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政府統計の総合窓口のデータや、OECDやUCIやのデータを使って、Rの練習をしています。ときどき、読書記録も載せています。

OECD Researchers data analysis 3 - 5 Named Graphs in R

UnsplashPhong Nguyenが撮影した写真 

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This post is following of the above post.
In this post I will create 5 names graphs in R.

I refer to Chapter 2 Data Visualization | Statistical Inference via Data Science (moderndive.com)

5 Named Grpahs are

#1 scatterplots

#2 linegraphs

#3 histograms

#4 boxplots 

#5 barplots

Let's start with #1 scatterplots

scatterplots shows two variables relationship. The above plot show TIME vs l_tot_1000employed. In general recent time has more large l_tot_1000employed.

The above scatterplot shows l_usd_cap vs. l_tot_1000empolyed. The more l_usd_cap, the more l_tot_1000employed.

The next 5 named graphs is #2 linegraphs

The above linegrap shows TIME vs. l_women_pc_researcher. Recent TIME has largeer l_woemn_pc_researcher.

The 3rd five named graphs is #3 histograms.

Histgrams shows variable distribution. The above histogram shows l_women_headcount distribution.  Let's see another histograms.

I added " facet_wrap(~ TIME) " so that I can see histograms by TIME. 

The 4th five named grapsh is boxplots.

I see recent TIME has greater l_tot_headcount in general.

Tha last 5 named grpahs is #5 barplots.

I see odd number TIME has more observations than even number TIME has.

Let's see number of observations by LOCATION.

HUN has the most observations.

That's it. Thank you!

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