--- title: "Prerunner" author: "Scary Scarecrow" date: "2022-09-05" output: html_document --- ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE) library(shinymanager) library(tidystringdist) library(tidyverse) ``` ## Credentials ```{r cars} credentials <- data.frame( user = c("lanubia", "admin" ,"german","austrian","swiss","chinese","spanish","finnish","italian","dutch","polish","swedish","norwegian"), password = c("lanubia@2021", "adminadmin","german","austrian","swiss","chinese","spanish","finnish","italian","dutch","polish","swedish","norwegian"), country = c("All","All","DE","AT","CZ","CN","ES","FI","IT","NL","PL","SE","NO"), admin = c(TRUE, TRUE, rep(FALSE,11)), stringsAsFactors = FALSE ) data.frame(user, password) dat<-c("1", "4545", "1", "6", "4000", "Europe", "2", "3565", "5", "8", "5450", "Asia", "3", "4646", "1", "5", "3455", "Europe") str(dat) number_of_columns<-6 number_of_rows<-length(dat)/number_of_columns data.frame(matrix(dat, nrow = number_of_rows)) ``` ## Including Plots You can also embed plots, for example: ```{r pressure, echo=FALSE} create_db( credentials_data = credentials, sqlite_path = "credentials.sqlite", # will be created # passphrase = key_get("R-shinymanager-key", "KjnsduYgrajidi(87368()*7726Gdjicjs") passphrase = "KjnsduYgrajidi(87368()*7726Gdjicjs" ) iris |> filter(Species %in% c("setosa","versicolor")) ``` Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot. ```{r} # Duplicates accfilepath <- list.files("./accounts/output", pattern = "*_Account.csv", full.names = T) accfiles <- lapply(accfilepath, read.csv) accdf <- unique(do.call(ltodf, accfiles)) accdf$source<-"legacy" accdfn<-read.csv("account.csv") ``` ```{r} colnames(accdf) accdf<- accdf |> select(External_Key, Name, source, CountryRegion) ``` ```{r} colnames(accdfn) accdf<- accdfn |> select(External_ID, Name, CountryRegion) |> mutate(source="ERP") |> rename(External_Key=External_ID) |> rbind(accdf) mat<-accdf |> tidy_comb_all(Name) |> tidy_stringdist() mat<- mat |> filter(cosine < 0.05) |> # Set a threshold pivot_longer(starts_with("V"), names_to = "x", values_to = "match") |> pull(match) accdf %>% filter(Name %in% mat) %>% arrange(Name) |> write.csv("./accounts/errors/accdup.csv", row.names = FALSE) read.csv("./accounts/errors/accdup.csv") ``` ```{r} contfilepath <- list.files("./contacts/output", pattern = "*_Contact.csv", full.names = T) contfiles <- lapply(contfilepath, read.csv) contdf <- unique(do.call(ltodf, contfiles)) contdf<-contdf |> mutate(Name=paste0(First_Name," ", Last_Name)) |> mutate(source="legacy") |> select(External_Key, Name, EMail, source, CountryRegion) condfn<-read.csv("contact.csv") contdf<- condfn |> mutate(Name=paste0(First_Name," ", Last_Name)) |> mutate(source="ERP") |> select(External_ID,Name, EMail, source, CountryRegion) |> rename(External_Key=External_ID) |> rbind(contdf) mat<-contdf |> tidy_comb_all(Name) |> tidy_stringdist() mat<- mat |> filter(cosine < 0.03) |> # Set a threshold pivot_longer(starts_with("V"), names_to = "x", values_to = "match") |> pull(match) cinddupname<- contdf %>% filter(Name %in% mat) %>% arrange(Name) mat<-contdf |> tidy_comb_all(EMail) |> tidy_stringdist() mat<- mat |> filter(cosine < 0.02) |> # Set a threshold pivot_longer(starts_with("V"), names_to = "x", values_to = "match") |> pull(match) cinddupemail<- contdf %>% filter(EMail %in% mat) %>% arrange(EMail) rbind(cinddupname, cinddupemail) |> unique() |> write.csv("./contacts/errors/condup.csv", row.names = FALSE) ``` ```{r} # cdecaded520d57cd dsn_database<-"postgres" dsn_hostname<-"localhost" dsn_port<-"5432" dsn_uid<- "postgres" dsn_pwd<-"julley09" library(RPostgres) connec <- dbConnect( RPostgres::Postgres(), dbname = dsn_database, host = dsn_hostname, port = dsn_port, user = dsn_uid, password = dsn_pwd ) emp<-read.csv("empmissinginsap.csv") |> mutate(action=NA) emp_cn<-emp |> filter(CountryRegion=="CN") emp_cz<-emp |> filter(CountryRegion=="CZ") emp_de<-emp |> filter(CountryRegion=="DE") emp_es<-emp |> filter(CountryRegion=="ES") emp_fi<-emp |> filter(CountryRegion=="FI") emp_it<-emp |> filter(CountryRegion=="IT") emp_nl<-emp |> filter(CountryRegion=="NL") emp_no<-emp |> filter(CountryRegion=="NO") emp_pl<-emp |> filter(CountryRegion=="PL") emp_se<-emp |> filter(CountryRegion=="SE") dbWriteTable(connec, "crh_emp_cn", emp_cn, append=TRUE) dbWriteTable(connec, "crh_emp_cz", emp_cz, append=TRUE) dbWriteTable(connec, "crh_emp_de", emp_de, append=TRUE) dbWriteTable(connec, "crh_emp_es", emp_es, append=TRUE) dbWriteTable(connec, "crh_emp_fi", emp_fi, append=TRUE) dbWriteTable(connec, "crh_emp_it", emp_it, append=TRUE) dbWriteTable(connec, "crh_emp_nl", emp_nl, append=TRUE) dbWriteTable(connec, "crh_emp_no", emp_no, append=TRUE) dbWriteTable(connec, "crh_emp_pl", emp_pl, append=TRUE) dbWriteTable(connec, "crh_emp_se", emp_se, append=TRUE) dbWriteTable(connec, "crh_emp", emp, append=TRUE) dupacc<-read.csv("duplicateaccounts.csv") |> mutate(action=NA) dupacc_cn<-emp |> filter(CountryRegion=="CN") dupacc_cz<-emp |> filter(CountryRegion=="CZ") dupacc_de<-emp |> filter(CountryRegion=="DE") dupacc_es<-emp |> filter(CountryRegion=="ES") dupacc_fi<-emp |> filter(CountryRegion=="FI") dupacc_it<-emp |> filter(CountryRegion=="IT") dupacc_nl<-emp |> filter(CountryRegion=="NL") dupacc_no<-emp |> filter(CountryRegion=="NO") dupacc_pl<-emp |> filter(CountryRegion=="PL") dupacc_se<-emp |> filter(CountryRegion=="SE") dbWriteTable(connec, "crh_dupacc_cn", dupacc_cn, append=TRUE) dbWriteTable(connec, "crh_dupacc_cz", dupacc_cz, append=TRUE) dbWriteTable(connec, "crh_dupacc_de", dupacc_de, append=TRUE) dbWriteTable(connec, "crh_dupacc_es", dupacc_es, append=TRUE) dbWriteTable(connec, "crh_dupacc_fi", dupacc_fi, append=TRUE) dbWriteTable(connec, "crh_dupacc_it", dupacc_it, append=TRUE) dbWriteTable(connec, "crh_dupacc_nl", dupacc_nl, append=TRUE) dbWriteTable(connec, "crh_dupacc_no", dupacc_no, append=TRUE) dbWriteTable(connec, "crh_dupacc_pl", dupacc_pl, append=TRUE) dbWriteTable(connec, "crh_dupacc_se", dupacc_se, append=TRUE) dupcon<-read.csv("duplicatecontacts.csv") |> mutate(action=NA) dupcon_cn<-emp |> filter(CountryRegion=="CN") dupcon_cz<-emp |> filter(CountryRegion=="CZ") dupcon_de<-emp |> filter(CountryRegion=="DE") dupcon_es<-emp |> filter(CountryRegion=="ES") dupcon_fi<-emp |> filter(CountryRegion=="FI") dupcon_it<-emp |> filter(CountryRegion=="IT") dupcon_nl<-emp |> filter(CountryRegion=="NL") dupcon_no<-emp |> filter(CountryRegion=="NO") dupcon_pl<-emp |> filter(CountryRegion=="PL") dupcon_se<-emp |> filter(CountryRegion=="SE") dbWriteTable(connec, "crh_dupcon_cn", dupcon_cn, append=TRUE) dbWriteTable(connec, "crh_dupcon_cz", dupcon_cz, append=TRUE) dbWriteTable(connec, "crh_dupcon_de", dupcon_de, append=TRUE) dbWriteTable(connec, "crh_dupcon_es", dupcon_es, append=TRUE) dbWriteTable(connec, "crh_dupcon_fi", dupcon_fi, append=TRUE) dbWriteTable(connec, "crh_dupcon_it", dupcon_it, append=TRUE) dbWriteTable(connec, "crh_dupcon_nl", dupcon_nl, append=TRUE) dbWriteTable(connec, "crh_dupcon_no", dupcon_no, append=TRUE) dbWriteTable(connec, "crh_dupcon_pl", dupcon_pl, append=TRUE) dbWriteTable(connec, "crh_dupcon_se", dupcon_se, append=TRUE) unique(dupcon$CountryRegion) ``` ```{r} dupcon |> filter(FullName =="Mireille Ramez") ```