[Updated] Your First Python Data Analysis (Easily! Learn the Entire Process of Preprocessing, pandas, and Visualization) [Data Analysis/Science Part 1]

This course teaches the fundamental skills needed to learn the entire Python data analysis process for beginners in data analysis. As an e-commerce planner and developer who actively uses data analysis techniques in the field, I designed it to help you easily learn the full Python data analysis process and apply it right away.

(4.9) 377 reviews

4,428 learners

Level Basic

Course period Unlimited

Python
Python
Pandas
Pandas
Plotly
Plotly
Python
Python
Pandas
Pandas
Plotly
Plotly

Reviews from Early Learners

4.9

5.0

홍현빈

100% enrolled

What sets this lecture apart from others is... You often say things like: "You don't need to understand 100%." "Make good use of AI." "The important thing isn't creating results by utilizing 100% of the code yourself." Thanks to those words, even though I can't write code from A to Z from scratch, I've become able to start projects by utilizing AI and thinking, "Ah, so this part is used with this meaning," "Oh, I could try changing this part like this," or "I think there were functions like that back then; should I look them up?" Of course, it would be wonderful to be able to do everything from A to Z alone, but when it's difficult to invest that much time while balancing a career, I believe it's more important to at least have the fundamentals and background knowledge to utilize code written by others. In that sense, this course not only allows you to build a solid foundation through repeated listening, but it also felt comfortable—like receiving private tutoring without the pressure. At first, I just listened and nodded along. After class, I took the time to do some clone coding on at least a few of the final files (if not all of them), adding my own comments and editing them in my own style. Thank you for the great lecture.

5.0

데싸데분

31% enrolled

I'm continuing this course after taking the Web Scraping Basics Bootcamp! I'm currently taking other bootcamps in parallel with the goal of becoming a data scientist, and from a beginner's perspective, Fun Coding's lecture quality seems truly overwhelmingly excellent! Going forward, I plan to actively use Fun Coding's lectures for preview purposes, while focusing on review and project work in other bootcamps! Thank you sincerely for the great lectures and passionate feedback every time! I'll see you again in the next lecture 😊

5.0

gyunhwank

100% enrolled

This course was structured around practical exercises covering data preprocessing and EDA using Pandas, and visualization through Plotly, which was a great help in learning the flow and feel of data analysis. By applying the various features of Pandas to actual datasets, I became familiar with the analysis process, and through Plotly, I could create intuitive visualization results, allowing me to develop my data interpretation skills as well. As someone learning data analysis for the first time, the practical-oriented structure was particularly useful, and because the instructor's explanations were kind, it was a course that even non-majors could follow without difficulty.

What you will gain after the course

  • How to use pandas

  • Data Analysis Basics

  • Python data preprocessing

  • Latest data visualization

  • Plotly visualization library

  • Various Data Formats and Data Collection

The official course chosen by Naver, Kakao, LINE, Coupang, and Baemin for internal training!

A high-quality course to build a solid foundation in Python data analysis

This course has been revamped to reflect the feedback received.

This course systematically teaches specialized Python data analysis techniques.

It is designed to teach you data preprocessing, pandas-based data manipulation and analysis, and even the latest visualization library (plotly).

Built alongside real-world work over 10 years of teaching experience with 100,000 learners, this course was created with learners' perspectives in mind more than typical IT courses, and detailed materials are also provided.

This course is currently being used at one of the major Korean tech companies
as an official in-house Python data analysis training course

The detailed content is as follows.

How can I build a foundation in data science and data analysis?

Experience the entire process of data collection, preprocessing, and analysis (SQL/NoSQL + Python).Learn professional analysis skills using the Python-based techniques covered in this course. If your goal is to become a data analyst or scientist, we provide a step-by-step roadmap from the basics. (See the data analysis/science roadmap below.)

I also created a video that provides a detailed explanation of data-related careers and the entire data analysis/science process. Depending on your goals, you can efficiently learn data skills through self-study.

I want to analyze real data myself as soon as possible!

Everyone has the basic knowledge needed for data analysis.You only need to know the average. The key is to quickly learn the skills needed to go through the entire analysis process with Python.

From various data preprocessing techniques to data analysis using real-world data
we cover all the essential skills for professional data analysis

Python data analysis is not a skill you can master all at once. To build your skills, you need “familiarity”, but it is most effective when you encounter similar concepts and application examples from various angles. That is why I would like to introduce a book I wrote that you can refer to alongside this course.

