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Pandas for Data Analysis: From Basics to Data Analysis

Datarian's Pandas basic course with over 10,000 cumulative students and rich online/offline lecture experience. Learn Pandas, Python's representative data analysis library, systematically with official documentation. You can also improve your proficiency by learning theories and solving problems in parallel.

(4.8) 32 reviews

374 learners

Pandas

Reviews from Early Learners

What you will learn!

  • Processing data with Pandas

  • Analysis and visualization using Pandas

  • Improve your Pandas proficiency by solving problems

Pandas for data analysis,
Get a solid understanding with the official documentation!

Pandas, why should I learn it?

Using the Python library, Pandas
You can analyze data easily and conveniently.

When data analysts conduct analysis in Python, the first thing they typically do is import the Pandas library . Whether it's visualization, machine learning, or applying statistical models, preprocessing data to create a suitable format is essential. Pandas is the library (package) most specialized for this data handling process, and is therefore the most widely used.

Get started with Pandas, the essential Python data analysis course, with Datarian!

✔️ Course Roadmap


What makes this course special?

Use the official Pandas documentation.

We'd all agree that "Googling is essential" when coding. While the web offers a wealth of documentation for information, the official documentation is by far the best. It offers precise terminology and usage guidelines. Even those already proficient with Pandas are often surprised by the official documentation, exclaiming, "Wow, there's such a great feature!"

For those of you just starting out with Pandas, why not start with the official documentation, the best textbook ever? Our course will serve as a guide to help you on this journey. You'll learn by reading the official documentation, following along with example code, and adding additional explanations.


Comparisons with SQL and Excel help you understand quickly.

The data Pandas handles is a "two-dimensional data frame." While the term "two-dimensional data frame" might sound unfamiliar, it's actually a concept you're already familiar with. Think of it as tabular data, like those often seen in spreadsheets like Excel. If you're familiar with SQL tables, you'll understand it even better.

Because Pandas is a tool that handles similar data types, it often offers similar, or even more powerful, features than SQL and Excel. That's why, when learning a new function, I've included comparisons with SQL or Excel. Learning by comparing it to what you already know will make it easier and faster to understand, right?

This course is helpful for those who are starting Python to do more in-depth analysis and visualization than what can be done with SQL, or for those who need Pandas to handle large amounts of data that cannot be imported into Excel, or for those who are already using other tools.

Q. SQL, is it something I absolutely need to know?

I recommend starting with SQL first, but if you have experience with Excel, I don't think you'll have much difficulty understanding the lecture :)

Excel, Pandas, and SQL are all similar tools in that they handle tabular data with rows and columns . Their supported features are also very similar. The official documentation, which is also included in the lecture, requires no prior knowledge of any language other than Python. While some concepts common to SQL when working with data tables, such as joining two tables using common keys and group-by operations, are omitted from the video, supplementary material is provided at the bottom of the video. If you've watched the sample lecture and thought, "This is worth a try," that's enough.


Improve your skills by solving problems together.

Seeing is believing! Learning is only as effective as practicing. Take the time to truly understand and master the grammar you've learned, understanding the specific situations and tasks for which it's applicable.

At the end of each section, we'll provide a list of problems that allow you to practice the functions you've learned in that section. We encourage you to pause the lecture and review by solving the problems. We'll also share the solution process in the final video, "Problem Solving," of each section. The final section consists of problems that synthesize everything you've learned so far, so let's keep going!


Recommended students

Pandas
Systematically
Anyone who wants to understand

With problem solving
Pandas
Those who want to study

When using SQL
Analysis area with Python
Those who want to expand

Spreadsheets such as Excel
I tried it
Anyone who wants to learn Pandas


The curriculum
Please check it out.

Pandas Warm Up!

We'll learn about Google Colaboratory (Colab), the platform we'll use in this course, and then work through the official Pandas documentation. We'll explore the steps involved in loading and saving data with Pandas, and learn how to select specific columns and rows.

Data Exploration A to Z.

We'll use Pandas to create simple visualizations to understand data trends and flows. You'll also learn how to create new columns by calculating values from existing columns, perform necessary calculations, and aggregate and scale data.

