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Fundamental Tools of Data Wrangling

Fundamental Tools of Data Wrangling

Name: Fundamental Tools of Data Wrangling
Rating: 4.285714285714286 (21 reviews)

This course is part of Data Wrangling with Python Specialization

Instructor: Di Wu

2,438 already enrolled

Included with

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5 modules

Gain insight into a topic and learn the fundamentals.

21 reviews

Beginner level

Recommended experience

3 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

21 reviews

Beginner level

Recommended experience

3 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

You will be able to describe the fundamentals of programming in Python.
You will be able to identify data structures for efficient organization and manipulation of data.
You will practice using NumPy and Pandas for numerical computing, data manipulation, and analysis.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

10 assignments

Taught in English

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This course is part of the Data Wrangling with Python Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 5 modules in this course

Data wrangling is a crucial step in the data analysis process, as it involves the transformation and preparation of raw data into a suitable format for analysis. The "Fundamental Tools for Data Wrangling" course is designed to provide participants with essential skills and knowledge to effectively manipulate, clean, and analyze data. Participants will be introduced to the fundamental tools commonly used in data wrangling, including Python, data structures, NumPy, and pandas. Through hands-on exercises and practical examples, participants will gain the necessary proficiency to work with various data formats and effectively prepare data for analysis.

In this course, participants will dive into the world of data manipulation using Python as the primary programming language. They will learn about data structures, such as lists, dictionaries, and arrays, and how to use them to store and organize different types of data. Furthermore, participants will explore the power of Python packages like random and math for generating and performing mathematical operations on data. They will also be introduced to NumPy, a powerful library for numerical computing, and learn how to efficiently work with multi-dimensional arrays and matrices. A significant focus of the course will be on pandas, a versatile library for data manipulation and analysis. Participants will discover various techniques to clean, reshape, and aggregate data using pandas, enabling them to derive valuable insights from messy datasets.

Module details

This week provides an introduction to the Python programming language, covering fundamental concepts and practical applications. You will gain a solid understanding of Python's syntax and semantics, enabling you to write efficient and concise code. We will also cover essential topics such as basic variables and operations, flow control structures, functions, and the utilization of external packages to enhance Python's capabilities.

What's included

4 videos8 readings3 assignments

4 videosTotal 47 minutes

Course Overview2 minutes
Python Fundamentals27 minutes
Python Functions12 minutes
Python Packages6 minutes

8 readingsTotal 301 minutes

Course Updates and Accessibility Support1 minute
Assessment Strategy30 minutes
Python Fundamentals Slides30 minutes
Python Fundamentals Practice Lab60 minutes
Python Functions Slides30 minutes
Python Functions Practice Lab60 minutes
Python Packages Slides30 minutes
Python Packages Practice Lab60 minutes

3 assignmentsTotal 90 minutes

Python Fundamentals Quiz30 minutes
Python Functions Quiz30 minutes
Python Packages Quiz30 minutes

The "Data Structures" week provides you with a comprehensive understanding of commonly used data structures for efficient organization and manipulation of data. You will explore various data structures, including strings, lists, sets, and dictionaries. Through theoretical explanations and practical examples, you will grasp the advantages of using each data structure and learn the fundamental operations associated with them.

What's included

4 videos7 readings4 assignments

4 videosTotal 53 minutes

Data Structure - List19 minutes
String16 minutes
Data Structure - Set7 minutes
Data Structure - Dictionary12 minutes

7 readingsTotal 300 minutes

List Demo30 minutes
List Practice Lab60 minutes
String Demo30 minutes
Set Demo30 minutes
Set Practice Lab60 minutes
Dictionary Demo30 minutes
Dictionary Practice Lab60 minutes

4 assignmentsTotal 120 minutes

List Quiz30 minutes
String Quiz30 minutes
Set Quiz30 minutes
Dictionary Quiz30 minutes

The "NumPy" week serves as an introduction to the fundamental concepts and practical applications of NumPy, a powerful library for numerical computing in Python. You will gain insights into the advantages of utilizing NumPy for efficient data manipulation and mathematical operations. The week will cover the underlying data structure of NumPy arrays and guide students through basic array operations, including accessing and manipulation. Moreover, you will delve into advanced operations, such as masking and filtering, to perform complex data manipulations effectively.

What's included

3 videos4 readings1 assignment

The "Pandas" week provides you with a comprehensive introduction to Pandas, a powerful and widely used library for data manipulation and analysis in Python. You will explore the advantages of using Pandas for handling structured data efficiently. The week will cover the underlying data structure of Pandas, namely DataFrames and Series, and guide you through basic data operations, including accessing and manipulation. Moreover, you will delve into advanced data manipulations, such as masking, filtering, aggregating, pivot tables, and more, to effectively analyze and transform datasets.

What's included

3 videos4 readings1 assignment

The "Case Study" week offers you the opportunity to apply the knowledge you have gained throughout the course in a practical simulation case study. Through hands-on exercises and real-world scenarios, you will use Python and relevant packages to create a dummy dataset, mimicking a real dataset they might encounter in data analysis or scientific research. Throughout the case study, you will face challenges commonly encountered in real-world data analysis and will be encouraged to employ critical thinking and problem-solving skills to overcome them. This practical exercise will not only consolidate their understanding of Python and relevant packages but also foster a deeper appreciation for the importance of data preparation and analysis in various domains.