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cohortBuilder provides common API for creating cohorts
on multiple data sources, such as local data frame, database schema or
external data api.
With only two steps:
set_source.cohort.You can operate on data using common methods, such as:
filter - to define and run to apply
filtering rules,step - to perform multi-stage filtering,get_data, stat, attrition,
plot_data - to extract, sum up or visualize your cohort
data.With cohortBuilder you can share the cohort easier with
useful methods:
code - to get reproducible cohort creation code,get_state - to get cohort state (e.g. in JSON) that can
be then easily restored with restore.Or modify the cohort configuration with:
add_filter, rm_filter,
update_filter - to manage filters definitionadd_step, rm_step - to manage filtering
steps,update_source - to manage the cohort source.The goal of cohortBuilder is to provide common API for
creating data cohorts, but also to be easily extendable for working on
different data sources (and interactive dashboards).
cohortBuilder allows to operate on local data frames (or
list of data frames), yet you may easily switch to a database source by
loading cohortBuilder.db layer.
As a standalone R package, you use cohortBuilder to
perform all the operations in non-interactive R script, but its shiny
layer shinyCohortBuilder package helps you to easily switch
to intuitive gui mode. More to that you may integrate
cohortBuilder with your custom Shiny application.
If you want to learn how to write custom source extension, please
check vignette("custom-extensions").
# CRAN version
install.packages("cohortBuilder")
# Latest development version
remotes::install_github("https://github.com/r-world-devs/cohortBuilder")librarian_source <- set_source(
as.tblist(librarian)
)
coh <- librarian_source %>%
cohort(
filter(
"discrete", id = "author", dataset = "books",
variable = "author", value = "Dan Brown"
),
filter(
"range", id = "copies", dataset = "books",
variable = "copies", range = c(5, 10)
),
filter(
"date_range", id = "registered", dataset = "borrowers",
variable = "registered", range = c(as.Date("2010-01-01"), Inf)
)
) %>%
run()
get_data(coh)
#> $books
#> # A tibble: 1 × 6
#> isbn title genre publisher
#> <chr> <chr> <chr> <chr>
#> 1 0-385-50420-9 The Da Vinci Code Crime, Thriller & Adventure Transworld
#> author copies
#> <chr> <int>
#> 1 Dan Brown 7
#>
#> $borrowers
#> # A tibble: 8 × 6
#> id registered address
#> <chr> <date> <chr>
#> 1 000013 2011-09-30 534 Iroquois Ave. Watertown, MA 02472
#> 2 000014 2013-01-12 7968 Victoria Drive Dearborn, MI 48124
#> 3 000015 2013-12-24 9484 Somerset Road Romeoville, IL 60446
#> 4 000016 2014-01-20 48 Prairie Ave. Palos Verdes Peninsula, CA 90274
#> 5 000017 2014-04-07 8501 Lawrence Rd. Terre Haute, IN 47802
#> name phone_number program
#> <chr> <chr> <chr>
#> 1 Dr. Sharif Kunde 104-832-8013 premium
#> 2 Marlena Reichert PhD 044-876-8419 vip
#> 3 Mr. Brandan Oberbrunner 568-044-7463 vip
#> 4 Lloyd Adams III 001-017-0211 standard
#> 5 Randy Ziemann 895-995-2326 premium
