}
df = pd.DataFrame(data)

# create Series of ages to filter on
ages = pd.Series([25, 35])

# filter DataFrame using Series
filtered_df = df[df['Age'].isin(ages)]

print(filtered_df)

This will output:

     Name  Age Gender
0   Alice   25      F
2  Charlie  35      M