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566 lines
19 KiB
566 lines
19 KiB
---
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title: "Untitled"
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output: html_document
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---
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```{r setup, include=FALSE}
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knitr::opts_chunk$set(echo = TRUE)
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library(tidyverse)
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library(lubridate)
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library(fst)
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library(DT)
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library(data.table)
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library(scales)
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# get_png <- function(filename) {
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# grid::rasterGrob(png::readPNG(filename), interpolate = TRUE)
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# }
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# l <- get_png("logo.png")
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# sum.na<-function(x){sum(is.na(x))}
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id<-read.csv("./data/id20210921.csv", sep=";", header = F)
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# alive<-read.csv("active.csv",sep=",")
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# dead<-read.csv("inactive.csv",sep=",")
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oi<-read.fst("./data/open_items_new.fst")
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# oi |> filter(o.type =="Installments") |> filter(due_date>"2021-07-31")
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indi<-id %>%
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filter(V3=="Identiteitsbewijs") %>%
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select(V2,V4)
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dunn<-read.fst("./data/dunning.fst")
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last.dunn<-dunn %>%
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group_by(DUNN_GPART, DUNN_VKONT) %>%
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filter(DUNN_DATE==max(DUNN_DATE)) %>%
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mutate(DUNN_GPART=as.character(DUNN_GPART))
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#dead.org<-read.fst("./data/dead.fst")
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#org.status<-dead.org %>%
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rename(business_partner=V2) %>%
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mutate(type="org", e.status="discontinued") %>%
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select(business_partner,e.status,type)
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#ind.status<-ind.status %>%
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select(business_partner, e.status) %>%
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mutate(type="indi")
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#bp_operating_status<-rbind(org.status,ind.status)
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#write.fst(bp_operating_status,"./data/bp_operating_status.fst")
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operating_status<-read.fst("./data/bp_operating_status.fst")
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# ind.status<-indi %>%
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# left_join(ind.status, by=c("V4"="Id.Nummer")) %>%
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# filter(!is.na(e.status))
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# ind.status %>%
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# rename(business_partner=V2, Id.Number=V4) %>%
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# mutate(business_partner=as.character(business_partner)) %>%
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# write.fst("./data/indestatus.fst")
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# dead.indi<-indi %>% unique() %>% inner_join(dead.indi, by=c("V4"="Id.Nummer")) %>% rename(business_partner=V2, id_number=V4)
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oi<-
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oi%>%
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mutate(o.type = case_when(
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deposit == T ~ "Deposit",
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documen_desc == "Installments" ~ "Installments",
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contract_type=="Waste" | grepl("Waste",trandesc) ~ "Waste",
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TRUE ~ "Real"
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)
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)
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oi<-oi %>%
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select(-c(sap_client,main_tran,sub_tran,division,dunn_exclu,payment_meth,clearing_date,clearing_post_date,clearing_reason,document_type,X,trantype, OUT_AGE)) %>%
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left_join(operating_status, by="business_partner") %>%
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mutate(e.status=ifelse(is.na(e.status),"active",e.status)) %>%
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select(-type)
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oi %>%
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write.fst("./data/open_items.fst")
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# c.status<-
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# oi %>%
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# mutate(AGE_BUCKET=ifelse(AGE_BUCKET!="5+ years","5- years", "5+ years")) %>%
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# select(contract_account,AGE_BUCKET) %>%
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# count(contract_account,AGE_BUCKET) %>%
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# pivot_wider(names_from = AGE_BUCKET,values_from = n) %>%
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# mutate(spread=ifelse(is.na(`5+ years`),"Only less than 5",ifelse(is.na(`5- years`)," Only more than 5","Both"))) %>%
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# select(contract_account,spread)
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oi<-oi %>%
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left_join(c.status, by="contract_account")
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unique(oi$contract_type)
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```
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Credit amounts: aggregated per contract account but older than 5 years
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```{r}
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oi |>
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filter(o.type %in% c("Real", "Installments")) |>
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filter(negative) |>
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filter(AGE_BUCKET=="5+ years") |>
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group_by(contract_account) |>
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summarise(amount=sum(amount)) |> write.csv("creditagrrolderthan5.csv")
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```
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Credit amounts: aggregated per contract account but older than 3 years
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```{r}
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oi |>
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filter(o.type %in% c("Real", "Installments")) |>
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filter(negative) |>
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filter(AGE_BUCKET %in% c("5+ years","4-5 years","3-4 years")) |>
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group_by(contract_account, active) |>
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summarise(amount=sum(amount)) |> #pull(amount) |> sum()
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write.csv("creditagrrolderthan3.csv")
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```
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Open amounts for Deceased individuals: aggregated per contract account for only less than 60 days past their Date of Death
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```{r}
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oi |>
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filter(e.status=="Passed") |>
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filter(date.event <= due_date) |>
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filter(due_date < date.relaxed) |>
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group_by(contract_account, negative) |>
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summarise(amount=sum(amount)) |>
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pivot_wider(names_from = negative, values_from = amount) |>
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rename(Open=`FALSE`, Credit=`TRUE`) |> write.csv("deceasedaggrlessthan60butnotbeforevent.csv")
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```
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Open amounts for migrated persons: aggregated per contract account for only less than 60 days past their migration date
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```{r}
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oi |>
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filter(e.status=="Left") |>
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filter(date.event <= due_date) |>
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filter(due_date < date.relaxed) |>
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group_by(contract_account, negative) |>
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summarise(amount=sum(amount)) |>
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pivot_wider(names_from = negative, values_from = amount) |>
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rename(Open=`FALSE`, Credit=`TRUE`) |> write.csv("leftaggrlessthan60butnotbeforevent.csv")
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```
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Open amounts for Deceased individuals: aggregated per contract account for only less than 60 days past their Date of Death
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```{r}
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oi |>
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filter(e.status=="Passed") |>
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filter(due_date < date.relaxed) |>
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group_by(contract_account, negative) |>
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summarise(amount=sum(amount)) |>
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pivot_wider(names_from = negative, values_from = amount) |>
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rename(Open=`FALSE`, Credit=`TRUE`) |> write.csv("deceasedaggrlessthan60inclbeforevent.csv")
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oi |>
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filter(o.type %in% c("Real", "Installments")) |>
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filter(e.status == "Left") |>
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group_by(contract_account, rel.status, active) |>
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summarise(amount=sum(amount)) |>
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ungroup() |>
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pivot_wider(names_from = rel.status, values_from = amount) |>
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rename(duedatebeforedaterelaxed=`long past`, duedateafterrelaxeddate=`within limit`) |>
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mutate(statu= ifelse(is.na(duedatebeforedaterelaxed),"Only duedateafterrelaxeddate",
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ifelse(is.na(duedateafterrelaxeddate), "Only duedatebeforedaterelaxed", "Both"))) |>
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inner_join(uniquebpcont, by="contract_account") |>
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filter(statu=="Only duedatebeforedaterelaxed") |>
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filter(duedatebeforedaterelaxed>10000) |>
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write.csv("leftaggr.csv")
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uniquebpcont<-oi |>
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select(contract_account, business_partner) |> unique()
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```
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```{r}
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oi |>
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filter(e.status=="Left") |>
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filter(due_date < date.relaxed) |>
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group_by(contract_account, negative) |>
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summarise(amount=sum(amount)) |>
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pivot_wider(names_from = negative, values_from = amount) |>
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rename(Open=`FALSE`, Credit=`TRUE`) |> write.csv("leftaggrlessthan60inclbeforevent.csv")
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```
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## Dump Dec 29
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```{r}
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passed<-read.csv("./data-raw/passed.csv", sep = ";") |> mutate(contract_account=as.character(contract_account)) |> select(-c(BP,Name))
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migrated<-read.csv("./data-raw/migrated.csv", sep = ";") |> mutate(contract_account=as.character(contract_account)) |> select(-c(BP,Name))
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inactived<-read.csv("./data-raw/inactived.csv", sep = ";") |> mutate(contract_account=as.character(contract_account)) |> select(-c(BP,NAME))
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discontinued<-read.csv("./data-raw/discontinued.csv", sep = ";") |> mutate(contract_account=as.character(contract_account)) |>
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select(-c(BP,NAME))
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bpnames<-read.csv("./data-raw/bpnames.csv", sep = ";") |> select(c(PARTNER,X)) |> unique()
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bpnames<-uniquebpcont |>
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full_join(bpnames, by=c("business_partner"="PARTNER")) |>
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select(contract_account, business_partner, X) |>
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rename(Name=X) |> filter(!is.na(contract_account))