The workflow may feel unfamiliar at first. After learning how to use the tools and execute code by watching the lectures, you can build a solid foundation by deleting the code in the provided notebook, writing the key code yourself, and comparing it with the video.

After building a solid foundation, encountering different explanations of the same syntax and additional examples in books can effectively improve your skills.

When you need more examples
A reference book to consult

Introduction to Python Data Analysis: Coding Self-Study with Jaeminae Coding

코딩 자율학습 잔재미코딩의 파이썬 데이터 분석 입문

There are plenty of data analysis courses, but even after taking various courses, you still don't get it!

The data field combines various theories and technologies, so learning them systematically is important. Rather than a course that assumes you already know all the relevant theories and immediately analyzes data while applying flashy machine learning and AI technologies, a course where beginners learn and practice the theories and technologies they need one by one and make them their own is more helpful.

A course based on real-world data analysis and domain experience at Naver, Kakao, Line, Coupang, and Baemin
that explains all the essential technologies step by step and systematically from a beginner’s perspective

I even want to participate in Kaggle competitions

Kaggle competitions primarily use machine learning and AI to predict data. To learn these technologies, you must first become familiar with data analysis techniques such as pandas. This course covers pandas and data visualization, and is structured to help you progressively learn machine learning and deep learning (AI) by following the roadmap. (See the roadmap below)

What skills are needed for data analysis?

In the field, data is primarily analyzed using SQL and pandas.Professional analysis requires data preprocessing, analysis, and visualization skills, which you can learn by mastering pandas and Plotly. This course covers all of these core skills.

How can you effectively learn data analysis skills?

pandas syntax is not intuitive and its extensive functionality creates a barrier to entry, so plenty of practice is required. This course is structured with that in mind:

First half
Learn pandas basics and preprocessing functions by transforming extensive daily data into monthly data
Latter half
Conduct EDA on real e-commerce data and apply data analysis and visualization (plotly) techniques

Designed to help you become familiar with pandas and plotly in a short period and master the entire data analysis process.

They say that data analysis requires a good understanding of the actual business domain, right?

That said, it’s difficult to take a course that requires you to first understand a field you’re not even interested in. Analyze the e-commerce data covered in this course.In recent years, all businesses have been moving online, and e-commerce data is at the core of that shift. You can gain both an understanding of the most useful domain and the related technical skills.

Gain a grasp of the core e-commerce data in the business domain and real-world experience
as well as data analysis and the business domain!

Even after watching the course, should I also buy the book since there are no materials?

We provide code you can run right away, along with concise explanations that go beyond the limitations of books. By watching the lectures and working through the materials alongside them, you can review easily and refer back to them anytime. (We put a lot of care into our materials. We make them better than books, so the materials alone make the course fee worthwhile.)

Now validated by 100,000 learners online and offline over 10 years
With well-organized materials and clear explanations
we provide better online IT courses!
Learn well, and you’ll change!
파이썬 데이터 분석 강의 자료

Don't you need to learn matplotlib for Python visualization?

matplotlib is a traditional yet limited visualization technology focused on creating static graphs. On the other hand, the modern technology plotly focuses on interactive graph creationthat users can interact with,offering excellent visual quality, suitability for web environments, and support for a wider variety of graphs. That is why plotly is becoming the industry standard, and this course also explains plotly.

plotly (supports interactive graphs) VS matplotlib (focused on static graphs)
Plotly와 matplotlib 시각화 비교

A helpful course even for those who have taken data analysis courses before!

To truly master Python data analysis, you need plenty of hands-on practice. This course analyzes real-world examples (COVID-19 data preprocessing and e-commerce data analysis) from start to finish. You can improve your proficiency and organize the knowledge you may have missed.

Don't waste your time!
It's not that we can't do it because we lack information!
Learn with a proven course!

This course was refined through years of countless feedback and created after much deliberation, driven by my dedication to online education.

So that you can feel, 'Ah! This is truly different!'
This course is created through continuous thought and improvement.
Those who are serious about learningonly
please enroll!

A data preprocessing example using actual raw data
COVID data is the most helpful example for learning pandas' basic functions and data preprocessing. It is designed to help you thoroughly master the related techniques by creating graphs of the entire period when COVID was most active, as follows

국가별 코로나 확진자 추이 데이터 전처리 예제

Daily COVID-19 confirmed case trends by country (including the entire period of tracking confirmed cases at the time)

Create reports at the level required for real-world data analysis, complete with industry know-how!
Simply drawing graphs is not enough. In the real world, attention to detail matters.

