I have been trying to convert UK charity commission data which is in .bcp file format into .csv file format which could then be read into R. The data I am referring to is available here: http://data.charitycommission.gov.uk/. What I am trying to do is turn these .bcp files into useable dataframes that I can clean and run analyses on in R.
There are suggestions on how to do this through python on this github page https://github.com/ncvo/charity-commission-extract but unfortunately I haven't been able to get these options to work.
I am wondering if there is any syntax or packages that will allow me to open these data in R directly? I haven't been able to find any.
Another option would be to simply open the files within R as a single character vector using readLines. I have done this and the files are delimited with @**@ for columns and *@@* for rows. (See here: http://data.charitycommission.gov.uk/data-definition.aspx). Is there an R command that would allow me to create a dataframe from a long character string, defining de-limiters for both rows and columns?
R-solution
edited version
Not sure if all .bcp files are in the same format.. I downloaded the dataset you mentioned, and tried a solution for the smallest file; extract_aoo_ref.bcp
library(data.table)
#read the file as-is
text <- readChar("./extract_aoo_ref.bcp",
nchars = file.info( "./extract_aoo_ref.bcp" )$size,
useBytes = TRUE)
#replace column and row separator
text <- gsub( ";", ":", text)
text <- gsub( "@\\*\\*@", ";", text)
text <- gsub( "\\*@@\\*", "\n", text, perl = TRUE)
#read the results
result <- data.table::fread( text,
header = FALSE,
sep = ";",
fill = TRUE,
quote = "",
strip.white = TRUE)
head(result,10)
# V1 V2 V3 V4 V5 V6
# 1: A 1 THROUGHOUT ENGLAND AND WALES At least 10 authorities in England and Wales N NA
# 2: B 1 BRACKNELL FOREST BRACKNELL FOREST N NA
# 3: D 1 AFGHANISTAN AFGHANISTAN N 2
# 4: E 1 AFRICA AFRICA N NA
# 5: A 2 THROUGHOUT ENGLAND At least 10 authorities in England only N NA
# 6: B 2 WEST BERKSHIRE WEST BERKSHIRE N NA
# 7: D 2 ALBANIA ALBANIA N 3
# 8: E 2 ASIA ASIA N NA
# 9: A 3 THROUGHOUT WALES At least 10 authorities in Wales only Y NA
# 10: B 3 READING READING N NA
same for the tricky file; extract_charity.bcp
head(result[,1:3],10)
# V1 V2 V3
# 1: 200000 0 HOMEBOUND CRAFTSMEN TRUST
# 2: 200001 0 PAINTERS' COMPANY CHARITY
# 3: 200002 0 THE ROYAL OPERA HOUSE BENEVOLENT FUND
# 4: 200003 0 HERGA WORLD DISTRESS FUND
# 5: 200004 0 THE WILLIAM GOLDSTEIN LAY STAFF BENEVOLENT FUND (ROYAL HOSPITAL OF ST BARTHOLOMEW)
# 6: 200005 0 DEVON AND CORNWALL ROMAN CATHOLIC DEVELOPMENT SOCIETY
# 7: 200006 0 THE HORLEY SICK CHILDREN'S FUND
# 8: 200007 0 THE HOLDENHURST OLD PEOPLE'S HOME TRUST
# 9: 200008 0 LORNA GASCOIGNE TRUST FUND
# 10: 200009 0 THE RALPH LEVY CHARITABLE COMPANY LIMITED
so.. looks like it is working :)