all period to date functions work and pass tests

Author: hagan

R/abc.R

@@ -158,7 +158,6 @@ abc_fn <- function(x){
     dplyr::select(
       -dist_rank,
       -category_value,
-      -row_id,
       -max_row_id,
       -cum_unit_prop
     )

R/utils-sql.R

@@ -49,7 +49,7 @@ seq_date_sql <- function(start_date, end_date, time_unit, .con) {
 
   # 2. Variable Prep -------------------------------------------------------
   unit <- tolower(time_unit)
-  is_duckdb_pg <- inherits(.con, "duckdb_.connection") || inherits(.con, "Pq.connection")
+  is_duckdb_pg <- inherits(.con, "duckdb_connection") || inherits(.con, "Pqconnection")
   is_snowflake <- inherits(.con, "Snowflake")
   is_test      <- inherits(.con, "Test.connection")
 

tests/testthat.R

@@ -0,0 +1,12 @@
+# This file is part of the standard setup for testthat.
+# It is recommended that you do not modify it.
+#
+# Where should you do additional test configuration?
+# Learn more about the roles of various files in:
+# * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
+# * https://testthat.r-lib.org/articles/special-files.html
+
+library(testthat)
+library(fpaR)
+
+test_check("fpaR")

tests/testthat/test-ti.R

@@ -0,0 +1,194 @@
+library(testthat)
+library(dplyr)
+library(lubridate)
+
+# We skip these tests if 'contoso' isn't available, preventing errors on systems without the data
+skip_if_not_installed("contoso")
+
+describe("Year-related functions (YTD)", {
+
+  it("calculates YTD margin with standard calendar (grouped)", {
+    result <- contoso::sales |>
+      group_by(store_key) |>
+      ytd(order_date, margin, "standard") |>
+      calculate() |>
+      collect()
+
+    expect_s3_class(result, "data.frame")
+    expect_true("ytd_margin" %in% names(result))
+    expect_gt(nrow(result), 0)
+  })
+
+  it("calculates YTD margin with 445 calendar (grouped by customer)", {
+    result <- contoso::sales |>
+      group_by(customer_key) |>
+      ytd(order_date, margin, "445") |>
+      calculate() |>
+      collect() # Added collect() to ensure we get data back
+
+    expect_true("ytd_margin" %in% names(result))
+    expect_gt(nrow(result), 0)
+  })
+})
+
+describe("Quarter, Month, Week to Date (QTD, MTD, WTD)", {
+
+  it("calculates QTD, MTD, WTD correctly", {
+    # QTD Standard
+    res_qtd <- contoso::sales |>
+      qtd(order_date, margin, "standard") |>
+      calculate() |>
+      collect()
+    expect_true("qtd_margin" %in% names(res_qtd))
+
+    # MTD 445
+    res_mtd <- contoso::sales |>
+      mtd(order_date, margin, "445") |>
+      calculate() |>
+      collect()
+    expect_true("mtd_margin" %in% names(res_mtd))
+
+    # WTD Standard
+    res_wtd <- contoso::sales |>
+      wtd(order_date, margin, "standard") |>
+      calculate() |>
+      collect()
+    expect_true("wtd_margin" %in% names(res_wtd))
+  })
+
+  it("calculates ATD (All-to-date)", {
+    result <- contoso::sales |>
+      group_by(store_key) |>
+      atd(order_date, margin, "445") |>
+      calculate() |>
+      collect()
+
+    expect_true("atd_margin" %in% names(result))
+  })
+})
+
+describe("Period Over Period (YOY, QOQ, MOM, WOW, DOD)", {
+
+  it("calculates YOY margin and filters specific store", {
+    result <- contoso::sales |>
+      group_by(store_key) |>
+      yoy(order_date, margin, "standard", 1) |>
+      calculate() |>
+      collect() |> # Collect before filtering in R if strictly checking logic, or keep lazy if supported
+      filter(store_key == "999999")
+
+    expect_true("yoy_margin" %in% names(result))
+  })
+
+  it("calculates QOQ, MOM, WOW, DOD", {
+    # QOQ
+    res_qoq <- contoso::sales |> qoq(order_date, margin, "standard") |> calculate() |> collect()
+    expect_true("qoq_margin" %in% names(res_qoq))
+
+    # MOM
+    res_mom <- contoso::sales |> mom(order_date, margin, "445") |> calculate() |> collect()
+    expect_true("mom_margin" %in% names(res_mom))
+
+    # WOW
+    res_wow <- contoso::sales |> wow(order_date, margin, "standard") |> calculate() |> collect()
+    expect_true("wow_margin" %in% names(res_wow))
+
+    # DOD
+    res_dod <- contoso::sales |> dod(order_date, margin, "standard") |> calculate() |> collect()
+    expect_true("dod_margin" %in% names(res_dod))
+  })
+})
+
+describe("Prior Period to Current YTD/QTD/MTD", {
+
+  it("calculates YOYTD (Year Over Year To Date)", {
+    result <- contoso::sales |>
+      fpaR::yoytd(order_date, margin, "standard", 1) |>
+      calculate() |>
+      collect()
+
+    expect_true("pytd_margin" %in% names(result)) # Based on your filter snippet
+    expect_true("ytd_margin" %in% names(result))
+  })
+
+  it("calculates QOQTD and MOMTD", {
+    # QOQTD
+    res_qoqtd <- contoso::sales |> fpaR::qoqtd(order_date, margin, "standard", 1) |> calculate() |> collect()
+    expect_true("pqtd_margin" %in% names(res_qoqtd))
+
+    # MOMTD
+    res_momtd <- contoso::sales |> fpaR::momtd(order_date, margin, "standard", 1) |> calculate() |> collect()
+    expect_true("pmtd_margin" %in% names(res_momtd))
+  })
+
+  it("calculates WOWTD", {
+    result <- contoso::sales |>
+      fpaR::wowtd(order_date, margin, calendar_type = "standard", lag_n = 1) |>
+      calculate() |>
+      collect()
+
+    expect_s3_class(result, "data.frame")
+  })
+})
+
+describe("Prior To Date Functions (PYTD, PQTD, PMTD, PWTD)", {
+
+  it("calculates pure Prior YTD/QTD/MTD/WTD columns", {
+    # PYTD
+    res_pytd <- contoso::sales |> fpaR::pytd(order_date, margin, "standard", 1) |> calculate() |> collect()
+    expect_true("pytd_margin" %in% names(res_pytd))
+
+    # PQTD
+    res_pqtd <- contoso::sales |> fpaR::pqtd(order_date, margin, "standard", 1) |> calculate() |> collect()
+    expect_true("pqtd_margin" %in% names(res_pqtd))
+
+    # PWTD
+    res_pwtd <- contoso::sales |> fpaR::pwtd(order_date, margin, "standard", 1) |> calculate() |> collect()
+    expect_true("pwtd_margin" %in% names(res_pwtd))
+  })
+})
+
+describe("Complex Comparisons (YTDOPY, MTDOPM, etc)", {
+
+  it("calculates YTD over Prior Year", {
+    result <- contoso::sales |>
+      fpaR::ytdopy(order_date, margin, calendar_type="standard", lag_n = 1) |>
+      calculate() |>
+      collect()
+
+    expect_true("yoy_margin" %in% names(result))
+  })
+
+  it("calculates MTD over Prior Month", {
+    result <- contoso::sales |>
+      fpaR::mtdopm(order_date, margin, calendar_type="standard", lag_n = 1) |>
+      calculate() |>
+      collect()
+
+    expect_true("mom_margin" %in% names(result))
+  })
+})
+
+describe("Special Functions (ABC, Cohort)", {
+
+  it("performs ABC analysis", {
+    result <- contoso::sales |>
+      group_by(store_key) |>
+      fpaR::abc(category_values = c(.3,.5,.7,.8), .value = margin) |>
+      calculate() |>
+      collect()
+
+    # Typically ABC adds a category/class column, check for that or the value
+    expect_gt(nrow(result), 0)
+  })
+
+  it("performs Cohort analysis", {
+    result <- contoso::sales |>
+      group_by(store_key) |>
+      fpaR::cohort(.date = order_date, .value = margin, time_unit = "month", period_label = FALSE) |>
+      calculate() |>
+      collect()
+
+    expect_gt(nrow(result), 0)
+  })
+})

vignettes/articles/abc.qmd

@@ -28,7 +28,7 @@ The `abc()` function applies this method by ranking group members according to e
 
 **Value Capture**  
 
--  If `.value` is provided, then that column is aggregate per group member; otherwise, it counts rows
+-  If `.value` is provided, then that column is aggregated per group member; otherwise, it counts rows
 
 **Category Values**
 
@@ -160,7 +160,7 @@ tibble::tibble(
     "The cumulative proportion of the total, showing the running total percentage of the entire dataset as you move through the rows.",
     "The unique identifier for the row, often used to track or identify specific rows in the dataset. Typically sequential ID or index.",
     "The maximum row ID in the current group (if grouping is applied), representing the total number of rows in the group.",
-    "The cumulative proportion of the unit values, similar to cum_prop_total, but typically used when the unit is treated as aggregate.",
+    "The cumulative proportion of the unit values, similar to cum_prop_total, but typically used when the unit is aggregated.",
     "The category value that corresponds to the cumulative proportion break points (e.g., top 10%, top 40%, etc.). Based on the break points provided.",
     "The name of the category assigned to each row based on the cumulative contribution. Categories are represented by letters (A, B, C, etc.)."
   ),

vignettes/articles/cohort.qmd

@@ -25,7 +25,7 @@ The `cohort()` function in **fpaR** provides a **tibble and database-friendly im
 
 - Assigns each member in your dataset to a **time-based cohort** based on the first occurrence in the `.date` column
 - Aggregates distinct counts of cohort members over time
-- Supports multiple calendar types (`"standard"` or a non-standard calendar `"544"`) and `time_unit` (`day`, `week`, `month`, `quarter`, `year`)
+- Supports multiple time units (`day`, `week`, `month`, `quarter`, `year`)
 - Returns a **segment object**, which can be processed using `calculate()` to generate the cohort table
 
 # Arguments
@@ -35,8 +35,7 @@ The `cohort()` function in **fpaR** provides a **tibble and database-friendly im
 | `.data` | A `tibble` or DBI object containing your dataset. |
 | `.date` | The date column to base the cohort assignment on. |
 | `.value` | The column representing members to track (e.g., customer ID). |
-| `calendar_type` | Type of calendar to use for aggregation: `"standard"` or `"554"`. |
-| `time_unit` | Time unit to summarize the cohort table by (`day`, `week`, `month`, `quarter`, `year`). Default is `"month"`. |
+| `time_unit` | Argument to group your calendar dates: `day`, `week`,`month`,`quarter` or `year` |
 | `period_label` | Whether to use numeric period labels (`TRUE`) or actual dates (`FALSE`). Default is `FALSE`. |
 
 
@@ -52,7 +51,6 @@ The function returns a **segment_cohort** object. Use `calculate()` to retrieve
 fpaR::cohort(.data = contoso::sales,
                   .date = order_date,
                   .value = customer_key,
-                  calendar_type = "standard",
                   time_unit = "month",
                   period_label = FALSE
              )