How to Filter Rows Based on Value Range in a DataFrame Without Ambiguous Truth Values?

Selecting Rows Based on Value Range in a DataFrame

When working with DataFrames, it can be necessary to filter rows based on a specific range of values in a particular column. For instance, consider a DataFrame named df containing a column closing_price. To extract rows where the values in closing_price fall between 99 and 101, the following code is commonly utilized:

df[99 <= df['closing_price'] <= 101]

However, this code may trigger a ValueError indicating "ambiguous truth value of a Series." This error occurs because the comparison results in a Series of boolean values, and attempting to use this directly for row selection can cause the ambiguity.

Fortunately, there is a more suitable method to achieve this filtering without resorting to loops. Here is the corrected code using Series.between():

df[df['closing_price'].between(99, 101)]

Series.between() provides a straightforward way to check if values in a Series fall within a specified range. This method takes two arguments: the lower bound and the upper bound. In the example above, we provide 99 and 101 as the lower and upper bounds, respectively, to select rows where closing_price is between these values.

This method effectively resolves the ambiguity issue by returning a Series of boolean values that explicitly indicate whether each row meets the criteria. These boolean values are then used to filter and select the desired rows from the DataFrame.

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