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How to use Pandas for financial data analysis

The fact that you can analyze data more easily and effectively with Python Pandas instead of Excel! Learn the basic functions of the Pandas library and how to use it in practice through financial data analysis.

(4.7) 수강평 43개

강의소개.상단개요.수강생.short

난이도 초급

수강기한 12개월

Pandas
Pandas
Investment
Investment
Quant
Quant
Pandas
Pandas
Investment
Investment
Quant
Quant

먼저 경험한 수강생들의 후기

먼저 경험한 수강생들의 후기

4.7

5.0

정유재

100% 수강 후 작성

I think this is the best introduction to PANDAS lectures. Each code is well explained, and I think it is a class that is closer to reality than a rigid theory. A lecture that starts with Python functions and covers everything from pandas methods to how to access data!

5.0

JE Chory

100% 수강 후 작성

I've only listened to the series so far, but since the lecture is based on the know-how the instructor gained from his work, rather than simply explaining grammar, I think he collected phrases that are good to get used to, so I'm very satisfied... There's a bit of a problem with the learning environment. When I listen to the lecture, the instructor's screen is too small, so my eyes hurt. (I'm a student in my 20s with very good eyesight, lol.. Also, I'm taking the class with a 15-inch laptop.) The code the instructor wrote is well organized in the Jupyter note, so I can take the class sufficiently by referring to the Jupyter note, but I wonder if you can update it to a version that's a little zoomed in, and if that's not possible, when you film a new lecture, you should reduce the margins on both sides and zoom in. Of course, this part will vary from person to person, but... Compared to other Inflearn lectures, there's that aspect. I'm really satisfied with the lecture content.

5.0

법경

100% 수강 후 작성

Thank you for the great lecture.

강의상세_배울수있는것_타이틀

  • Pandas Basics

  • How to use Pandas to analyze financial data!

Data Analysis, Smarter with Pandas!
Analyze financial data with your own hands.

Excel data analysis, something is missing ... 😯

Data analysis capabilities are becoming increasingly important day by day!
That's how many people are interested in data analysis.

However, anyone who has ever processed and analyzed a large amount of data using Excel has probably thought about this at least once.
When you deal with a lot of data, your sheets start to slow down and you start to get headaches because of functions that are not very usable.


Now that Excel is frustrating,
When you need to meet Pandas .

Pandas is a programming language that uses Python.
Used for data extraction, processing, analysis, and visualization.
This is a library specialized in data analysis .

When it comes to using programming for data analysis, it can seem difficult.
However, if you start analyzing data with Pandas instead of Excel, you can analyze and process data much more easily and conveniently.

Three reasons to use Pandas instead of Excel!


Easy with Pandas
Start analyzing financial data 💡

I know the basic grammar of Python, but
How to handle financial data/time series data
This was created for those who don't know.

How to use the Pandas library for financial data analysis revealed!

This lecture explains in detail how to use Pandas to handle time series data. I will introduce how to load data with Pandas and analyze it, and I will provide the Pandas manual that I am familiar with. In addition, I will show various examples using various data so that you can feel closer to actual financial data analysis.

In addition, I have included various experiences I have had while actually handling financial data with Pandas in the lecture. I have included various examples necessary for actual data analysis so that you can skip over the parts that require a lot of time and thought when starting data analysis without much thought.

The goal of this lecture is to create your own Pandas manual and to use Python instead of Excel for financial data analysis. At first, Pandas may seem unfamiliar and difficult, but after listening to the lecture, you will feel that Pandas is a really useful tool for data analysis . I support your challenge!

Recommended for these people

  • If you are new to Pandas or are unfamiliar with it
  • Anyone who wants to analyze financial data with Python
  • Anyone who wants to create their own Pandas manual for financial data analysis

Anyone can do it!
Practical Pandas learning in 4 steps .

Data analysis that fosters application skills

This course is not just about explaining what Pandas is and doing code exercises.
The course is structured to enable students to create a practical Pandas manual for data analysis.

100% realistic! Example-based lectures

From the beginning to the end of the course, you will practice with real financial data. You will directly deal with various examples that can occur in real analysis from beginning to end.

No to lectures that you watch once and then stop!

Let's create a pandas manual using Jupyter Notebook. In the future, whenever we do data analysis, we will be able to refer to the manual created in the lecture.

I also think about future concerns

In this lecture, we will directly point out the points that beginners can easily get confused about while using Pandas. We will reduce the worries and trial and error of those who will use Pandas in the future.

Level up with vivid projects!

In the second half, we will show you how to apply what you have learned through a practical project. See how you can use it in real-life financial data analysis.

You can check the detailed curriculum directly below.


Created a lecture
A word from a knowledge sharer 🎤

Hello! This is QT.

I organized the lectures with the intention of conveying the knowledge that I use in my work and in finance. Data analysis may seem unfamiliar and distant, but I want to inform and convey that it is not the case.

There is no right answer in data analysis, and even with the same results, each person can claim different conclusions. I hope my knowledge and experience can help you make decisions.


