Data Science Desktop Survival Guide by Graham Williams
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Comments

20200105

resume

Use a single # to introduce ordinary comments and separate comments from code with a single empty line before and after the comment. Comments should be full sentences beginning with a capital and ending with a full stop.

Preferred

# How many locations are represented in the dataset.

ds$location %>% unique() %>% length()

# Identify variables that have a single value.

ds[vars] %>%
  sapply(function(x) all(x == x[1L])) %>%
  which() ->
constants

Sections might begin with all uppercase titles and subsections with initial capital titles. The last four dashes at the end of the comment are a section marker supported by . Other conventions are available for structuring a document and different environments support different conventions.

Preferred

# DATA WRANGLING —-

# Normalise Variable Names —-

# Review the names of the dataset columns.

names(ds)

# Normalise variable names and confirm they are as expected.

ds %<>% dplyr::rename_all(rattle::normVarNames)
names(ds)

# Wrangle weatherAUS —-

# Convert the character variable 'date' to a Date data type.

class(ds$date)
ds$date %<>%
  lubridate::ymd() %>%
  as.Date() %T>%
  {class(.); print()}