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bpnames |> count(contract_account) |> arrange(desc(n))
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bpnames |> filter(PARTNER=="1301041926")
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```
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```{r}
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bpnames |>
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select(business_partner, Name) |>
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unique()
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right_join(discontinued, by="contract_account") |>
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arrange(contract_account) |>
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filter(amount!="") |> mutate(amount=as.numeric(amount))
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pull(amount) |> sum() #|> write.csv("disco.csv")
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```
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```{r}
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oi |> filter(contract_account == "11460001")
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```
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## New inactive and kvk list post discussion with Aldo on Dec 30, 2021
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1. Compare our inactive list and inactive list of Betza
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2. If they match, proceed with aggregation
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3. Create a list of aggregation of KvK
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```{r}
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betza_inactive<-read.csv("betzainactive.csv", sep=";", dec = ",")
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```
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```{r}
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our.inactive<-oi |>
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filter(o.type %in% c("Real", "Installments")) |>
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filter(bp_category=="Organization") |>
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filter(!active)
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our.inactive<-our.inactive |>
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filter(!negative) |>
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group_by(business_partner, contract_account) |>
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summarise(amount=sum(amount))
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bpnames<-bpnames |>
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select(business_partner, Name) |>
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unique()
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our.inactive |>
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left_join(bpnames, by="business_partner") |> filter(contract_account=="11493258")
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write.csv(our.inactive,"ourinactive.csv")
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```
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None of them match. That means, Betza's list contain inactive businesses that are falsely marked as active in our data.
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```{r}
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bi<-betza_inactive |>
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group_by(contract_account, business_partner) |>
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summarise(amount=sum(amount)) |>
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mutate(contract_account=as.character(contract_account)) |>
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left_join(bpnames, by="contract_account") |> arrange(business_partner.x) |>
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select(-business_partner.y) |>
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rename(business_partner=business_partner.x) |>
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group_by(business_partner, Name) |>
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summarise(amount=sum(amount)) |>
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mutate(business_partner=as.character(business_partner)) #|> write.csv("Betza_Inactive_Named_aggregated.csv")
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betzaaldokvk<-read.csv("betzaaldokvk.csv",sep=";",dec=",")
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ba<-betzaaldokvk |>
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mutate(BP=as.character(BP)) |>
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rename(business_partner=BP) |>
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left_join(oi, by="business_partner") |>
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filter(!negative) |>
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group_by(contract_account, business_partner, Name.x, Chamber.of.commerce) |>
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summarise(amount=sum(amount)) |>
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rename(Name=Name.x) |>
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arrange(business_partner)
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write.csv(ba,"Betza_Aldo_Named_kvk_aggregated.csv")
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our.inactive |>
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group_by(business_partner) |>
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summarise(amount=sum(amount)) |>
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full_join(bi, by="business_partner") |>
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rename(out.amount=amount.x, bi.amount=amount.y) |>
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full_join(ba, by="business_partner") |>
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rename(ba.amount=amount) |>
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filter(!is.na(out.amount)) |>
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filter(!is.na(ba.amount))
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```
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```{r}
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bi |>
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full_join(ba, by="business_partner") |>
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```
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```{r}
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bpnames
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```
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#Dec312021 Adding Names
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```{r}
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broke<-read.csv("./dec312021/broke.csv", sep=";", dec=",")
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dead<-read.csv("./dec312021/dead.csv", sep=";", dec=",")
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gone<-read.csv("./dec312021/gone.csv", sep=";", dec=",")
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smallamount<-read.csv("./dec312021/smallamount.csv", sep=";", dec=",")
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timebarred<-read.csv("./dec312021/timebarred.csv", sep=";", dec=",")
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broke |>
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mutate(contract_account=as.character(contract_account)) |>
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left_join(bpnames, by=c("contract_account")) |>
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rename(`status (1)`=status..1.)
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write.csv2("./dec312021/named/broke.csv",row.names = F)
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dead |>
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left_join(bpnames, by=c("Row.Labels"="contract_account")) |>
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write.csv2("./dec312021/named/dead.csv",row.names = F)
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gone |>
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mutate(Row.Labels=as.character(Row.Labels)) |>
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left_join(bpnames, by=c("Row.Labels"="contract_account")) |>
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write.csv2("./dec312021/named/gone.csv",row.names = F)
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smallamount |>
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mutate(contract_account=as.character(contract_account)) |>
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left_join(bpnames, by=c("contract_account")) |>
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rename(business_partner=business_partner.x) |>
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select(-business_partner.y) |>
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write.csv2("./dec312021/named/smallamount.csv",row.names = F)
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timebarred |>
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left_join(bpnames, by=c("Row.Labels"="contract_account"))
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write.csv2("./dec312021/named/timebarred.csv",row.names = F)
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```
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## Jan 05, 2021
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Task is to add year wise amount to the list of writeoff contract accounts
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inactive
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```{r}
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deceased<-read.csv("./data-raw/jan052021/inactive/deceased.csv")
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discontinued<-read.csv("./data-raw/jan052021/inactive/discontinued.csv")
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migrated<-read.csv("./data-raw/jan052021/inactive/migrated.csv")
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small<-read.csv("./data-raw/jan052021/inactive/small.csv")
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timebarred<-read.csv("./data-raw/jan052021/inactive/timebarred.csv")
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```
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```{r}
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real.pos<-oi |>
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filter(o.type %in% c("Real", "Installments")) |>
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filter(!negative) |> mutate(age=ifelse(AGE_BUCKET=="5+ years", "More than 5","Less than 5"))
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deceased |> #pull(Grand.Total) |> sum() # They have not used the 60 days filter here. SO, I'm not using as well
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select(c(Row.Labels,business_partner,Name)) |>
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rename(contract_account=Row.Labels) |>
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mutate(contract_account=as.character(contract_account)) |>
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left_join(real.pos, by="contract_account") |>
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select(-business_partner.y) |>
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rename(business_partner=business_partner.x) |>
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mutate(year.due=lubridate::year(due_date)) |>
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group_by(contract_account, business_partner, Name, year.due) |>
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summarise(amount=sum(amount)) |>
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pivot_wider(names_from = year.due, values_from = amount) |>
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rename(name=Name) |> write.csv("./data-raw/jan052021/inactive/deceasedbyyear.csv")
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## Number not matching
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discontinued |> #pull(amount) |> sum() # 1108257
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select(c(contract_account)) |> unique() |>
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mutate(contract_account=as.character(contract_account)) |>
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left_join(oi, by=c("contract_account"="contract_account")) |>
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filter(AGE_BUCKET %in% c("4-5 years","3-4 years","2-3 years","1-2 years",
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"181-365 days","91-180 days","61-90 days", "0-30 days")) |>
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filter(o.type %in% c("Real", "Installments") ) |>
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mutate(year.due=lubridate::year(due_date)) |>
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group_by(contract_account,year.due) |>
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summarise(amount=sum(amount)) |> #pull(amount) |> sum()
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pivot_wider(names_from = year.due, values_from = amount) |>
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left_join(bpnames, by="contract_account") |>
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select(c(contract_account,business_partner, Name, `2016`,`2017`,`2018`)) |> write.csv("./data-raw/jan052021/inactive/discontinuedbyyear.csv", na="", row.names = F)
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## Number not matching
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migrated |> #pull(Grand.Total) |> sum()#130502
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select(c(contract_account)) |> unique() |>
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mutate(contract_account=as.character(contract_account)) |>
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left_join(real.pos, by="contract_account") |>
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#filter(o.type %in% c("Real", "Installments") ) |>
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filter(AGE_BUCKET %in% c("4-5 years","3-4 years","2-3 years","1-2 years",
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"181-365 days","91-180 days","61-90 days","31-60 days")) |>
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mutate(year.due=lubridate::year(due_date)) |>
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group_by(contract_account,year.due) |>
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summarise(amount=sum(amount)) |> #pull(amount) |> sum()
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pivot_wider(names_from = year.due, values_from = amount) |>
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left_join(bpnames, by="contract_account") |>
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select(c(contract_account,business_partner,Name, `2016`, `2017`, `2018`, `2021`)) |>
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write.csv("./data-raw/jan052021/inactive/migratedbyyear.csv", na="", row.names = F)
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small |> #pull(Open.Items) |> sum() #123207.9
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select(c(contract_account,business_partner,Name)) |>
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mutate(contract_account=as.character(contract_account)) |>
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left_join(real.pos, by="contract_account") |>
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select(-business_partner.y) |>
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rename(business_partner=business_partner.x) |> #pull(amount) |> sum()
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mutate(year.due=lubridate::year(due_date)) |>
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group_by(contract_account, business_partner, Name.x, year.due) |>
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summarise(amount=sum(amount)) |>
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pivot_wider(names_from = year.due, values_from = amount) |>
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rename(name=Name.x) |> write.csv("./data-raw/jan052021/inactive/smallbyyear.csv", na="")
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# not required
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timebarred |> #pull(Sum.of.amount) |> sum() #25943341
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rename(contract_account=Row.Labels) |>
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mutate(contract_account=as.character(contract_account)) |>
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left_join(real.pos, by="contract_account") |>
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select(-business_partner.y) |>
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rename(business_partner=business_partner.x) |> pull(amount) |> sum()
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|
|
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real.pos |>
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filter(contract_account=="15276925") |>
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pull(amount) |> sum()
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```
