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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 Adult education level data analysis 4 - Making a scatter plot using ggplot() + geom() function with R

UnsplashSergey Leont'evが撮影した写真 

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This post is following of the above post.

In this post, let's see relationship between two variables.

First, let's see correlations.

I use cor() function to see correlation. TRY and men_women has negative correlation, -0.442, TRY and l_usd_cap has positive correlation, 0.746 and men_women and l_usd_cap has negative correlation, -0.207.

Then, let's make scatter plots with ggplot() + geom_point() function.

I add aes(color = LOCATION) in geom_point() function, so that I can see scatter plots by LOCATIONs. I see each LOCATIONs have positiove relationship between TRY and l_usd_cap.

Let's use aes(color = as.factor(TIME)). 

I cannot say any meaningful comment on above scatter plot.

Let's use facet_wrap()  function instead of aes(color = as.factor(TIME)).

Now, I can say TRY and l_usd_cap have positiove correlations each year.

Next, let's see men_women and l_usd_cap.

I see men_women and l_usd_cap have negative correlation in each LOCATIONs.

How about by TIME? I use facet_wrap() function.

Oh! It is intersting, when I use facet_wrap( ~ TIME), clear positive relationship between men_women and l_usd_cap disappear .

Next, let's see TRY and men_women.

I see each LOCATION have positive relationship between TRY and men_women.

How about by TIME?

I see there are weak negative relationships.

That's it. Thank you!

Next post is

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To read from the 1st post,

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