You can install the the development version from GitHub with:
# install.packages("devtools")
-devtools::install_github("CDU-data-science-team/nottshcMethods")Once the package is installed, xaringan presentation slides with Nottinghamshire Healthcare NHS Foundation Trust branding can be access easily using the RStudio IDE, by selecting File -> R markdown ... -> From Template.
as_age_groups.RdCategorise continuous age into age groups
+as_age_groups( + var, + min = 0, + max = 100, + by = 10, + grouping_method = c("user_defined", "ons_1", "ons_2", "nhs_survey") +)+ +
| var | +Name of variable or vector |
+
|---|---|
| min | +Numeric, specifying the minimum age of the first age group. +Age values lower than this will be returned as missing values (NA) |
+
| max | +Numeric, specifying the upper end of the last age group |
+
| by | +Numeric, increment of the age categories |
+
| method | +String, specyfing the method to be used for grouping age into categories. +Details about the different methods are available here: +"user_defined", "ons_1", "ons_2", "nhs_survey" ... TODO |
+
+# Example using a vector: +set.seed(123) +age <- sample(1:100, 100, replace = T) +as_age_groups(age) +#> [1] 30-39 70-79 50-59 10-19 60-69 40-49 50-59 40-49 10-19 20-29 90-99 90-99 +#> [13] 60-69 90-99 50-59 90-99 0-9 90-99 90-99 70-79 20-29 0-9 40-49 0-9 +#> [25] 80-89 30-39 70-79 80-89 40-49 70-79 10-19 30-39 0-9 0-9 40-49 70-79 +#> [37] 20-29 20-29 60-69 50-59 0-9 50-59 20-29 90-99 30-39 80-89 30-39 90-99 +#> [49] 60-69 70-79 70-79 60-69 10-19 80-89 90-99 90-99 20-29 30-39 20-29 70-79 +#> [61] 40-49 40-49 90-99 60-69 90-99 10-19 90-99 0-9 70-79 80-89 80-89 30-39 +#> [73] 30-39 80-89 50-59 30-39 0-9 10-19 60-69 20-29 50-59 20-29 80-89 30-39 +#> [85] 20-29 80-89 30-39 40-49 30-39 10-19 30-39 30-39 60-69 90-99 10-19 90-99 +#> [97] 90-99 70-79 60-69 20-29 +#> Levels: 0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80-89 90-99 100++# Example using a data frame +tibble::tibble(age = sample(1:115, 100, replace = T)) %>% + dplyr::mutate(age_groups = as_age_groups(age, min = 10, max = 100)) +#> Error in tibble::tibble(age = sample(1:115, 100, replace = T)) %>% dplyr::mutate(age_groups = as_age_groups(age, min = 10, max = 100)): could not find function "%>%"
calc_monthly_freq.RdCalculate frequencies of groups per month
+calc_monthly_freq( + data, + by, + date_var_name, + .drop_latest_month = TRUE, + .calc_year_month_day_vars = TRUE +)+ +
| data | +Data |
+
|---|---|
| by | +Grouping variables used in group_by |
+
| date_var_name | +String specifying date variable, needs to be class date |
+
| .drop_latest_month | +Logical, specifying whether or not to drop the most recent month |
+
| .calc_year_month_day_vars | +Logical, specifying whether to calculate separate year, month, and day variable |
+
ggplotly_nottshc.RdThere are some problems with x and y axis labels when converting +ggplot2 to plotly, especially when using facets. This fun has a workaround that is not perfect.
+ggplotly_nottshc( + ggplot, + xtitle = NULL, + ytitle = NULL, + aes_txt_tooltip = TRUE, + display_mode_bar = FALSE +)+ +
| ggplot | +ggplot2 object |
+
|---|---|
| xtitle | +String, x lab title |
+
| ytitle | +String, y lab title |
+
| aes_txt_tooltip | +Logical, specifying whether or not to use tooltip |
+
| display_mode_bar | +Logical, specifying whether to show the annoying +mode bar from plotly, FALSE by default! |
+
Categorise continuous age into age groups
Calculate frequencies of groups per month
Convert ggplot object into plotly
One way hash a vector
CDU data science team ggplot2 theme
sample_vector.RdA ggplot2 theme with a white panel background, no grid lines, +large axis and legend titles, +and increased text padding for better readability.
+sample_vector(values, weights, length)+ +
| values | +Vector- the thing you want to sample from |
+
|---|---|
| weights | +vector of integers the same length as values- the proportions +with which you want to sample |
+
| length | +integer- how long you want the return value to be- e.g. the +number of rows in a dataframe |
+
+sample_vector(values = c(NA, "Male", "Female", "Other"), +weights = c(10, 50, 50, 2), +length = 100) +#> [1] "Other" "Male" "Male" "Male" "Female" "Female" "Female" "Female" +#> [9] "Female" "Female" "Female" "Female" "Female" NA "Male" "Male" +#> [17] "Male" "Male" "Male" "Female" "Male" "Male" "Male" "Male" +#> [25] "Female" "Female" "Female" "Male" "Male" "Male" "Male" "Female" +#> [33] "Male" "Male" "Male" "Female" "Male" "Female" "Male" "Male" +#> [41] "Female" "Female" "Male" "Male" "Male" "Female" "Male" "Female" +#> [49] "Female" "Female" "Female" "Male" "Female" "Female" "Female" "Female" +#> [57] "Male" "Female" "Male" "Female" "Female" "Male" "Female" NA +#> [65] NA "Male" "Male" "Other" "Female" NA "Female" "Male" +#> [73] "Female" "Male" "Female" "Male" NA "Female" "Female" "Male" +#> [81] "Female" "Male" "Male" "Male" "Male" "Female" "Male" "Male" +#> [89] "Female" "Male" "Female" "Male" "Male" "Female" NA "Male" +#> [97] NA "Female" "Female" "Male"+