현업 데이터 분석 보고서 수준의 그래프 예제

Various graphs and analysis from various perspectives

다양한 데이터 분석 그래프 예제

Learn systematically
Dave Lee's Roadmap from Janje-micode

Following this course, explore these roadmaps to learn according to your goals: AI · Development · Data · CS Roadmaps

IT technologies are interconnected.
By selectively learning connected technologies and adding AI to them, you can reach your goals much faster.

Every roadmap covers how to connect and use technologies together,
is designed to gradually increase in difficulty from beginner to expert leveland
is continuously updated over the years.

It is also more discounted than taking the courses individually.

3.Fundamentals of development and data, and core computer science (CS) knowledge

From computer architecture, operating systems, networks, system software, software engineering, and architecture to data structures and algorithms

← Swipe left and right to view the CS courses and the full roadmap →

View the full computer science roadmap in detail

4. The most reliable and powerful AI utilization roadmap (2026)

From Claude Code workflow automation and vibe coding to Codex, OpenClaw, Claude Code–based data analysis, advanced Claude Code techniques such as agentic, harness, and loop engineering, and AI agent development

← Swipe left and right to explore AI courses and reference courses →

View the Most Reliable Ultimate AI Utilization Roadmap (2026) in Detail

Recommended for
these people

Who is this course right for?

  • Those who want to learn Python data analysis techniques

  • Those who want to learn pandas and data visualization techniques

  • Those who want to grow into data analysts in the long term

  • Those who want to learn data analysis skills over the long term

  • Those who want to build a solid foundation in basic data analysis skills

Need to know before starting?

  • Python Basic Syntax

Hello
This is funcoding

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4.9

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Courses

Janjemi Coding, Dave Lee

  • About Janjaemi Coding Introduction Blog [Click]

  • Key Experience: Coupang Senior Development Manager/Principal Product Manager, Samsung Electronics Development Manager (Approx. 15 years of experience)

  • Education: BA in Japanese Language and Literature, Korea University / MS in Computer Science, Yonsei University (A complete mix)

  • Key Development Experience: Samsung Pay, E-commerce Search Service, RTOS Compiler, Linux Kernel Patch for NAS

  • Books: Linux Kernel Programming, Understanding and Developing the Linux Operating System, IT Core Technologies That Anyone Can Easily Read and Understand, Python Programming Primer for Absolute Beginners

  • Operating Site: Fun-Coding (http://www.fun-coding.org) [Click]

  • This is a site that shares free materials related to full-stack development, data science, and AI.

  • Others: Fun-Coding YouTube Channel [Click]

    • I am starting little by little to share tips and short free lectures that are helpful for IT learning~

While working in the industry, I have been consistently creating solid full-stack, data science, and AI courses for 8 years.

 

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Curriculum

All

58 lectures ∙ (12hr 26min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

377 reviews

4.9

377 reviews

  • sorayeon님의 프로필 이미지
    sorayeon

    Reviews 85

    Average Rating 5.0

    5

    48% enrolled

    Thank you very much. It was a great help. I am very satisfied with the lecture content and lecture materials. I am also looking forward to the machine learning lecture. ^_^

    • funcoding
      Instructor

      I am so glad that it was helpful. I will also use the course reviews you wrote to encourage me, always think about them, and try to make better lectures. I really work hard on the lecture materials. I also enjoy making materials. I am so glad and happy that you are satisfied. Please do not open it to the outside, and use it only for personal use. Thank you.

  • jeayun24654823님의 프로필 이미지
    jeayun24654823

    Reviews 2

    Average Rating 5.0

    5

    71% enrolled

    The materials in the provided Jupyter notebook are neat and easy to read, and the practice of graphing the trend of confirmed COVID-19 cases by country is good. If you ask a question you don't know, they will answer quickly and sincerely, and there are no points to deduct. 5 out of 5. The explanations are also good and not difficult.