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active
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|
```{r}
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act.inact<-read.csv("./data-raw/jan052021/active/inactive.csv")
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act.disc<-read.csv("./data-raw/jan052021/active/discontinued.csv")
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act.migrated<-read.csv("./data-raw/jan052021/active/migrated.csv")
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act.passed<-read.csv("./data-raw/jan052021/active/passed.csv")
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#Not matching
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|
act.inact |> #pull(amount) |> sum() #6830028
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select(c(contract_account)) |> unique() |>
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|
mutate(contract_account=as.character(contract_account)) |>
|
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left_join(real.pos, by="contract_account") |> #pull(amount) |> sum()
|
|
mutate(year.due=lubridate::year(due_date)) |>
|
|
group_by(contract_account,year.due) |>
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|
summarise(amount=sum(amount)) |> #pull(amount) |> sum()
|
|
pivot_wider(names_from = year.due, values_from = amount) |>
|
|
left_join(bpnames, by="contract_account") |>
|
|
select(c(contract_account,business_partner, Name, `2004`,`2005`,`2006`,`2007`,`2008`,
|
|
`2009`,`2010`,`2011`,`2012`,`2013`,`2014`,`2015`,`2016`,`2017`,`2018`,`2019`,`2020`,`2021`)) |>
|
|
write.csv("./data-raw/jan052021/active/inactivebyyear.csv", na="", row.names = F)
|
|
|
|
act.disc |> #pull(amount) |> sum() #1214182
|
|
select(c(contract_account, rel.status, age)) |> unique() |>
|
|
mutate(rel.status=ifelse(rel.status=="More than 60 days", "long past","within limit")) |>
|
|
mutate(contract_account=as.character(contract_account)) |>
|
|
left_join(real.pos, by=c("contract_account"="contract_account", "rel.status"="rel.status","age"="age")) |>
|
|
mutate(year.due=lubridate::year(due_date)) |>
|
|
group_by(contract_account,year.due) |>
|
|
summarise(amount=sum(amount)) |> #pull(amount) |> sum()
|
|
pivot_wider(names_from = year.due, values_from = amount) |>
|
|
left_join(bpnames, by="contract_account") |>
|
|
select(c(contract_account,business_partner, Name,`2006`,`2007`,`2008`,
|
|
`2009`,`2010`,`2011`,`2012`,`2013`,`2014`,`2015`,`2016`,`2017`,`2018`,`2019`,`2020`,`2021`)) |>
|
|
write.csv("./data-raw/jan052021/active/discontinuedbyyear.csv", na="", row.names = F)
|
|
|
|
|
|
|
|
# Matching
|
|
act.migrated |> #1401989
|
|
select(c(contract_account, Name)) |>
|
|
mutate(contract_account=as.character(contract_account)) |>
|
|
left_join(real.pos, by="contract_account") |>
|
|
mutate(year.due=lubridate::year(due_date)) |>
|
|
group_by(contract_account,business_partner, Name, year.due) |>
|
|
summarise(amount=sum(amount)) |> #pull(amount) |> sum(na.rm = T)
|
|
pivot_wider(names_from = year.due, values_from = amount) |>
|
|
select(c(contract_account,business_partner, Name,`1994`,`1995`,`1996`,`1997`,`1998`,`1999`,`2000`,`2001`,`2002`,`2003`,`2004`,`2005`,`2006`,`2007`,`2008`,
|
|
`2009`,`2010`,`2011`,`2012`,`2013`,`2014`,`2015`,`2016`,`2017`)) |>
|
|
write.csv("./data-raw/jan052021/active/migratedbyyear.csv", na="", row.names = F)
|
|
|
|
|
|
|
|
|
|
# Matching
|
|
act.passed |> #pull(duedatebeforedaterelaxed) |> sum(na.rm=T) #929285.6
|
|
select(c(contract_account, Name)) |>
|
|
mutate(contract_account=as.character(contract_account)) |>
|
|
left_join(real.pos, by="contract_account") |>
|
|
mutate(year.due=lubridate::year(due_date)) |>
|
|
group_by(contract_account,business_partner, Name, year.due) |>
|
|
summarise(amount=sum(amount)) |> #pull(amount) |> sum(na.rm = T)
|
|
pivot_wider(names_from = year.due, values_from = amount) |>
|
|
select(c(contract_account,business_partner, Name,`1900`,`1994`,`1995`,`1996`,`1997`,`1998`,`1999`,`2000`,`2001`,`2002`,`2003`,`2004`,`2005`,`2006`,`2007`,`2008`,
|
|
`2009`,`2010`,`2011`,`2012`,`2013`,`2014`,`2015`,`2016`,`2017`)) |>
|
|
write.csv("./data-raw/jan052021/active/passedbyyear.csv", na="", row.names = F)
|
|
|
|
```
|
|
|
|
|
|
|
|
|
|
|
|
|
|
## R Markdown
|
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|
|
This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see <http://rmarkdown.rstudio.com>.
|
|
|
|
When you click the **Knit** button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:
|
|
|
|
```{r cars}
|
|
summary(cars)
|
|
```
|
|
|
|
## Including Plots
|
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|
|
You can also embed plots, for example:
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|
|
|
```{r pressure, echo=FALSE}
|
|
plot(pressure)
|
|
```
|
|
|
|
Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot.
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|