Filtering Data with query()

When analyzing data, we often need to filter rows based on certain conditions. In addition to traditional Boolean indexing, Pandas provides a cleaner and SQL-like syntax: query().

This article uses simple examples to show how to filter data using query().

Here’s an example dataset:

import pandas as pd

data = {
    'Class': ['A', 'A', 'B', 'B', 'C', 'C'],
    'Name': ['Ming', 'Mei', 'Hua', 'Qiang', 'An', 'Jie'],
    'Gender': ['M', 'F', 'M', 'M', 'F', 'M'],
    'Score': [85, 90, 78, 82, 95, 70]
}

df = pd.DataFrame(data)
print(df)

Filter with a Single Condition

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To find students with scores above 80:

df.query('Score > 80')

Result:

Filter with Multiple Conditions

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You can combine conditions using and / or. For example, to find male students with scores above 80:

df.query('Score > 80 and Gender == "M"')

Result: