Visualizing the Adjusted Demographic Trends

Let's compare changes in borrowing across demographics over time. The data frame rydf you created in the last exercise is available in your workspace.

Note: We removed the row corresponding to "Not Avail".

แบบฝึกหัดนี้เป็นส่วนหนึ่งของหลักสูตร

Scalable Data Processing in R

ดูคอร์ส

คำแนะนำการฝึกหัด

tidyr and ggplot2 are loaded in your workspace.

Print the rydf and pop_proportion objects.
Convert rydf to a long-formatted data frame by gathering all columns except Race.
Create a line chart with Year and Adjusted_Count on the x and y axes, respectively.

แบบฝึกหัดเชิงโต้ตอบแบบลงมือทำ

ลองทำแบบฝึกหัดนี้โดยเติมโค้ดตัวอย่างนี้ให้สมบูรณ์

# View rydf
___ 

# View pop_proportion
___

# Gather on all variables except Race
rydfl <- ___(rydf, ___, names_to = "Year", values_to = "Count")

# Create a new adjusted count variable
rydfl$Adjusted_Count <- rydfl$Count / pop_proportion[rydfl$Race]

# Plot
ggplot(rydfl, aes(x = ___, y = ___, group = Race, color = Race)) + 
    geom_line()

แก้ไขและรันโค้ด