| Title: | Reading Annual Financial Reports from Bovespa's DFP, FRE and FCA System |
| Version: | 1.6 |
| Date: | 2021-03-24 |
| Description: | Reads annual financial reports including assets, liabilities, dividends history, stockholder composition and much more from Bovespa's DFP, FRE and FCA systems http://www.b3.com.br/pt_br/produtos-e-servicos/negociacao/renda-variavel/empresas-listadas.htm. These are web based interfaces for all financial reports of companies traded at Bovespa. The package is specially designed for large scale data importation, keeping a tabular (long) structure for easier processing. |
| Depends: | R (≥ 3.3.0) |
| Imports: | stringr, XML, dplyr, readr, reshape2, tibble, xlsx, stats, curl, lubridate, crayon |
| ByteCompile: | true |
| License: | GPL-2 |
| BugReports: | https://github.com/msperlin/GetDFPData/issues |
| URL: | https://github.com/msperlin/GetDFPData/ |
| LazyData: | false |
| RoxygenNote: | 7.1.1 |
| Suggests: | knitr, rmarkdown, testthat, ggplot2 |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2021-04-01 11:49:37 UTC; msperlin |
| Author: | Marcelo Perlin [aut, cre] |
| Maintainer: | Marcelo Perlin <marceloperlin@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2021-04-01 12:00:03 UTC |
Fix NULL values in dataframe
Description
Fix NULL values in dataframe
Usage
fix.fct(x, type.info = "character", format.date = "%Y-%m-%d")
Arguments
x |
Am object, possibly NULL |
type.info |
Type of object |
format.date |
Format of data, as string |
Value
A single object
Examples
x <- NULL
x2 <- fix.fct(x)
Downloads and reads financial reports from B3's DFP/FRE/FCA system
Description
Annual data for financial reports and corporate events are downloaded from B3 for a combination of companies and time period. This function gathers data into a single tibble object and organizes it in a tabular/long format.
Usage
gdfpd.GetDFPData(
name.companies,
first.date = Sys.Date() - 12 * 30,
last.date = Sys.Date(),
selected.data = "DFP|FRE|FCA",
inflation.index = "dollar",
max.levels = 3,
folder.out = tempdir(),
do.cache = TRUE,
cache.folder = "DFP Cache Folder",
fetch.new.files = FALSE,
max.dl.tries = 10
)
Arguments
name.companies |
Official names of companies to get financial reports (e.g. 'ELETROPAULO METROPOLITANA EL.S.PAULO S.A'). Names of companies can be found using function gdfpd.search.company('nametolookfor') or gdfpd.get.info.companies('companies') |
first.date |
First date (YYYY-MM-DD) to get data. Character or Date. E.g. first.date = '2010-01-01'. |
last.date |
Last date (YYYY-MM-DD) to get data. Character or Date. E.g. last.date = '2017-01-01'. |
selected.data |
Symbols for the selection of datasets: 'DFP|FRE|FCA', 'DFP|FRE', 'FRE|FCA', 'DFP|FCA', 'DFP', 'FRE', 'FCA'. Default = 'DFP|FRE|FCA' |
inflation.index |
Sets the inflation index to use for finding inflation adjusted values of all reports. Possible values: 'dollar' (default) or 'IPCA', the brazilian main inflation index. When using 'IPCA', the base date is set as the last date found in the DFP dataset. |
max.levels |
Sets the maximum number of levels of accounting items in financial reports (default = 3) |
folder.out |
Folder where to download and manipulate the zip files. Default = tempdir() |
do.cache |
Logical for controlling to whether to use a cache system or not. Default = TRUE |
cache.folder |
Folder to cache (save) all processed information. Default = file.path(getwd(),'DFP Cache Folder') |
fetch.new.files |
Logical. Should the function search for new files/data in Bovespa? (default = FALSE) |
max.dl.tries |
Maximum number of attempts for dowloading files |
Details
The easiest way to get started with gdfpd.GetDFPData is looking for the official name of traded companies using function gdfpd.search.company('nametolookfor'). Alternatively, you can use function gdfpd.get.info.companies('companies') to import a dataframe with information for all available companies and time periods.
