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Data Science

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Data Analysis

[R] Collection and management of data on all KOSPI/KOSDAQ items

Learn how to collect and manage all stocks listed on the stock market. Create a dashboard using shiny that automatically collects new stock prices every day and can also identify stock trends by industry.

(4.9) 8 reviews

92 learners

Level Intermediate

Course period Unlimited

  • coco
R
R
Web Crawling
Web Crawling
R
R
Web Crawling
Web Crawling

Reviews from Early Learners

Reviews from Early Learners

4.9

5.0

DT로

100% enrolled

It's great for practical assignments.

5.0

hakjuknu

87% enrolled

Good!

5.0

조정태

100% enrolled

I am very satisfied with the lecture content. I will continue to review it so that I can fully understand it. Thank you.

What you will gain after the course

  • Collection of all KOSPI/KOSDAQ stocks

  • Industry-specific stock data management

  • Understanding industry-specific stock trends

🙆🏻‍♀ Automate all stock data collection and management/industry-specific stock management 🙆🏻‍♂

KOSPI/KOSDAQ
Collection and management of data for all categories

🗒 Course Introduction

Would you like to analyze a stock you are interested in or all stocks listed on KOSPI/KOSDAQ?
To do analysis, you need data .

This course collects and manages all stocks listed on our country's stock market.
Due to time constraints, the lecture collects data for the past three years for all subjects.
If you change 3 to 10, you can easily collect 10 years' worth of data.

Starting today, we will collect not only the last 10 years of data, but also new data, that is, data generated the next day.
Automation updates the stocks daily by collecting data on the day's transactions around 4 p.m., when the stock market closes.

Create a Shiny Dash Board like the address below.

https://leegt.shinyapps.io/shiny/

(Connection may not be possible if the number of people exceeds a certain number)

🌈 Get stock code

All companies (stocks) listed on the stock market have their own unique code.
Depending on this code, the address to be crawled will change.
So, first, we collect the unique code for each company.
Additionally, we preprocess the code so that it can be imported from Naver Finance.

🌈 Collection of all stocks

After setting the Naver Financial address for each stock, data for the past three years is collected for all stocks.
It took about 4 hours to collect 3 years' worth, so I think 10 years' worth could be collected in about 12 hours.

After collecting daily stock data by stock, create a folder for each stock and save it in each folder.
Additionally, exception handling is provided in case an error occurs.

🌈 Automated daily stock collection

We can't scrape 10 years' worth of data like this every day. It's highly inefficient.
After today's stock trading is completed, automation proceeds by collecting only today's stock data and merging it with previously stored data.
Now we can automatically update all daily stock data every day at 4 PM.

🌈 Understand stock trends by industry and create a dashboard using Shiny

From a mid- to long-term stock investment perspective, it is important to understand industry/theme trends.
We collect stock codes by industry, retrieve data on these stocks, identify trends, and visualize them.

🌈 Full process automation

After the stock market closes each day, we collect additional daily data and automate the entire process, from managing and visualizing stocks by industry.

✅ Please make sure to check!

This lecture is This is a follow-up lecture.
The lecture assumes basic knowledge of the R language and crawling.

Web Crawling with R - Introduction
You can learn the concepts of R and get started with crawling.

Recommended for
these people

Who is this course right for?

  • Someone who knows the basics of R

  • Anyone who needs stock data

  • Anyone who wants to build up basic data for investing

Hello
This is

8,388

Learners

509

Reviews

136

Answers

4.4

Rating

20

Courses

I am an unemployed scholar who majored in statistics as an undergraduate, earned a PhD in industrial engineering (artificial intelligence), and is still studying.

Awards ㆍ 6th Big Contest: Game User Churn Algorithm Development / NCSOFT Award (2018) ㆍ 5th Big Contest: Loan Delinquency Prediction Algorithm Development / Korea Association for ICT Promotion

Awards

ㆍ 6th Big Contest Game User Churn Prediction Algorithm Development / NCSOFT Award (2018)

ㆍ 5th Big Contest Loan Defaulter Prediction Algorithm Development / Korea Association for ICT Promotion (KAIT) Award (2017)

ㆍ 2016 Weather Big Data Contest / Korea Institute of Geoscience and Mineral Resources President's Award (2016)

ㆍ 4th Big Contest: Development of Insurance Fraud Prediction Algorithm / Finalist (2016)

ㆍ 3rd Big Contest Baseball Game Prediction Algorithm Development / Minister of Science, ICT and Future Planning Award (2015)

* blog : https://bluediary8.tistory.com

My primary research areas are data science, reinforcement learning, and deep learning.

I am currently doing crawling and text mining as a hobby :)

I developed an app called Marong that uses crawling to collect and display only popular community posts,

I also created a restaurant recommendation app by collecting lists of famous restaurants and blog posts from across the country :) (it failed miserably..)

I am currently a PhD student researching artificial intelligence.

I even developed a restaurant recommendation app by collecting blog posts and lists of top-rated restaurants across the country :) (though it failed miserably...) Now, I am a PhD student researching artificial intelligence.

I even developed a restaurant recommendation app by collecting lists of famous restaurants and blogs from all over the country :) (It failed miserably...) Now, I am a PhD student researching artificial intelligence.

I even developed a restaurant recommendation app by collecting lists of famous restaurants and blogs from all over the country :) (It failed miserably...) Now, I am a PhD student researching artificial intelligence.

I even developed a restaurant recommendation app by collecting lists of famous restaurants and blogs from all over the country :) (It failed miserably...) Now, I am a PhD student researching artificial intelligence.

Curriculum

All

23 lectures ∙ (3hr 55min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

8 reviews

4.9

8 reviews

  • psangkuk6551님의 프로필 이미지
    psangkuk6551

    Reviews 4

    Average Rating 5.0

    5

    100% enrolled

    It's great for practical assignments.

    • hakjuknu님의 프로필 이미지
      hakjuknu

      Reviews 155

      Average Rating 5.0

      5

      87% enrolled

      Good!

      • jtcho님의 프로필 이미지
        jtcho

        Reviews 15

        Average Rating 5.0

        5

        100% enrolled

        I am very satisfied with the lecture content. I will continue to review it so that I can fully understand it. Thank you.

        • jangdh1993 (탈퇴)님의 프로필 이미지
          jangdh1993 (탈퇴)

          Reviews 1

          Average Rating 5.0

          5

          100% enrolled

          thank you

          • kyuhakkim1684님의 프로필 이미지
            kyuhakkim1684

            Reviews 1

            Average Rating 4.0

            4

            100% enrolled

            Good content. However, the content using Naver site is from a year ago, so it seems like the data needs to be supplemented.

            $42.90

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