Unlock the Power of Pandas: Mastering the between() Method

Understanding the between() Method

The between() method takes three arguments: left, right, and inclusive. The left and right arguments define the lower and upper boundaries of the range, respectively. The inclusive argument, which is optional, specifies whether the boundaries are included in the filter.

Unleashing the Power of between()

The between() method returns a boolean Series of the same length as the input Series, indicating whether each element falls within the specified range.

Filtering Values Within a Range

Suppose we have a Series of temperatures, and we want to find the values between 20 and 30 degrees (inclusive). By using the between() method, we can create a boolean Series that indicates which temperatures fall within this range. Then, we can use this boolean Series to filter the original temperatures, resulting in a new Series containing only the values within the specified range.

import pandas as pd

temperatures = pd.Series([15, 25, 30, 35, 40])
filtered_temperatures = temperatures[temperatures.between(20, 30, inclusive=True)]
print(filtered_temperatures)

Filtering Dates with Ease

We can also use the between() method to filter dates. For instance, if we have a Series of dates from January 1 to January 10, 2023, we can use the between() method to select dates between January 4 and January 7, 2023, inclusive.

import pandas as pd

dates = pd.date_range('2023-01-01', '2023-01-10')
filtered_dates = dates[dates.to_series().between('2023-01-04', '2023-01-07', inclusive=True)]
print(filtered_dates)

Excluding Boundaries with Ease

What if we want to exclude the boundaries from our filter? No problem! By setting the inclusive argument to ‘neither’, we can select numbers between 3 and 8, excluding the boundaries themselves.

import pandas as pd

numbers = pd.Series([1, 2, 3, 4, 5, 6, 7, 8, 9])
filtered_numbers = numbers[numbers.between(3, 8, inclusive='neither')]
print(filtered_numbers)

Filtering String Values with Precision

The between() method can even be used to filter string values. For example, if we have a Series of fruit names, we can use the between() method to select fruit names that are alphabetically between banana and date (inclusive).

import pandas as pd

fruits = pd.Series(['apple', 'banana', 'cherry', 'date', 'elderberry'])
filtered_fruits = fruits[fruits.between('banana', 'date', inclusive=True)]
print(filtered_fruits)

By mastering the between() method, you’ll be able to extract the data you need with precision and ease, unlocking new insights and possibilities in your data analysis journey.