зеркало из https://github.com/microsoft/wpa.git
refactor: reduce dependencies
A series of changes to satisfy CRAN requirements. This includes reducing the number of dependencies
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@ -16,5 +16,8 @@
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# Ignore all figures
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^man/figures
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# Ignore all vignettes
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^vignettes
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# Ignore vignettes
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^vignettes/best-practices.Rmd$
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^vignettes/Change-over-time.Rmd$
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^vignettes/IV-report.Rmd$
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^vignettes/text-mining-capabilities.Rmd$
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@ -35,7 +35,6 @@ Imports:
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dplyr,
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stats,
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utils,
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tibble,
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tidyr,
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tidyselect (>= 1.0.0),
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magrittr,
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@ -55,7 +54,6 @@ Imports:
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ggraph,
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igraph,
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proxy,
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rlang,
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ggwordcloud,
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methods,
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data.table,
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@ -182,8 +182,6 @@ importFrom(proxy,dist)
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importFrom(purrr,map_if)
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importFrom(purrr,pmap)
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importFrom(purrr,reduce)
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importFrom(rlang,"!!")
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importFrom(rlang,sym)
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importFrom(scales,percent)
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importFrom(scales,wrap_format)
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importFrom(stats,cutree)
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@ -48,7 +48,7 @@ tm_clean <- function(data,
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# Remove WPI custom irrelevant words
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if(!is.data.frame(stopwords)){
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stopwords <- tibble::tibble(word = "")
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stopwords <- dplyr::tibble(word = "")
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}
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@ -303,8 +303,6 @@ workpatterns_hclust <- function(data,
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#'
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#' @import ggplot2
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#' @import dplyr
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#' @importFrom rlang sym
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#' @importFrom rlang "!!"
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#' @importFrom tidyselect all_of
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#' @importFrom tidyr gather
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#'
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@ -449,7 +447,7 @@ run_sum_hr <- function(data,
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mode_val <- uni[which.max(tabulate(match(hour_raw, uni)))]
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tibble::tibble(cluster = x$cluster[1],
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dplyr::tibble(cluster = x$cluster[1],
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median_hour = median(hour_raw),
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p5_hour = stats::quantile(hour_raw, .05),
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p25_hour = stats::quantile(hour_raw, .25),
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@ -29,7 +29,6 @@ To start off using **wpa**, you'll have to load it by running `library(wpa)`. Fo
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```{r message=FALSE, warning=FALSE}
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library(wpa)
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library(dplyr)
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library(tibble)
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library(tidyr)
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```
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