#> # ℹ 3 more rows
#>
#> $issues
#> # A tibble: 50 × 4
#> id borrower_id isbn date
#> <chr> <chr> <chr> <date>
#> 1 000001 000019 0-676-97976-9 2015-03-17
#> 2 000002 000010 978-0-7528-6053-4 2008-09-13
#> 3 000003 000016 0-09-177373-3 2014-09-28
#> 4 000004 000005 0-224-06252-2 2005-11-14
#> 5 000005 000004 0-340-89696-5 2006-03-19
#> # ℹ 45 more rows
#>
#> $returns
#> # A tibble: 30 × 2
#> id date
#> <chr> <date>
#> 1 000001 2015-04-06
#> 2 000003 2014-10-23
#> 3 000004 2005-12-29
#> 4 000005 2006-03-26
#> 5 000006 2016-08-30
#> # ℹ 25 more rows
#>
#> attr(,"class")
#> [1] "tblist"
#> attr(,"call")
#> as.tblist(librarian)coh <- librarian_source %>%
cohort() %->%
step(
filter(
"discrete", id = "author", dataset = "books",
variable = "author", value = "Dan Brown"
),
filter(
"date_range", id = "registered", dataset = "borrowers",
variable = "registered", range = c(as.Date("2010-01-01"), Inf)
)
) %->%
step(
filter(
"range", id = "copies", dataset = "books",
variable = "copies", range = c(5, 10)
)
) %>%
run()get_data(coh, step_id = 1)
#> $books
#> # A tibble: 2 × 6
#> isbn title genre publisher
#> <chr> <chr> <chr> <chr>
#> 1 0-385-50420-9 The Da Vinci Code Crime, Thriller & Adventure Transworld
#> 2 0-671-02735-2 Angels and Demons Crime, Thriller & Adventure Transworld
#> author copies
#> <chr> <int>
#> 1 Dan Brown 7
#> 2 Dan Brown 4
#>
#> $borrowers
#> # A tibble: 8 × 6
#> id registered address
#> <chr> <date> <chr>
#> 1 000013 2011-09-30 534 Iroquois Ave. Watertown, MA 02472
#> 2 000014 2013-01-12 7968 Victoria Drive Dearborn, MI 48124
#> 3 000015 2013-12-24 9484 Somerset Road Romeoville, IL 60446
#> 4 000016 2014-01-20 48 Prairie Ave. Palos Verdes Peninsula, CA 90274
#> 5 000017 2014-04-07 8501 Lawrence Rd. Terre Haute, IN 47802
#> name phone_number program
#> <chr> <chr> <chr>
#> 1 Dr. Sharif Kunde 104-832-8013 premium
#> 2 Marlena Reichert PhD 044-876-8419 vip
#> 3 Mr. Brandan Oberbrunner 568-044-7463 vip
#> 4 Lloyd Adams III 001-017-0211 standard
#> 5 Randy Ziemann 895-995-2326 premium
#> # ℹ 3 more rows
#>
#> $issues
#> # A tibble: 50 × 4
#> id borrower_id isbn date
#> <chr> <chr> <chr> <date>
#> 1 000001 000019 0-676-97976-9 2015-03-17
#> 2 000002 000010 978-0-7528-6053-4 2008-09-13
#> 3 000003 000016 0-09-177373-3 2014-09-28
#> 4 000004 000005 0-224-06252-2 2005-11-14
#> 5 000005 000004 0-340-89696-5 2006-03-19
#> # ℹ 45 more rows
#>
#> $returns
#> # A tibble: 30 × 2
#> id date
#> <chr> <date>
#> 1 000001 2015-04-06
#> 2 000003 2014-10-23
#> 3 000004 2005-12-29
#> 4 000005 2006-03-26
#> 5 000006 2016-08-30
#> # ℹ 25 more rows
#>
#> attr(,"class")
#> [1] "tblist"
#> attr(,"call")
#> as.tblist(librarian)get_data(coh, step_id = 2)
#> $books
#> # A tibble: 1 × 6
#> isbn title genre publisher
#> <chr> <chr> <chr> <chr>
#> 1 0-385-50420-9 The Da Vinci Code Crime, Thriller & Adventure Transworld
#> author copies
#> <chr> <int>
#> 1 Dan Brown 7
#>
#> $borrowers
#> # A tibble: 8 × 6
#> id registered address
#> <chr> <date> <chr>
#> 1 000013 2011-09-30 534 Iroquois Ave. Watertown, MA 02472
#> 2 000014 2013-01-12 7968 Victoria Drive Dearborn, MI 48124
