How to Select DataFrame Rows Between Two Values in Python with pandas?

Selecting Rows in a DataFrame between Two Values with Python's pandas

When working with data analysis frameworks like pandas, it's often necessary to filter rows based on specific criteria. One common task is to select rows where a particular column falls within a specified range of values.

In your case, you're attempting to filter a DataFrame (df) to include rows with closing_price values between 99 and 101. However, you're encountering the error:

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

This error stems from the expression you're using for row selection:

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

To address this error, you can take advantage of the between method provided by pandas. This method allows you to filter a DataFrame based on whether a specified column satisfies a particular range.

Here's how you can revise your code using between:

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

In this modified code:

• df['closing_price'].between(99, 101) creates a Boolean Series that identifies rows where closing_price values fall between 99 and 101 (inclusive).
• df[ filters the original DataFrame (df) based on the Boolean Series generated by between. Only rows with True values in the Boolean Series are included in the filtered DataFrame.

This approach resolves the ambiguity issue and efficiently selects rows within the specified range.

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