Visualizing Female Proportion Borrowing
The return type of functions in the bigtabulate
and biganalytics
packages are base R types that can be used just like you would with any analysis. This means that we can visualize results using ggplot2
.
In this exercise, you will visualize the female proportion borrowing for urban and rural areas across all years.
This exercise is part of the course
Scalable Data Processing in R
Exercise instructions
The matrix prop_female
from the previous exercise is available in your workspace.
- Load the
tidyr
andggplot2
packages. - Convert
prop_female
to a data frame usingas.data.frame()
. - Add a new column,
Year
. Set it to therow.names()
ofprop_female_df
. - Call
pivot_longer()
on the columns ofprop_female_df
to convert it into a long format.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Load the tidyr and ggplot2 packages
___
___
# Convert prop_female to a data frame
prop_female_df <- ___
# Add a new column Year
prop_female_df$Year <- ___
# Call pivot_longer on prop_female_df
prop_female_long <- ___(prop_female_df, -Year, names_to = "Region", values_to = "Prop")
# Create a line plot
ggplot(prop_female_long, aes(x = Year, y = Prop, group = Region, color = Region)) +
geom_line()