crosshyou

主にクロス表(分割表)分析をしようかなと思いはじめましたが、あまりクロス表の分析はできず。R言語の練習ブログになっています。

OECD Young self-employed data analysis 2 - data visualization with ggplot2 package, geom_point(), geom_line(), geom_boxplot and geom_histogram() and geom_bar().

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This posit is following of above post.
Let's see data on some graphs.

I use ggplot2 package which is included in tidyverse package.

gerom_point() function makes scatter plot. I see men has higher self-employed percentage than women in general.

Next, let's see which LOCATION has the higest/lowest value.

JPN has extremely low percentge and ZAF hs the higest percentage.

Next, let's see trend line by LOCATION

Next, let's see women trend

I don't see typical time trend.

Next, let's see histograms.

mem's value has wider spread.

Next, let's see which LOCATION has the largest observations.

NLD, ITA, GRC and ESP hve the largest observations.

In this post, I use ggplot2 package to vizualization.
geom_point() for scatter plot,

geom_line() for line chart,

geom_boxplot() for box plot,

geom_histogram() for histogram and

geom_bar() for bar chart.

That's it. Thank you!

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