Following the directions on the Coursera assignment page, you will make four original visualizations. Note that the data for the CCES and CEL data are imported in code in the R Markdown file.

Put your name here: Hsin Chih Chen

Exercise 1

Explain what you are visualizing here:

In this exercise, I have generated random temperature between 15 to 30 degrees Celsius for Taiwan’s major cities in year 2020. The line plot shows each city’s temperature trend respectively.

Put your figure here:

Exercise 2

Explain what you are visualizing here:

This histogram will demonstrate the weight distribution for the Taiwan adult males range from age 15 to age 60.

Put your figure here:

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Exercise 3

Explain what you are visualizing here: This graph shows the scatter plot which demonstrate the correlation between the PM 2.5 level and Ozone level for Tamsui District’s air quality level located in Taiwan. Light theme was applied for this plot.

Put your figure here:

## Warning: 強制變更過程中產生了 NA
## Warning: Removed 25 rows containing missing values (geom_point).

Exercise 4

Explain what you are visualizing here:

This plot is using the cces dataset while recoding the education level and region, then plot the region’s population count based on education level.

Put your figure here: