Data Cleaning and Preprocessing with pandas

Introducing you to the fundamentals of the quintessential Python data analysis library, pandas, and its core data structures – the Series and DataFrame objects.

with Martin Ganchev

Course Overview

pandas is one of today’s most celebrated data analysis libraries. A favorite of many, its versatile functionalities can be leveraged for manipulation of many types of data - numeric, text, Boolean, and more. That’s one of the features that make pandas the go-to choice for analysts, especially during the data cleaning and preprocessing stages. pandas is built on NumPy and takes advantage of its computational power and abilities. But what sets pandas apart is its ability to operate with data in an easy-to-use way, allowing you to focus almost entirely on your analytic task. In this course, you will learn how to work with this powerful Python library and its core data structures – the pandas Series and DataFrames.

27 High Quality Lessons

3 Practical Tasks

2 Hours of Video

Certificate of Achievement

Skills you will gain

data analysisdata processingprogrammingpython

What You'll Learn

This course introduces you to one of the most widely used data analysis libraries – pandas. With pandas you’ll be able to solve your analytic tasks in an easy and professional way!

Develop a basic understanding of the pandas library

Navigate through the pandas documentation

Practice with fundamental programming tools

Study collecting, cleaning, and preprocessing data

Work with pandas Series and DataFrames

Practice data selection with pandas

Curriculum

pandas - Basics

15 Lesson 82 Min

Introduction to the pandas Library Free Installing and Running pandas Free Introduction to pandas Series Free Working with Attributes in Python Free Using an Index in pandas Free Label-based vs Position-based Indexing Free More on Working with Indices in Python Free Using Methods in Python - Part I Free Using Methods in Python - Part II Free Parameters vs Arguments Free The pandas Documentation Free Introduction to pandas DataFrames Free Creating DataFrames from Scratch - Part I Creating DataFrames from Scratch - Part II Additional Notes on Using DataFrames
Data Cleaning and Data Preprocessing

1 Lesson 5 Min

Data Cleaning and Data Preprocessing
pandas Series

5 Lesson 21 Min

.unique(), .nunique() Converting Series into Arrays .sort_values() Attribute and Method Chaining .sort_index()
pandas DataFrames

6 Lesson 38 Min

A Revision to pandas DataFrames Common Attributes for Working with DataFrames Data Selection in pandas DataFrames Data Selection - Indexing Data with .iloc[] Data Selection - Indexing Data with .loc[] A Few Comments on Using .loc[] and .iloc[]

“In this course, I will help you streamline the data cleaning and data preprocessing stages of analysis with pandas – the go-to library for data science and analytics professionals. By the end of this brief practical training, you will be able to handle the pandas Series object and DataFrames with confidence and ease.”

Martin Ganchev

Worked at European Commission

Courses You May Like

100 lessons 9 hours

The Complete Data Visualization Course with Python, R, Tableau, and Excel

with Elitsa Kaloyanova

174 lessons 6 hours

Introduction to R Programming

with Simona Dobreva, Iliya Valchanov

68 lessons 7 hours

Data Preprocessing with NumPy

with Viktor Mehandzhiyski

242 lessons 8 hours

with Martin Ganchev, Vladimir Saev

128 lessons 11 hours

Python Programmer Bootcamp

with Giles McMullen-Klein

9 lessons 1 hours

Introduction to Jupyter

with Martin Ganchev

20 lessons 1 hours

with Martin Ganchev

12 lessons 1 hours

with Giles McMullen-Klein

40 lessons 2 hours

Introduction to Python

with Martin Ganchev

46 lessons 2 hours

Dates and Times in Python

with Ivan Manov, Martin Ganchev

Data Cleaning and Preprocessing with pandas

with Martin Ganchev