We may earn an affiliate commission when you visit our partners.

Data Analysis Using Python

This course provides an introduction to basic data science techniques using Python. Students are introduced to core concepts like Data Frames and joining data, and learn how to use data analysis libraries like pandas, numpy, and matplotlib. This course provides an overview of loading, inspecting, and querying real-world data, and how to answer basic questions about that data. Students will gain skills in data aggregation and summarization, as well as basic data visualization.

Enroll now

Or subscribe to Coursera Plus

And get unlimited access to Coursera

Three deals to help you save

We found three deals and offers that may be relevant to this course.

Save money when you learn. All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

Valid until December 12

Annual Subscription Savings

Unlock programs from Google, Microsoft, and IBM and join 77% of learners who reported positive career outcomes.

Only $239!

Valid for a limited time only

Future-proof your career

Access O'Reilly books, live events, courses, and more. Save with an annual subscription.

Take

15%

off

What's inside

Syllabus

Module 1 : Loading, Querying, & Filtering Data Using the csv Module

This first module provides students with an overview of loading, inspecting, and exploring data using Python's simple csv library. To get started, this module includes a brief overview of Jupyter Notebook and a concise review of basic Python, including data structures, loops, and functions. This module showcases to the students an in-depth analysis of data stored in a .csv file, including basic querying, approaches for dealing with data errors, and how to filter and sort data based on a variety of criteria.

Module 2 : Loading, Querying, Joining & Filtering Data Using pandas

In this module, students are introduced to core concepts like the Data Frame and joining data. Students will get experience using pandas, an industry-standard data analysis library, to load and query real-world data and to answer questions about that data. This module demonstrates how to do advanced filtering and indexing, slice subsets of data, restrict data attributes in query results, and do basic computations over the data. Includes how to build a simple recommendation system, and approaches for cleaning data, dealing with missing values, and creating new data.

Module 3 : Summarizing & Visualizing Data

This module takes data analysis a step further by providing an overview of the process of aggregating, summarizing, and visualizing data. Students are introduced to the concept of grouping and indexing data, and how to display results in a pivot table using pandas. This module also demonstrates how to prepare and visualize data using a histogram and scatterplot in Jupyter Notebook. Students will gain skills in data aggregation and summarization, as well as basic data visualization. In addition, students will get experience using data analysis libraries like numpy and matplotlib.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides hands-on experience with data analysis tools like pandas, numpy, and matplotlib, which is standard practice in industry

Develops a strong foundation in core data science techniques and concepts for novices

Builds skills in data aggregation, summarization, and visualization, which are highly relevant to data analysis

Taught by instructors like Brandon Krakowsky who are recognized for their expertise in data science

Examines real-world data analysis through examples and exercises

Advisable to have basic Python knowledge before beginning this course

Save this course

Save Data Analysis Using Python to your list so you can find it easily later:

Save

Reviews summary

Comprehensive python course for data analysis

learners say this course provides a strong foundation in Python for data analysis. The course is engaging and well-structured, and the assignments help learners apply concepts in practical scenarios. It covers topics such as Pandas, NumPy, Matplotlib, and data summarization, with hands-on exercises and a helpful PDF of slides and examples.

TAs and discussion forums provide support to learners.

"The supporting tutors are very responsive !"

"My only complaint is that the auto-grading sometimes doesn't consider that the order of completion may vary while the final results are effectively the same."

"The course staff replying that the answers were accepted."

Assignments are generally well-written and provide clear instructions.

"The programming assignments are frustrating because they are harder than any of the examples given and require you to know the material well enough to apply it to something else."

"Putting aside the usual issues with Jupyter Notebooks that people run into (not running cells in the correct order, etc.), I find that I had tremendous difficulty with a few of the assignments and those issues were not with my code."

"I would run the cells and have my answers get rejected."

Brandon Krakowsky is praised for his clear and concise teaching style.

"The instructor, Brandon Krakowsky, is excellent."

"His instructions are clear and descriptive."

"He also seems to know when to repeat explanations or specific details."

Thorough coverage of Pandas for data manipulation.

"This was a great course for focusing on pandas, plus some numpy and matplotlib."

"All the hands-on problem solving really deepened by knowledge of these python libraries."

"This course covers many areas of data analysis using the Python language."

Engaging videos and hands-on exercises.

"Video lectures were split() into short fragments which I enjoyed very much."

"Assignments are frustrating because they are harder than any of the examples given and require you to know the material well enough to apply it to something else."

"Lots of practice exercises on offer."

Covers key data analysis concepts and libraries.

"Covers many areas of data analysis using the Python language."

"Excellent introduction to the world of data analysis."

"Great furthering of development from the Intro to Python course that precedes it."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Analysis Using Python with these activities:

Review previous math concepts related to data science

Show steps

Enhance your understanding of data science by refreshing your knowledge of relevant mathematical concepts.

Browse courses on Statistics

Show steps

Review online resources or textbooks on statistics and linear algebra.
Focus on concepts such as probability, distributions, and matrix operations.

Refresh knowledge of programming fundamentals

Show steps

Review basic programming concepts such as data types, control flow, and functions to strengthen your foundation for data science.

Browse courses on Python

Show steps

Review online tutorials or textbooks on Python basics.
Complete practice exercises or code challenges to reinforce your understanding.

Explore a book on data science

Show steps

Gain insights from experts by reading a book specifically dedicated to data analysis using Python.

View Python for Data Analysis on Amazon

Show steps

Read selected chapters or sections relevant to the course material.
Take notes or summarize key concepts to enhance comprehension.

Ten other activities

Expand to see all activities and additional details

Show all 13 activities

Review of Basic Python Concepts

Show steps

Review basic Python concepts to strengthen your foundation for data science.