Any questions
Check it out now! 💬

Q. Can I take the course without knowing basic Python grammar?

This lecture is a Pandas lecture for learning data analysis using Python. You must be familiar with the basic Python grammar and listen to it. Anyone who knows basic Python grammar such as list, dict, tuple, and for loop can take the course.

Q. Are we learning all the features of Pandas?

The Pandas library has so many functions that you can't learn everything about Pandas. However, this lecture will focus on financial data analysis and cover the Pandas functions needed for financial data analysis.

Q. Where can I get actual financial data?

The code and financial data used in the lecture are provided directly in the lecture. Please refer to the [Preview] of the lecture to see how to take the lecture! (Section 0 [Things to note before taking the lecture])

Q. How is it different from other Pandas lectures?

The main difference from other courses is that it focuses on financial data analysis. We teach using actual financial data, and the curriculum is organized according to the order in which financial data is analyzed.

Q. What should I study further after attending the lecture?

This lecture is designed for those who do not know Pandas before taking the [Creating Your Own Trading Room Series] . If you have taken this [Using Pandas for Financial Data Analysis] lecture, we recommend that you take the [Creating Your Own Trading Room] series. Also, if you have completed this lecture, I believe you will not have any difficulties with Pandas in future Python lectures related to financial data analysis.


It's better when you listen together
Collection of related lectures 📌

If you need Python basics? Recommended player lectures

Getting Started with Programming: Introduction to Python

Financial Data Analysis, One Step Deeper! Follow-up Lecture

Creating your own trading room using Python - Part 1

강의소개.콘텐츠.추천문구

학습 대상은 누구일까요?

  • If you are new to Pandas or not familiar with it

  • Anyone who wants to analyze financial data with Python

선수 지식, 필요할까요?

  • Python Basic Grammar

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43개

4.7

43개의 수강평

  • morrisrt68514454님의 프로필 이미지
    morrisrt68514454

    수강평 2

    평균 평점 5.0

    5

    100% 수강 후 작성

    I think this is the best introduction to PANDAS lectures. Each code is well explained, and I think it is a class that is closer to reality than a rigid theory. A lecture that starts with Python functions and covers everything from pandas methods to how to access data!

    • quanttrader
      지식공유자

      Hello, Jeong Yu-jae! Thank you so much for your course review. I think this course review is really too much for me. Since this is my first time filming a lecture, I made a lot of mistakes and there must have been a lot of parts where I stumbled.... Thank you so much for listening to the lecture. If you have any questions or have any concepts for courses you would like to take in the future, please let me know at any time. I will use them as a reference when making future lectures. Thank you for your hard work listening to the lecture. Happy New Year!

  • jaecheolfruit1063님의 프로필 이미지
    jaecheolfruit1063

    수강평 7

    평균 평점 5.0

    5

    100% 수강 후 작성

    I've only listened to the series so far, but since the lecture is based on the know-how the instructor gained from his work, rather than simply explaining grammar, I think he collected phrases that are good to get used to, so I'm very satisfied... There's a bit of a problem with the learning environment. When I listen to the lecture, the instructor's screen is too small, so my eyes hurt. (I'm a student in my 20s with very good eyesight, lol.. Also, I'm taking the class with a 15-inch laptop.) The code the instructor wrote is well organized in the Jupyter note, so I can take the class sufficiently by referring to the Jupyter note, but I wonder if you can update it to a version that's a little zoomed in, and if that's not possible, when you film a new lecture, you should reduce the margins on both sides and zoom in. Of course, this part will vary from person to person, but... Compared to other Inflearn lectures, there's that aspect. I'm really satisfied with the lecture content.

    • quanttrader
      지식공유자

      Hello JE Chory.... Thank you so much for the great lecture review. I should have paid more attention to that part while recording the lecture, but I didn't. I recorded the lecture thinking too much about myself..... It's a lecture that's already been uploaded, so it's a bit difficult to edit... I'm really sorry. However, I will take note of JE Chory's words and record the next lecture so that the students can listen comfortably. Fighting for the rest. If you have any questions, please leave a comment at any time. Thank you so much for the lecture review.

  • mirrorlaw0346님의 프로필 이미지
    mirrorlaw0346

    수강평 49

    평균 평점 4.9

    5

    100% 수강 후 작성

    Thank you for the great lecture.

    • quanttrader
      지식공유자

      Hello, Beopgyeong! Thank you so much for your review! I really appreciate you listening to Trading Room Part 1. I wonder if it was of any help to you. If you have any questions or want to hear more lectures in the future, please let me know. Thank you for your hard work listening to the lectures. Happy New Year!

  • dlemfflsk8970님의 프로필 이미지
    dlemfflsk8970

    수강평 5

    평균 평점 5.0

    5

    41% 수강 후 작성

    Thank you for the great lecture. However, the screen is too small 😭😭 Also, things may vary depending on the Pandas version, so let's refer to the 'Q&A' section!

    • donseoklee2548님의 프로필 이미지
      donseoklee2548

      수강평 33

      평균 평점 4.9

      5

      100% 수강 후 작성

      It was something I didn't know much about, but it was so good that I could easily understand it.

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