    • hwanhanhan8907님의 프로필 이미지
      hwanhanhan8907

      Reviews 5

      Average Rating 5.0

      5

      93% enrolled

      As a coding beginner, I started with nothing, starting with the Python bootcamp lecture, then the crawling lecture, and now I have finished the Python data analysis lecture. Although these lectures may seem like separate lectures on the outside, they have a single flow and purpose as they always emphasize during the lectures, and most importantly, they explain in detail and in an easy-to-understand manner from the perspective of a non-major, so I was able to take the classes comfortably. I am currently working in the real estate business, and after taking these lectures, I gained the ability to process and utilize data provided by sites such as Naver Real Estate and public data portals as I want. It may seem lacking to experts, but I think that having this ability as a real estate business owner who is not an IT expert is a really great weapon. Also, there is a huge difference between passively looking at processed data provided by others and looking at data that you have processed yourself. So, if you are just starting out like me, don't worry too much and follow Janjaemi Coding's lectures one by one, you will find yourself growing before you know it. And if there's one thing I wish for, it would be great if there was a lecture that completed a project from start to finish (even if the lecture length is relatively short) based on the lectures I've taken so far (Python Bootcamp, Database, Crawling, Data Analysis, etc.). I'm now going to listen to SQL and NOSQL that I missed in the middle!!!! (My goal is to take all of Janjaemi Coding's lectures this yearㅎㅎ) Thank you for the great lecture and I will continue to trust and follow you in the future.

      • funcoding
        Instructor

        Ah... such a good course review... you must have spent some time on it... thank you. I'm a little touched again. In my opinion, developers only know IT, but people in other fields have expertise in their own fields. Since there are not many people in each field who know IT well, I think that if you have your own expertise and can utilize IT, you can have a huge impact. However, it is very difficult to create such a lecture or absorb such a lecture. Nevertheless, through this lecture, I really like that you actually analyzed real estate data with Python. I think it's because the students are that smart. Thank you.

    • jhryu12089922님의 프로필 이미지
      jhryu12089922

      Reviews 3

      Average Rating 5.0

      5

      100% enrolled

      I am a student who aims for graduate school and research in deep learning, machine learning, and mechatronics. So I took Python lectures from other instructors to build up my basics, and I took this lecture to learn the data processing and analysis process. At first, unlike other instructors, he didn't write the source code while filming videos, but prepared class materials and lectured on the content in detail. Most of the lectures I took were from the former, so it took me a while to get used to the latter. However, the materials related to the class content were really solid. I really liked this part. Also, as the class progressed, what impressed me the most was that even though the class was just continuing, it was repetitive learning. For me, the most difficult thing about listening to lectures is repetitive learning. In the case of academies, they make students repetitive learning through assignments, but on average, many students, including me, find repetitive learning difficult or boring through lectures. However, this lecture was a very helpful lecture for me because it allowed me to learn new content while repetitive learning. Of course, I plan to take other classes again and challenge myself with repeated learning, lol... When I take this class, I first watch the video all at once. If there is a part that I don't understand, I watch it over and over again. Then, I put down the video, put the materials that the teacher gave me on one monitor window, and at first, I wrote down the source code as I remembered it, and when I couldn't remember it/when I thought I had finished writing the source code, I checked the materials. In addition, if you post a question on the Q&A board or the video, you will receive a reply in a day or less at the earliest. This is where you can feel the teacher's enthusiasm. Also, one of the things I felt when I took the Python class was that when you ask a question, they give you a link to the relevant content. And I saw some people who lectured by saying that it would be helpful if you referred to it. Personally, I didn't like it, but the instructor of that class put a lot of effort into leaving comments. And, I plan to take a class on MongoDB for the next class! The class was really good ^_^!

      • funcoding
        Instructor

        Thank you so much for leaving such a great review. It must have taken you a long time to write such a review, but I was actually a little touched that you wrote it in such detail. Reviews like this are a great force that can create good lectures. I tried both the method you mentioned, writing code while doing it, and the method of explaining it with materials and a kind of scenario, but when I did the former, the content I wanted to convey was not conveyed in a substantial way, and since I was worried about both the code and the content I wanted to convey, the learning effect actually decreased. So I decided to use the latter. Actually, answering questions every day is not easy for me either... I'm worried that I'll have to make an announcement when I go on vacation, haha. After all, since I've never met you before, if my answer is not conveyed properly, it's easy for there to be misunderstandings, so I'm paying more attention. When I meet many people online without meeting them in person, there are many cases... Luckily, many people gave me positive reviews, which is a great help. Thank you so much.

    • dkarlfurqkd1님의 프로필 이미지
      dkarlfurqkd1

      Reviews 2

      Average Rating 5.0

      5

      31% enrolled

      Thanks to the A-Z approach with detailed explanations for each topic, I feel like I'm building knowledge from the ground up. No matter what subject you're studying, finding the right course and instructor that fits you is the most important thing, and I think I've found mine.

      • funcoding
        Instructor

        Thank you!!

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