University Solutions Hub provides Visual Analytics Week 6 solution
(Visual Analytics).
Week 6: Building Layered Visualizations
- get the structure of the gss_sm dataframe. What is the data type of
race, sex, region and income? What do the levels refer to?
- create a graph that shows a count of religious preferences grouped
by region
- turn the region counts in percentages
- use dodge2() to put the religious affiliations side by side within
regions
- show the religious preferences by region, faceted version with the
coordinate system swapped
- using pipes show a 10 random instances of the first six columns in
the organdata data set
- create a scatterplot of donors vs. year
- create a faceted set of line chart graphs showing donors for year
for different countries
- create a boxplot of the data with coordinates swapped (because the
mean is calculated in every boxplot and because R throws an error when
trying to calculate means when there is missing data, add the na.rm =
TRUE parameter to remove the NA’s).
- Replace the boxplot with points
- jitter the points
- reduce the amount of jitter
- using organdata, create a table of summary statistics by country
called by_country (show the mean of donors, gdp, health, roads,
cerebvas, and the standard deviation of donors)
- what is the cerebvas column referring to?
- What conclusions can you draw from the previous plot?
Note:
- Only for knowledge gain and helping to the students(who are facing
difficulties when solving to the Assessments/ Home works) with their
course support.