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| #### Function for uniquely matching features between two datasets #### | |
| # | |
| # 1) computing features similarity matrix | |
| # 2) assigning fatures across the two datasets (Hungarian algorithm) | |
| # 3) returning a | |
| #requires clue for the Hungarian algorithm | |
| library(clue) |
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| http://jianghao.wang/post/2017-12-08-rmarkdown-templates/#r-packages |
snakecaseby @Tazmaaanggstatsplotsby @patilindrajeetsresembleby @
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| #!/usr/bin/env bash | |
| # author: cgpu | |
| # *NOTE*: | |
| # PLEASE FIND ATTACHED AT THE tail OF THE FILE AN APPENDIX OF | |
| # TASKS/COMMANDS THAT WERE PERFORMED OUTSIDE OF THE .sh FILE FOR THE CRONJOB. | |
| # STEP 0: | |
| #___________________________________________________________________________________________________________________ |
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| EDAtoR <- function(df){ | |
| DT::datatable( (utils::str(df)), escape = FALSE, filter = 'bottom') ) | |
| DT::datatable( print(skimr::skim(df)), escape = FALSE, filter = 'bottom') ) | |
| DT::datatable( print(base::summary(df)), escape = FALSE, filter = 'bottom') ) | |
| DT::datatable( print(dplyr::glimpse(df)), escape = FALSE, filter = 'bottom') ) | |
| plot(visdat::vis_dat(df)) | |
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| # WHAT | Under the hood #datasci starter pack-ages 📦 installation | |
| # WHY | To de-clutter code - Use at own(er's) risk | |
| sourceRy <- function(){ | |
| if (!require("librarian")) install.packages("librarian", | |
| dependencies = TRUE, | |
| quiet = TRUE) | |
| librarian::shelf( | |
| # CRAN |
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| https://stackoverflow.com/questions/4860417/placing-custom-images-in-a-plot-window-as-custom-data-markers-or-to-annotate-t |
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| Numextract <- function(string){ unlist(regmatches(string,gregexpr("[[:digit:]]+\\.*[[:digit:]]*",string)))} |
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| my_color_palette = c( '#da627d', #pinkpanther | |
| '#2d3047', #nightblue | |
| '#f46036', #brickorange | |
| '#5b85aa', #mellowlightblue | |
| '#9c528b', #purple | |
| '#ffae19', #mustardyellow | |
| '#c0c0c0') #coconutash | |