Value
A tibble object with all gathered financial statements, with each company as a row
Examples
## Not run: #dontrun: keep cran check time short
name.companies <- 'ELETROPAULO METROPOLITANA EL.S.PAULO S.A'
first.date <- '2005-01-01'
last.date <- '2006-01-01'
df.statements <- gdfpd.GetDFPData(name.companies = name.companies,
first.date = first.date,
last.date = last.date)
## End(Not run)
Converts a dataframe from gdfpd_GetDFPData to the wide format
Description
Converts a dataframe from gdfpd_GetDFPData to the wide format
Usage
gdfpd.convert.to.wide(data.in, data.in.cols = "original")
Arguments
data.in |
Data frame with financial information |
data.in.cols |
Which data to go in rows values ('original' or 'inflation adjusted') |
Value
A dataframe in the wide format
Examples
# get example data from RData file
my.f <- system.file('extdata/Example_DFP_Report_Petrobras.RData', package = 'GetDFPData')
load(my.f)
df.assets <- df.reports$fr.assets[[1]]
df.assets.wide <- gdfpd.convert.to.wide(df.assets)
Downalods files from the internet
Description
Downalods files from the internet
Usage
gdfpd.download.file(dl.link, dest.file, max.dl.tries)
Arguments
dl.link |
Link to file |
dest.file |
= Destination, as local file |
max.dl.tries |
Maximum number of attempts for dowloading files |
Value
Nothing
Examples
my.url <- paste0('http://www.rad.cvm.gov.br/enetconsulta/',
'frmDownloadDocumento.aspx?CodigoInstituicao=2',
'&NumeroSequencialDocumento=46133')
## Not run: # keep CHECK fast
dl.status <- gdfpd.download.file(my.url, 'tempfile.zip', 10)
## End(Not run)
Export tibble to an excel or csv (zipped) file
Description
Export information from gdfpd_GetDFPData() to an excel file or csv. In the csv case, all tables are exported as csv files and zipped in a single zip file.
Usage
gdfpd.export.DFP.data(
df.reports,
base.file.name = paste0("GetDFPData_Export_", Sys.Date()),
type.export = "xlsx"
)
Arguments
df.reports |
Tibble with financial information (output of gdfpd.GetDFPData) |
base.file.name |
The basename of excel file (make sure you dont include the file extension) |
type.export |
The extension of the desired format: 'xlsx' (default) or 'csv' |
Value
TRUE, if successfull (invisible)
Examples
# get example data from RData file
my.f <- system.file('extdata/Example_DFP_Report_Petrobras.RData', package = 'GetDFPData')
load(my.f)
## Not run: # dontrun: keep cran check time short
gdfpd.export.DFP.data(df.reports, base.file.name = 'MyExcelFile', format.data = 'wide')
## End(Not run)
Fix dataframe for version issues and inflation measures (internal)
Description
Fix dataframe for version issues and inflation measures (internal)
Usage
gdfpd.fix.DFP.dataframes(df.in, inflation.index, df.inflation, max.levels = 3)
Arguments
df.in |
A dataframe with financial statements |
inflation.index |
Sets the inflation index to use for finding inflation adjusted values of all reports. Possible values: 'dollar' (default) or 'IPCA', the brazilian main inflation index. When using 'IPCA', the base date is set as the last date found in the DFP dataset. |
df.inflation |
Dataframe with inflation data |
max.levels |
Sets the maximum number of levels of accounting items in financial reports (default = 3) |
Value
The fixed data.frame
Examples
#'
# get example data from RData file
my.f <- system.file('extdata/Example_DFP_Report_Petrobras.RData', package = 'GetDFPData')
load(my.f)
df.assets <- df.reports$fr.assets[[1]]
df.inflation <- gdfpd.get.inflation.data('dollar', do.cache = FALSE)
df.assets.fixed <- gdfpd.fix.DFP.dataframes(df.assets,
inflation.index = 'dollar',
df.inflation = df.inflation)
Reads information for a company from B3 site
Description
Given a CVM code, this function scrapes information from the company page.
