Day 23 | Series between() Method With DataFrame | Python Pandas Tutorial | Exploratory Data Analysis

Welcome to another insightful session on our Pandas DataFrame playlist!

In this video, we delve into the powerful between() method within the Pandas library, geared towards fine-tuning our data filtering skills.

Our main goal today is to explore how this method seamlessly integrates with DataFrames to extract valuable insights from our dataset.

We kick off the session by loading our dataset using the head() method to gain a quick overview of its structure.

Next, we dive straight into the between() method, which allows us to filter data within a specified range. Through detailed code explanations and practical examples, we demonstrate how to apply this method to the 'calories' column of our dataset, effectively isolating data points falling within a certain range.

By leveraging the between() method in conjunction with other DataFrame functionalities, such as shape() and sample(), we showcase its versatility in addressing various data filtering requirements.

Whether it's selecting specific rows or sampling a subset of our dataset, the between() method proves to be a valuable asset in our data manipulation toolkit.

Join us on this journey as we unravel the intricacies of Pandas DataFrames and empower ourselves with advanced filtering techniques.

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Timestamp:
00:00 : Introduction of Series between() Method with Dataframe
02:29 : Applying Series between() Method to the 'Calories' column
05:52 : Using boolean mask to extract from original Dataframe
06:52 : Samples from extracted dataframe
08:00 : End Note

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