프로그래밍 시작하기 : 파이썬 입문 (Inflearn Original)
인프런
이미 2만명 이상이 학습하고 만족한 최고의 프로그래밍 입문 강의. 인프런이 비전공자 위치에서 직접 기획하고 준비한 프로그래밍 입문 강의로, 프로그래밍을 전혀 접해보지 못한 사람부터 실제 활용 가능한 프로그래밍 능력까지 갈 수 있도록 도와주는 강의입니다.
입문
Python
BEST
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.
Reviews from Early Learners
What you will learn!
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.
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
Financial Data Analysis, One Step Deeper! Follow-up Lecture
Recommended for
these people
Who is this course right for?
If you are new to Pandas or not familiar with it
Anyone who wants to analyze financial data with Python
Need to know before starting?
Python Basic Grammar
706,185
Learners
6,305
Reviews
118
Answers
4.7
Rating
133
Courses
배움의 기회는 경제적, 물리적 한계에서 자유로워야 한다고 생각합니다.
우리는 성장기회의 평등을 추구합니다.
Curriculum
All
59 lectures ∙ (10hr 15min)
Course Materials:
Lecture resources
7. About Pandas
05:44
8. Pandas Type
04:53
9. Create Series
09:51
18. NaN handling
04:29
24. Series Finale
04:15
Published:
Last updated:
Reviews
All
30 reviews
4.8
30 reviews
정유재Reviews 2
∙
Average Rating 5.0
5
100% enrolledPANDAS 강의 입문으로 최고라고 생각합니다. 각각의 코드에 대한 설명도 잘 되어있고 딱딱한 이론보다 더욱더 현실에 가까운 수업이라고 생각합니다. 파이썬 함수들부터 시작해서 pandas method, 데이터에 어떻게 접근하면 되는지까지 잘 녹여낸 강의!
- Suit & CoffeeInstructor
안녕하십니까 정유재님! 수강평 정말 감사합니다. 정말 제게 너무나 과분한 수강평인것 같네요. 처음 촬영해본 강의라서 실수도 많고, 더듬더듬 거리는 부분도 정말 많았을텐데.... 강의 들어주셔서 정말 감사합니다 혹시 궁금한 내용이나 앞으로 수강하고 싶은 강좌 컨셉이 있으면 언제든지 말씀해주세요. 향후 강의제작에 참고하도록 하겠습니다 강의 듣느라 정말 고생하셨습니다 새해 복 많이 받으세요!
- JE Chory
Reviews 7
∙
Average Rating 5.0
5
100% enrolled아직 시리즈까지밖에 안들었지만, 강사님이 실무에서 얻은 노하우를 바탕으로 강의가 진행되어서 그런지 단순히 문법을 설명해주기 보다는 손에 익히면 좋을만한 구문을 모아놓으신것 같아 만족도가 높습니다만... 수강환경 측면에는 조금 문제가 있습니다.. 강의를 들을시에 강사분의 화면이 너무 작아서 눈이 아픕니다. (저는 굉장히 시력이 좋은 20대 학생입니다 ㅋㅋ.. 또한 15인치 노트북으로 수강중입니다.) 강사분께서 작성하신 코드는 주피터 노트에 잘 정리되어있기에 주피터 노트를 참고하면서 충분히 수강이 가능하지만 조금 줌인이 되어있는 버전으로 업데이트를 해주실 수 있는지 궁금하고, 그게 불가능하다면, 새로운 강의를 찍으실때는 양 옆쪽의 여백을 줄이고 줌인을 하셔서 찍으셔야 할 것 같습니다. 물론 이 부분은 개인차가 있겠습니다만.. 다른 인프런 강의에 비교해보았을 때 그런 측면이 있다는 것입니다. 강의 콘텐츠는 정말 만족스럽습니다.
- Suit & CoffeeInstructor
안녕하세요 JE Chory님 .... 좋은 강의평 정말 감사합니다. 강의를 찍으면서 그 부분에 대해서 신경을 좀 써야 했었는데, 제가 그러지 못했습니다. 너무 저 위주로 생각하면서 강의를 찍었네요..... 이미 다 올라온 강의라 수정은 조금 어렵다는 점.... 정말 죄송합니다. 하지만 JE Chory님의 말을 참고하여 다음 강의부터는 수강생 입장에서 편하게 들을 수 있게 촬영하도록 하겠습니다. 남은 부분도 화이팅이시구요. 궁금한 부분 있으면 언제든지 댓글 남겨주세요. 수강평 정말 감사합니다.
- 법경
Reviews 49
∙
Average Rating 4.9
5
100% enrolled좋은 강의 감사합니다
- Suit & CoffeeInstructor
안녕하세요 법경님! 수강평 정말 감사합니다! 트레이딩룸 Part1도 들어주시고, 정말 감사함을 느낍니다. 법경님에게 조금이나마 도움이 되었는지 모르겠네요. 앞으로 듣고싶은 강의나 궁금한 점 있으면 언제든지 말씀해주세요. 강의 듣느라 정말 고생 많으셨습니다. 새해 복 많이받으세요!
- GG G
Reviews 5
∙
Average Rating 5.0
- donseok.lee
Reviews 31
∙
Average Rating 4.9
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