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Select rows from a Python Pandas DataFrame based on column values

Select rows from a Python Pandas DataFrame based on column values

David Y.

The ProblemJump To Solution

How can I select rows from a DataFrame in Python Pandas based on column values? In other words, what is the DataFrame equivalent of a SELECT WHERE statement in SQL?

The Solution

This can be achieved using the DataFrame’s loc property.

To select rows with a specified column value:

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my_value = 3 results = my_dataframe.loc[my_dataframe["column_name"] == my_value]

To select rows that do not match a specified column value:

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my_value = 3 results = my_dataframe.loc[my_dataframe["column_name"] != my_value]

To select rows with a column value that matches one of a list of values:

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my_list = [1, 2, 3] results = my_dataframe.loc[my_dataframe["column_name"].isin(my_list)]

To select rows with a column value that falls in a range:

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lower_limit = 1 upper_limit = 3 my_dataframe.loc[(my_dataframe["column_name"] >= lower_limit) & (my_dataframe["column_name"] <= upper_limit)]
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