Browse courses on Python Basics

Show steps

Revisit data structures (e.g., lists, dictionaries).
Practice using loops and functions.

Join a study group or online forum for data science

Show steps

Engage with peers, share knowledge, and get support by actively participating in study groups or online forums.

Show steps

Find or create a study group with fellow students or individuals interested in data science.
Set regular meeting times to discuss course material, share resources, and work on problems together.
Be an active participant by contributing ideas, asking questions, and providing support.

Practice Loading and Querying Data

Show steps

Practice loading and querying data to improve your understanding of Python's csv library and basic data analysis techniques.

Browse courses on Loading Data

Show steps

Load a CSV file into a DataFrame.
Query the DataFrame using basic operators (e.g., ==, !=, >, <).
Filter the DataFrame based on specific criteria.
Sort the DataFrame by one or more columns.

Tutorial on Pandas for Data Manipulation

Show steps

Follow a tutorial to enhance your skills in data manipulation using the pandas library.

Browse courses on Data Manipulation

Show steps

Follow a guided tutorial on using pandas for data manipulation.
Apply the techniques learned in the tutorial to your own data analysis project.

Solve data analysis practice problems

Show steps

Strengthen your problem-solving skills and apply course concepts by working through practice problems.

Browse courses on Data Manipulation

Show steps

Find online resources or textbooks with data analysis practice problems.
Solve problems independently, focusing on understanding the approach and implementation.
Review solutions or consult with peers to verify your understanding.

Exercises on Data Aggregation and Summarization

Show steps

Solve exercises to strengthen your skills in data aggregation and summarization.

Browse courses on Data Aggregation

Show steps

Group data by one or more columns.
Calculate summary statistics (e.g., mean, median, standard deviation).
Create pivot tables to summarize data.
Visualize the summarized data using histograms or scatterplots.

Follow online tutorials on specific data science techniques

Show steps

Expand your knowledge and explore specific techniques by following guided tutorials that provide step-by-step instructions.

Browse courses on Data Cleaning

Show steps

Identify specific areas or techniques you want to enhance.
Find reputable online tutorials or courses that align with your learning goals.
Follow the tutorials carefully, taking notes and experimenting with the code.

Data Visualization Project

Show steps

Create a data visualization project to demonstrate your proficiency in data analysis and visualization.

Browse courses on Data Visualization

Show steps

Collect and clean a dataset.
Explore the data and identify trends or patterns.
Choose appropriate visualizations to represent the data.
Create visualizations using Matplotlib.
Present your findings in a clear and concise manner.

Develop a mini data analysis project

Show steps

Apply your skills to a practical project, reinforcing your understanding of the data analysis process.

Browse courses on Data Visualization

Show steps

Define a small-scale data analysis project that interests you.
Gather and explore the necessary data.
Analyze the data, draw insights, and prepare visualizations.
Present your findings in a clear and concise manner.

Become a mentor or tutor for junior data science learners

Show steps

Reinforce your understanding by sharing your knowledge and guiding others in their data science journey.

Show steps

Offer your services as a mentor or tutor to students or individuals who are new to data science.
Share your knowledge, provide guidance, and answer questions to support their learning.
Reflect on your own understanding as you explain concepts and assist others.

Career center

Learners who complete Data Analysis Using Python will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts analyze and interpret data to help businesses make informed decisions. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use their knowledge of data analysis and machine learning to solve business problems. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the programming skills you need to build machine learning models.

See salaries and explore the career path for Data Scientist

Statistician

Statisticians use their knowledge of statistics to collect, analyze, and interpret data. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Statistician

Market Researcher

Market Researchers use their knowledge of data analysis to understand consumer behavior. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Market Researcher

Data Engineer

Data Engineers design and build the systems that store and process data. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the programming skills you need to build data pipelines.

See salaries and explore the career path for Data Engineer

Financial Analyst

Financial Analysts use their knowledge of data analysis to evaluate investments. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Financial Analyst

Business Analyst

Business Analysts use their knowledge of data analysis to help businesses improve their operations. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Business Analyst

Data Visualization Analyst

Data Visualization Analysts use their knowledge of data analysis to create visual representations of data. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Data Visualization Analyst

Data Journalist

Data Journalists use their knowledge of data analysis to tell stories with data. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the writing skills you need to create clear and concise stories.

See salaries and explore the career path for Data Journalist

Operations Research Analyst

Operations Research Analysts use their knowledge of data analysis to optimize business processes. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Operations Research Analyst

Social Media Analyst

Social Media Analysts use their knowledge of data analysis to track and measure the effectiveness of social media campaigns. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Social Media Analyst

Software Tester

Software Testers use their knowledge of data analysis to find and fix bugs in software. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Software Tester

Quality Assurance Analyst

Quality Assurance Analysts use their knowledge of data analysis to ensure that products and services meet quality standards. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Quality Assurance Analyst

Web Analyst

Web Analysts use their knowledge of data analysis to track and measure the effectiveness of websites. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Web Analyst

Technical Writer

Technical Writers use their knowledge of data analysis to create documentation for software and other products. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the writing skills you need to create clear and concise documentation.

See salaries and explore the career path for Technical Writer

Reading list

We've selected 15 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Analysis Using Python.

Probabilistic Machine Learning

Save

Provides a comprehensive introduction to machine learning from a probabilistic perspective. It covers the basics of supervised and unsupervised learning, as well as more advanced topics.

Probabilistic Machine Learning: Advanced Topics...

Hardcover

$$$$

Machine Learning Q and AI

Save

Provides a comprehensive introduction to machine learning using Python. It covers the basics of supervised and unsupervised learning, as well as more advanced topics.

Data Analysis Using Python

Three deals to help you save

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Comprehensive python course for data analysis

Activities

Career center

Reading list

Share

Similar courses