Usage
gdfpd.get.bovespa.data(my.id)
Arguments
my.id |
A CVM id |
Value
A list with several dataframes
Examples
## Not run: # keep cran check fast
l.info.PETR <- gdfpd.get.dovespa.data(my.id = 9512)
str(l.info.PETR)
## End(Not run)
Fetches ALL new files from Bovespa
Description
Fetches ALL new files from Bovespa
Usage
gdfpd.get.files.from.bovespa(my.id)
Arguments
my.id |
Company's ID |
Value
A dataframe with several information about files
Examples
## Not run:
df.files <- gdfpd.get.files.from.bovespa(9512)
## End(Not run)
Downloads and read inflation data from github
Description
Inflation data is available at git repo 'msperlin/GetITRData_auxiliary'
Usage
gdfpd.get.inflation.data(inflation.index, do.cache)
Arguments
inflation.index |
Sets the inflation index to use for finding inflation adjusted values of all reports. Possible values: 'dollar' (default) or 'IPCA', the brazilian main inflation index. When using 'IPCA', the base date is set as the last date found in the DFP dataset. |
do.cache |
Logical for controlling to whether to use a cache system or not. Default = TRUE |
Value
A dataframe with inflation data
Examples
## Not run: # keep cran check fast
df.inflation <- gdfpd.get.inflation.data('IPCA')
str(df.inflation)
## End(Not run)
Reads up to date information about Bovespa companies from a github file
Description
A csv file with information about available companies, file links and time periods is read from github. This file is manually updated by the author. When run for the first time in a R session, a .RDATA file containing the output of the function is saved for caching.
Usage
gdfpd.get.info.companies(
type.data = "companies_files",
cache.folder = "DFP Cache Folder"
)
Arguments
type.data |
A string that sets the type of information to be returned ('companies' or 'companies_files'). If 'companies', it will return a dataframe with several information about companies, but without download links. |
cache.folder |
Folder to cache (save) all processed information. Default = file.path(getwd(),'DFP Cache Folder') |
Value
A dataframe with several information about Bovespa companies
Examples
## Not run: # keep cran check fast
df.info <- gdfpd.get.info.companies()
str(df.info)
## End(Not run)
Reads a single zip file downloaded from Bovespa
Description
Reads a single zip file downloaded from Bovespa
Usage
gdfpd.read.dfp.zip.file(my.zip.file, folder.to.unzip = tempdir(), id.type)
Arguments
my.zip.file |
Full path to zip file |
folder.to.unzip |
Folder to unzip files (default = tempdir()) |
id.type |
The type of file structure ('after 2011' or 'before 2011') |
Value
A list with several dataframes containing financial statements
Examples
my.f <- system.file('extdata/9512_PETR_2002-12-31.zip', package = 'GetDFPData')
#my.l <- gdfpd.read.dfp.zip.file(my.f, id.type = 'before 2011')
#print(my.l)
Reads folder for zip file post 2011 (internal)
Description
Reads folder for zip file post 2011 (internal)
Usage
gdfpd.read.dfp.zip.file.type.1(rnd.folder.name, folder.to.unzip = tempdir())
Arguments
rnd.folder.name |
Folder where unzipped files are available |
folder.to.unzip |
Folder to unzip files (default = tempdir()) |
Value
A list with financial statements
Examples
# no example (this functions not used directly)
Reads folder for zip file pre 2011 (internal)
Description
Reads folder for zip file pre 2011 (internal)
Usage
gdfpd.read.dfp.zip.file.type.2(rnd.folder.name, folder.to.unzip = tempdir())
Arguments
rnd.folder.name |
Folder where unzipped files are available |
folder.to.unzip |
Folder to unzip files (default = tempdir()) |
Value
A list with financial statements
Examples
# no example (this functions not used directly)
Reads a single FCA zip file downloaded from Bovespa
Description
Reads a single FCA zip file downloaded from Bovespa
Usage
gdfpd.read.fca.zip.file(my.zip.file, folder.to.unzip = tempdir())
