Rで何かをしたり、読書をするブログ

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 Tourism flows data analysis 3 - Boxplots and Scatter Plots using R.

UnsplashQuang Nguyen Vinhが撮影した写真 

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This post is floowing of above post.
In this post, I will draw some graphs to see relationship of two variables.

Fisrt, I see per capita and location with boxplots.

I see SAU, AUS and so on are rich locations while ZAF, COL and so on are not rich locations.

Next, locations and acc_nights.

FRA is espacially many acc_nights.

Next, locations and inter_arr

FRA is the top again.

Let's go on, locations and inter_dep

For inter_dep, GBR is the top.

Then, let's check time series trend. I start with per capita.

For per capita, I see up trend.

How about acc_nights?

I see 2020 and 2021 dropped, it maybe due to COVID-19 pandemic.

Let's ee inter_arr.

For inter_arr, I see more clear drop in 2020 and 2021.

Let's see inter_dep.

I see same drop about inter_dep in 2020 and 2021.

Then, let's make scatter plot to see two numerical variables relationship.

First, per_capita and acc_nights.

I don't see clear pettern. some locations have positive lelationship ande some have negative relationship.

Let's see per_capita and inter_arr.

I see positive relationship.

How about per_capita and inter_dep?

I also see positiove relationship.

Then, let's see acc_nights and inter_arr.

For overall relationship, there is positive relationship but for each location level, some have positive and some have negative and some have no relationship.

Let's see acc_nights and inter_dep.

Same as acc_nights and inter_arr.

Lastly, let' see inter_arr and inter_dep.

I see inter_arr and inter_dep have positive relationship.

That's it for this post. Thank you!

Next post is

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