
私もコーディングのJava基本編 - フルコース(20時間)
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学びの楽しみを知らせてくれる講義。私もコーディングのJava基本編を紹介します。
입문
Java, oop
You can use Python to analyze large amounts of data and visualize the analyzed data in graph form so that you can easily understand it at a glance.
How to use pandas, an essential library for Python data analysis
Matplotlib, a visualization library that lets you understand complex data at a glance
Analysis of the Population Pyramid of South Korea (Practical Project #1)
Analysis of births and total fertility rate (Practical Project #2)
If the basic Python grammar is now easy,
Finish your Python learning with data analysis and visualization! 😎
📢 Please check before attending the lecture.
The navigation system in your car can tell you what time, where, and how fast you were moving.
As this data accumulates, we can determine the current traffic volume on a road and provide a choice of smooth, slow, or congested conditions. In some cases, if congestion is severe, we can even provide additional detour guidance.
It is no exaggeration to say that data is overflowing around us, to the point where it is almost impossible to say that everything is data.
Analyzing this data can reveal a variety of insights, and Python provides the Pandas library , which allows for easy data analysis, allowing you to slice, paste, and filter data.
If you're trying to decide which of two cars to buy, the graph on the right might be easier to understand than the table on the left, right?
Data visualization, which presents data in graph form so that it can be easily seen with the eyes, is just as important as data analysis.
A picture like the one on the right is called a radar chart .
Python has a library called M atplotlib for data visualization .
You can create various graphs, such as bar graphs, histograms, and scatter plots.
In this way , you will learn how to perform basic data analysis and visualization using Pandas and Matplotlib.
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Who is this course right for?
Anyone who wants to discover the value hidden in data
People who frequently handle Excel files for work
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Python Basics
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Reviews
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Answers
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39 lectures ∙ (6hr 17min)
1. Intro
00:16
3. introduction
03:30
4. Series
09:35
5. DataFrame
10:54
6. Index
08:53
8. Data Verification
11:34
14. Missing values
11:16
15. Sorting data
06:25
16. Modify data
22:48
18. Grouping
15:32
19. Quiz
08:29
20. Graph Basics
09:48
21. axis
06:01
22. Legend
04:29
23. style
19:50
24. Save file
03:41
25. Text
04:45
26. Multiple data
05:32
31. Multi-bar graph
11:32
34. Scatter plot
11:16
35. Multiple graphs
08:53
36. Quiz
13:55
All
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