Package 'GetDFPData'

Title: Reading Annual Financial Reports from Bovespa's DFP, FRE and FCA System
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.
Authors: Marcelo Perlin [aut, cre]
Maintainer: Marcelo Perlin <[email protected]>
License: GPL-2
Version: 1.6
Built: 2024-11-04 06:40:48 UTC
Source: CRAN

Help Index


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)

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)

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)

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)