Saraswathi Analytics provides Visual Analytics Week 6 solution (Visual Analytics - 202051 - CRN140).

Building Layered Visualizations

  1. 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?
  2. create a graph that shows a count of religious preferences grouped by region
  3. turn the region counts in percentages
  4. use dodge2() to put the religious affiliations side by side within regions
  5. show the religious preferences by region, faceted version with the coordinate system swapped
  6. using pipes show a 10 random instances of the first six columns in the organdata data set
  7. create a scatterplot of donors vs. year
  8. create a faceted set of line chart graphs showing donors for year for different countries
  9. 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). 10. Replace the boxplot with points
  10. jitter the points
  11. reduce the amount of jitter
  12. 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)
  13. what is the cerebvas column referring to?
  14. What conclusions can you draw from the previous plot?

Submit a Word document by Sunday at midnight with screen shots of your work and text. Explain what each image is.

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.

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