#> 3 000015 2013-12-24 9484 Somerset Road Romeoville, IL 60446
#> 4 000016 2014-01-20 48 Prairie Ave. Palos Verdes Peninsula, CA 90274
#> 5 000017 2014-04-07 8501 Lawrence Rd. Terre Haute, IN 47802
#> name phone_number program
#> <chr> <chr> <chr>
#> 1 Dr. Sharif Kunde 104-832-8013 premium
#> 2 Marlena Reichert PhD 044-876-8419 vip
#> 3 Mr. Brandan Oberbrunner 568-044-7463 vip
#> 4 Lloyd Adams III 001-017-0211 standard
#> 5 Randy Ziemann 895-995-2326 premium
#> # ℹ 3 more rows
#>
#> $issues
#> # A tibble: 50 × 4
#> id borrower_id isbn date
#> <chr> <chr> <chr> <date>
#> 1 000001 000019 0-676-97976-9 2015-03-17
#> 2 000002 000010 978-0-7528-6053-4 2008-09-13
#> 3 000003 000016 0-09-177373-3 2014-09-28
#> 4 000004 000005 0-224-06252-2 2005-11-14
#> 5 000005 000004 0-340-89696-5 2006-03-19
#> # ℹ 45 more rows
#>
#> $returns
#> # A tibble: 30 × 2
#> id date
#> <chr> <date>
#> 1 000001 2015-04-06
#> 2 000003 2014-10-23
#> 3 000004 2005-12-29
#> 4 000005 2006-03-26
#> 5 000006 2016-08-30
#> # ℹ 25 more rows
#>
#> attr(,"class")
#> [1] "tblist"
#> attr(,"call")
#> as.tblist(librarian)update_filter(
coh, step_id = 1, filter_id = "author",
range = c(5, 6)
)
run(coh)
get_data(coh, step_id = 2)
#> $books
#> # A tibble: 1 × 6
#> isbn title genre publisher
#> <chr> <chr> <chr> <chr>
#> 1 0-385-50420-9 The Da Vinci Code Crime, Thriller & Adventure Transworld
#> author copies
#> <chr> <int>
#> 1 Dan Brown 7
#>
#> $borrowers
#> # A tibble: 8 × 6
#> id registered address
#> <chr> <date> <chr>
#> 1 000013 2011-09-30 534 Iroquois Ave. Watertown, MA 02472
#> 2 000014 2013-01-12 7968 Victoria Drive Dearborn, MI 48124
#> 3 000015 2013-12-24 9484 Somerset Road Romeoville, IL 60446
#> 4 000016 2014-01-20 48 Prairie Ave. Palos Verdes Peninsula, CA 90274
#> 5 000017 2014-04-07 8501 Lawrence Rd. Terre Haute, IN 47802
#> name phone_number program
#> <chr> <chr> <chr>
#> 1 Dr. Sharif Kunde 104-832-8013 premium
#> 2 Marlena Reichert PhD 044-876-8419 vip
#> 3 Mr. Brandan Oberbrunner 568-044-7463 vip
#> 4 Lloyd Adams III 001-017-0211 standard
#> 5 Randy Ziemann 895-995-2326 premium
#> # ℹ 3 more rows
#>
#> $issues
#> # A tibble: 50 × 4
#> id borrower_id isbn date
#> <chr> <chr> <chr> <date>
#> 1 000001 000019 0-676-97976-9 2015-03-17
#> 2 000002 000010 978-0-7528-6053-4 2008-09-13
#> 3 000003 000016 0-09-177373-3 2014-09-28
#> 4 000004 000005 0-224-06252-2 2005-11-14
#> 5 000005 000004 0-340-89696-5 2006-03-19
#> # ℹ 45 more rows
#>
#> $returns
#> # A tibble: 30 × 2
#> id date
#> <chr> <date>
#> 1 000001 2015-04-06
#> 2 000003 2014-10-23
#> 3 000004 2005-12-29
#> 4 000005 2006-03-26
#> 5 000006 2016-08-30
#> # ℹ 25 more rows
#>
#> attr(,"class")
#> [1] "tblist"
#> attr(,"call")
#> as.tblist(librarian)code(coh)
#> .pre_filtering <- function(source, data_object, step_id) {
#> for (dataset in names(data_object)) {
#> attr(data_object[[dataset]], "filtered") <- FALSE
#> }
#> return(data_object)
#> }
#> .run_binding <- function(source, binding_key, data_object_pre, data_object_post,
#> ...) {
#> binding_dataset <- binding_key$update$dataset