Arguments
my.zip.file |
Full path to zip file |
folder.to.unzip |
Folder to unzip files, default = tempdir() |
Value
A list with several dataframes containing financial statements
Examples
my.f <- system.file('extdata/FCA_9512_PETR_2015-12-31.zip', package = 'GetDFPData')
my.l <- gdfpd.read.fca.zip.file(my.f)
print(my.l)
Reads a single FRE zip file downloaded from Bovespa
Description
Reads a single FRE zip file downloaded from Bovespa
Usage
gdfpd.read.fre.zip.file(my.zip.file, folder.to.unzip = tempdir())
Arguments
my.zip.file |
Full path to zip file |
folder.to.unzip |
Folder to unzip files (default = tempdir()) |
Value
A list with several dataframes containing financial statements
Examples
my.f <- system.file('extdata/FRE_6629_HERC_2010-12-31.zip', package = 'GetDFPData')
my.l <- gdfpd.read.fre.zip.file(my.f)
print(my.l)
Reads FWF file from bovespa (internal)
Description
Reads FWF file from bovespa (internal)
Usage
gdfpd.read.fwf.file(my.f, flag.thousands)
Arguments
my.f |
File to be read |
flag.thousands |
A flag for thousands values |
Value
A dataframe with data
Examples
my.f <- system.file('extdata/DFPBPAE.001', package = 'GetDFPData')
df.assets <- gdfpd.read.fwf.file(my.f, flag.thousands = FALSE)
Reads folder for FCA zip file contents (internal)
Description
Reads folder for FCA zip file contents (internal)
Usage
gdfpd.read.zip.file.type.fca(rnd.folder.name, folder.to.unzip = tempdir())
Arguments
rnd.folder.name |
Folder where unzipped files are available |
folder.to.unzip |
Folder to unzip files, default = tempdir() |
Value
A list with FCA data
Examples
# no example (this functions is not used directly)
Reads folder for zip file post 2011 (internal)
Description
Reads folder for zip file post 2011 (internal)
Usage
gdfpd.read.zip.file.type.fre(rnd.folder.name, folder.to.unzip = tempdir())
Arguments
rnd.folder.name |
Folder where unzipped files are available |
folder.to.unzip |
Folder to unzip files (default = tempdir()) |
Value
A list with financial statements
Examples
# no example (this functions not used directly)
Helps users search for a company name
Description
Helps users search for a company name
Usage
gdfpd.search.company(char.to.search, cache.folder = "DFP Cache Folder")
Arguments
char.to.search |
Character for partial matching |
cache.folder |
Folder to cache (save) all processed information. Default = file.path(getwd(),'DFP Cache Folder') |
Value
Names of found companies
Examples
## Not run: # dontrun: keep cran check fast
gdfpd.search.company('GERDAU')
## End(Not run)
Fetches files for different systens (INTERNAL)
Description
Fetches files for different systens (INTERNAL)
Usage
get_files(my.id, type.fin.report)
Arguments
my.id |
Company id |
type.fin.report |
type of financial report (dfp/itr/fre/fca) |
Value
A dataframe
Examples
## Not run:
df.fre.files <- get_files(9512, type.fin.report = 'dfp')
## End(Not run)
Copies data to external file
Description
Copies data to external file
Usage
my.copy.fct(
df.in,
name.df,
base.file.name,
type.export = "xlsx",
csv.dir = tempdir()
)
Arguments
df.in |
Dataframe to be copied |
name.df |
Name of dataframe to be copied |
base.file.name |
The basename of excel file (make sure you dont include the file extension) |
type.export |
The extension of the desired format: 'xlsx' (default) or 'csv' |
csv.dir |
Location where to save csv files prior to zipping (default = tempdir()) |
Value
TRUE (invisible), if successfull
Examples
test.data <- data.frame(test.data = runif(100))
name.df <- 'TestData'
base.file.name <- 'TestData'
type.export <- 'csv'
my.copy.fct(df.in = test.data, name.df, base.file.name, type.export)
Merges (row wise) dataframes from different list, using names of dataframes as index
Description
Merges (row wise) dataframes from different list, using names of dataframes as index
Usage