Data organized into tables!

Learn how to transform and sort tables, link with Google Spreadsheets, and create pivot tables for data. You'll also learn how to link rows from multiple tables and combine them using common columns.

Various types of data are also OK.

We'll learn how to handle time series data and textual data, and even how to use regular expressions to find specific patterns.


Datarian Team
Interested in other lectures?

Seeing is believing!
Datalian SQL Series

Basic SQL for Data Analysis (Click)

Intermediate SQL for Data Analysis (Click)

Python Series for Data Analysis

Python for Data Analysis: From Beginners to Tips (Click)

Recommended for
these people

Who is this course right for?

  • For those who want to understand Pandas systematically

  • For those who want to study Pandas with problem solving

  • For those who are currently using SQL and want to expand their analysis area with Python

  • Those who have used spreadsheets such as Excel and want to learn Pandas

Need to know before starting?

  • Basic Python (understanding of data structures such as list, dict, etc.)

Hello
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33,356

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Reviews

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Answers

4.9

Rating

40

Courses

실무 경험이 탄탄한 현업 분석가들이 데이터 분석 교육을 기획하고, 직접 강의합니다.

데이터리안에 대해서 더 알아보고 싶다면

👉 https://datarian.io/

Curriculum

All

56 lectures ∙ (6hr 25min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

32 reviews

4.8

32 reviews

  • 상열님의 프로필 이미지
    상열

    Reviews 1

    Average Rating 5.0

    5

    70% enrolled

    선생님 정말 최고에요! 진짜 감사해요...수업 중간중간 보여주시는 참고자료도 이런게 있었구나 싶을 정도로 너무 좋고...그냥 감사하단 생각 뿐이네요ㅠ 파이썬 강의 더 출시해주시면 좋을 것 같아요....!!!!

    • 윤선미
      Instructor

      이런 수강평 남겨주신 상열님이 정말 최고입니다 진짜 감사해요... 참고자료 드리는게 유용했다니 정말 뿌듯하네요. 파이썬 시각화 강의 열심히 제작 중이에요. 올해 상반기 안으로 찾아 뵙겠습니다! 그리고 데이터 분석 공부하시는 분들에게 자주 추천드리는 자료들을 카카오톡에서 보실 수 있도록 모아놨어요. 팔로우 같은거 안하셔도 보실 수 있으니까 상열님께 유용한 자료 발견하셨으면 좋겠네요 감사합니다~ :D http://pf.kakao.com/_DQxfsb (링크는 모바일에서 열리구 보드 탭으로 들어가시면 돼요!)

  • 김태우님의 프로필 이미지
    김태우

    Reviews 7

    Average Rating 5.0

    5

    100% enrolled

    정말 좋습니다!

    • 윤선미
      Instructor

      김태우님 수강평 감사합니다 :D 늦었지만 완강 축하드려요!

  • kim_dh님의 프로필 이미지
    kim_dh

    Reviews 8

    Average Rating 4.9

    5

    98% enrolled

    SQL부터 선생님 강의 듣고 있습니다 ㅎㅎㅎㅎ 유익한 강의 감사드립니다♥

    • 윤선미
      Instructor

      안녕하세요! 어쩐지 익숙한 아이디네요ㅎㅎㅎ 강의는 재미있게 들으셨나요? SQL 강의랑 파이썬 강의는 느낌이 또 약간 다른데 어떻게 들으셨는지 궁금하네요. 수강평 감사합니다!

  • 까만돌님의 프로필 이미지
    까만돌

    Reviews 57

    Average Rating 4.8

    5

    98% enrolled

    좋은 강의 감사합니다.

    • 윤선미
      Instructor

      머털쌤님 수강평 감사합니다!

  • hodumaru님의 프로필 이미지
    hodumaru

    Reviews 7

    Average Rating 5.0

    5

    68% enrolled

    sql부터 듣고 있는데 많이 도움됐어요 ~

    • 윤선미
      Instructor

      명균님 수강평 감사합니다!!

$59.40

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