Gain insights into Pandas' powerful tools for data analysis. Learn about Series, DataFrames, and optimize performance for data operations, filtering, and file uploads in data science and machine learning.

Pandas is a very popular Python library that provides powerful, flexible and high-performance tools to process data.

If you’re looking to get into data science, machine learning, or you just want to brush up on your analytics skills, then look no further. In this course, you’ll learn how to process and analyze data with Pandas. 

You’ll start out by covering the basic data structures in Pandas: Series and dataframes. In the latter half of the course, you’ll learn how to perform operations on different data structures, and how to optimize performance for file uploads, data filtering, and more.

Data Analysis & Processing with Pandas

## Challenge - Drop duplicated rows on `SN` column and return the total price of male group

In this task, you should do the following things:

- Load the data to the DataFrame object.
- Drop those duplicated rows based on `SN` columns, but keep the last one.
- Group the data by the `Gender` column.
- Get the total price of `Male` group.

You should return one value.

# Challenge - Drop duplicated rows on `SN` column and return the total price of male group

In this task, you should do the following things:

- Load the data to the DataFrame object.
- Drop those duplicated rows based on `SN` columns, but keep the last one.
- Group the data by the `Gender` column.
- Get the total price of `Male` group.

You should return one value.

In this challenge, you will solve problems related to Series, such as drop duplicated rows.

Introduction

Basic Operations on DataFrames

Other topics

Improve performance

Challenge - Drop Duplicated Rows on SN