my.merge.dfs.lists(l.1, l.2)
Arguments
l.1 |
First dataframe |
l.2 |
Second dataframe |
Value
A list with binded dataframes (same names as l.1)
Examples
l.1 <- list(x = data.frame(runif(10)) )
l.2 <- list(x = data.frame(runif(10)) )
l <- my.merge.dfs.lists(l.1, l.2)
Reads XML data for auditing
Description
Reads XML data for auditing
Usage
xml.fct.auditing(x)
Arguments
x |
A list with data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for board composition
Description
Reads XML data for board composition
Usage
xml.fct.board.composition(x)
Arguments
x |
A list with data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for capita
Description
Reads XML data for capita
Usage
xml.fct.capital(x)
Arguments
x |
A list with capital summary data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for capital reduction data
Description
Reads XML data for capital reduction data
Usage
xml.fct.capital.reduction(x)
Arguments
x |
A list with data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for commitee composition
Description
Reads XML data for commitee composition
Usage
xml.fct.committee.composition(x)
Arguments
x |
A list with data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for compensation
Description
Reads XML data for compensation
Usage
xml.fct.compensation(x)
Arguments
x |
A list with compensation data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for compensation summary data
Description
Reads XML data for compensation summary data
Usage
xml.fct.compensation.summary(x)
Arguments
x |
A list with compensation summary data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for debt
Description
Reads XML data for debt
Usage
xml.fct.debt(x)
Arguments
x |
A list with data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for div details
Description
Reads XML data for div details
Usage
xml.fct.div.details(x)
Arguments
x |
A list with data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for family related parts
Description
Reads XML data for family related parts
Usage
xml.fct.family.related.parts(x)
Arguments
x |
A list with data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for family relations
Description
Reads XML data for family relations
Usage
xml.fct.family.relations(x)
Arguments
x |
A list with data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for patents details
Description
Reads XML data for patents details
Usage
xml.fct.intangible.details(x)
Arguments
x |
A list with data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for repurchases
Description
Reads XML data for repurchases
Usage
xml.fct.repurchases(x)
Arguments
x |
A list with data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for responsibles documents
Description
Reads XML data for responsibles documents
Usage
xml.fct.responsible(x)
Arguments
x |
A list with data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for splits/inplits data
Description
Reads XML data for splits/inplits data
Usage
xml.fct.splits.inplits(x)
Arguments
x |
A list with data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for stock value
Description
Reads XML data for stock value
Usage
xml.fct.stock.values(x)
Arguments
x |
A list with stock value data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for stockholder data
Description
Reads XML data for stockholder data
Usage
xml.fct.stockholder(x)
Arguments
x |
A list with stockholder data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for stock details
Description
Reads XML data for stock details
Usage
xml.fct.stocks.details(x)
Arguments
x |
A list with data |
Value
A dataframe
Examples
# No example (INTERNAL)
Reads XML data for transaction data
Description
Reads XML data for transaction data
Usage
xml.fct.transactions.related(x)
Arguments
x |
A list with transaction data |
Value
A dataframe
Examples
# No example (INTERNAL)