jeff1evesque / interview-deloitte Goto Github PK
View Code? Open in Web Editor NEWAnalyze fictitious 10K race data
Analyze fictitious 10K race data
We need to adjust our gender coloring dichotomy, when two visualizations are side by side.
We need to analyze how much time separates Chris Doe against the 10% of the same division.
We need to analyze the difference between gun and net time race results.
We need to a visualization between the net and gun time.
We need to determine the mean, median, mode, and range, of the race result for all racers by gender.
We'll assume all logic is correct so far. Therefore, any empty, Unknown
, or NA
rows need to be removed.
We will create main.R
initially to load, then format our provided datasets. This will later be extended to perform various exploratory analytics.
We will split the hometown
column into city
, and state
columns.
We need to fix a docstring typo in munger.R
.
We need to remove any runners with an age < 0.
We will create a barchart to compare the descriptive statistics between gender.
We will add a basic README.md
, as well as remove the unnecessary docx file.
We will create a dedicated package, to contain our current data munging logic.
We need to implement nzchar(Sys.getenv("RSTUDIO_USER_IDENTITY"))
to determine if we are running code in RStudio. This way our implemented dirname(rstudioapi::getSourceEditorContext()$path)
doesn't break our current script.
This issue is similar to jeff1evesque/ist-687#31.
We will add .gitignore
to ignore generated visualizations, as well as R generated files.
We need to relocate the color
aesthetics property within our chris_doe.R
.
We need to reduce the current verbose colname syntax.
We will create a basic deloitte
library.
We forgot to return only the top 10 percentile, in our chris_doe.R
.
We need to adjust the color scale for the female map visualization.
We need to upload the data exercise .
We need to analyze the race results for each division.
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