#> dependent_datasets <- names(binding_key$data_keys)
#> active_datasets <- data_object_post %>%
#> purrr::keep(~attr(., "filtered")) %>%
#> names()
#> if (!any(dependent_datasets %in% active_datasets)) {
#> return(data_object_post)
#> }
#> key_values <- NULL
#> common_key_names <- paste0("key_", seq_along(binding_key$data_keys[[1]]$key))
#> for (dependent_dataset in dependent_datasets) {
#> key_names <- binding_key$data_keys[[dependent_dataset]]$key
#> tmp_key_values <- dplyr::distinct(data_object_post[[dependent_dataset]][,
#> key_names, drop = FALSE]) %>%
#> stats::setNames(common_key_names)
#> if (is.null(key_values)) {
#> key_values <- tmp_key_values
#> } else {
#> key_values <- dplyr::inner_join(key_values, tmp_key_values, by = common_key_names)
#> }
#> }
#> data_object_post[[binding_dataset]] <- dplyr::inner_join(switch(as.character(binding_key$post),
#> `FALSE` = data_object_pre[[binding_dataset]], `TRUE` = data_object_post[[binding_dataset]]),
#> key_values, by = stats::setNames(common_key_names, binding_key$update$key))
#> if (binding_key$activate) {
#> attr(data_object_post[[binding_dataset]], "filtered") <- TRUE
#> }
#> return(data_object_post)
#> }
#> source <- list(dtconn = as.tblist(librarian))
#> data_object <- source$dtconn
#> step_id <- "1"
#> pre_data_object <- data_object
#> data_object <- .pre_filtering(source, data_object, "1")
#> data_object[["books"]] <- data_object[["books"]] %>%
#> dplyr::filter(author %in% c("Dan Brown", NA))
#> attr(data_object[["books"]], "filtered") <- TRUE
#> data_object[["borrowers"]] <- data_object[["borrowers"]] %>%
#> dplyr::filter((registered <= Inf & registered >= 14610) | is.na(registered))
#> attr(data_object[["borrowers"]], "filtered") <- TRUE
#> data_object <- .post_filtering(source, data_object, "1")
#> for (binding_key in binding_keys) {
#> data_object <- .run_binding(source, binding_key, pre_data_object, data_object)
#> }
#> step_id <- "2"
#> data_object <- .pre_filtering(source, data_object, "2")
#> data_object[["books"]] <- data_object[["books"]] %>%
#> dplyr::filter((copies <= 10 & copies >= 5) | is.na(copies))
#> attr(data_object[["books"]], "filtered") <- TRUE
#> data_object <- .post_filtering(source, data_object, "2")attrition(coh, dataset = "books")
get_state(coh, json = TRUE)
#> [{"step":"1","filters":[{"range":[5,6],"type":"discrete","id":"author","name":"author","variable":"author","value":"Dan Brown","dataset":"books","keep_na":true,"description":null,"active":true},{"type":"date_range","id":"registered","name":"registered","variable":"registered","range":["2010-01-01","Inf"],"dataset":"borrowers","keep_na":true,"description":null,"active":true}]},{"step":"2","filters":[{"type":"range","id":"copies","name":"copies","variable":"copies","range":[5,10],"dataset":"books","keep_na":true,"description":null,"active":true}]}]Special thanks to:
In a case you found any bugs, have feature request or general question please file an issue at the package Github. You may also contact the package author directly via email at krystian8207@gmail.com.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.