Comments (7)
There is no special support (yet) in finstr. But, when the id of the XBRL concept is known, it is possible to extract it from the XBRL directly. The sec.gov page (interactive data) exposes the concept id when clicked on the description in the table.
To extract the value from XBRL, join the element (concept) to the fact (value) and context (period, dimensions). Here is an example for the dei_EntityCommonStockSharesOutstanding
in 10-K:
# Apple 10-K report:
doc_url <- "https://www.sec.gov/Archives/edgar/data/320193/000162828016020309/aapl-20160924.xml"
# download and parse XBRL
library(XBRL)
old_o <- options(stringsAsFactors = FALSE)
xbrl_data <- xbrlDoAll(doc_url)
options(old_o)
library(dplyr)
xbrl_data$element %>%
filter(elementId == "dei_EntityCommonStockSharesOutstanding") %>%
left_join(xbrl_data$fact, by = "elementId") %>%
left_join(xbrl_data$context, by = "contextId") %>%
mutate(value = as.numeric(fact) * 10 ^ as.numeric(decimals)) %>%
select(elementId, value, unitId, endDate)
# elementId value unitId endDate
# 1 dei_EntityCommonStockSharesOutstanding 5332313 shares 2016-10-14
from finstr.
excellent, thanks for the help.
from finstr.
Thanks bergant for this excellent package working smoothly with SEC filings!
I am particularly looking for debt as reported in the balance sheet and debt breakup as given in the Notes to Financial Statement. The id of the XBRL concept is known: us-gaap_LongTermDebtNoncurrent
I ran into some error while running the query:
install.packages("devtools")
devtools::install_github("bergant/finstr")
Library(XBRL)
xbrl_url17 <- https://www.sec.gov/Archives/edgar/data/320193/000032019317000009/aapl-20170701.xml
old.o <- options(stringsAsFactors = FALSE)
xbrl_data17 <- xbrlDoAll(xbrl_url17)
options(old.o)
library(dplyr)
xbrl_data17$element %>% filter(elemntId =="us-gaap_LongTermDebtNoncurrent") %>% left_join(xbrl_data17$fact, by = "elementId") %>% left_join(xbrl_data17$context, by = "contextId") %>% mutate(value = as.numeric(fact) * 10 ^ as.numeric(decimals)) %>% select(elementId, value, unitId, endDate)
Error in filter(elemntId == "us-gaap_LongTermDebtNoncurrent") : object 'elemntId' not found
Can you pls help on this? How can I get this debt number as well as debt breakup as pasted from the footnotes
Kind regards,
from finstr.
First check the missing e
in elemntId
(in the filter
command...)
from finstr.
Thanks for pointing this. Still, I am not very much sure why I am getting an error : "Error in filter_impl(.data, quo) :
Result must have length 20798, not 166384"
Pls see my code below
install.packages("devtools")
devtools::install_github("bergant/finstr")
# Parsing AAPL 10Q ended July 2017 from SEC with XBRL package
library(XBRL)
xbrl_url17q <- "https://www.sec.gov/Archives/edgar/data/320193/000032019317000009/aapl-20170701.xml"
old.o <- options(stringsAsFactors = FALSE)
xbrl_data17 <- xbrlDoAll(xbrl_url17q)
options(old.o)
# after identifying the relevant element ID for long term debt: "us-gaap_LongTermDebtNoncurrent"
xbrl_data17$element %>%
filter(xbrl_data17$element == "us-gaap_LongTermDebtNoncurrent") %>%
left_join(xbrl_data17$fact, by = "elementID") %>%
left_join(xbrl_data17$context, by = "contextID") %>%
mutate(value = as.numeric (fact) * 10 ^ as.numeric(decimals)) %>%
select( elementID, value, unitID, endDate)
This still shows me the error:
Error in filter_impl(.data, quo) :
Result must have length 20798, not 166384
Best,
from finstr.
The following code
xbrl_data17$element %>%
filter(elementId == "us-gaap_LongTermDebtNoncurrent") %>%
left_join(xbrl_data17$fact, by = "elementId") %>%
left_join(xbrl_data17$context, by = "contextId") %>%
mutate(value = as.numeric (fact) * 10 ^ as.numeric(decimals)) %>%
select( elementId, value, unitId, endDate)
will return only values for the us-gaap_LongTermDebtNoncurrent
element:
#> elementId value unitId endDate
#> 1 us-gaap_LongTermDebtNoncurrent 75427 usd 2016-09-24
#> 2 us-gaap_LongTermDebtNoncurrent 89864 usd 2017-07-01
For debt summary table you should find all elements from "http://www.apple.com/role/DebtSummaryOfTermDebtDetails" role,
find their hierarchy and add facts and contexts.
Maybe we can start like this (this will not create a final table):
relations <-
finstr::xbrl_get_relations(xbrl_data17, role_id = "http://www.apple.com/role/DebtSummaryOfTermDebtDetails", lbase = "presentation")
elements <-
data.frame(
elementId = with(relations, unique(c(fromElementId, toElementId))),
stringsAsFactors = FALSE
) %>%
dplyr::left_join(xbrl_data17$element, by = c("elementId")) %>%
dplyr::left_join(relations, by = c("elementId" = "toElementId")) %>%
dplyr::left_join(xbrl_data17$label, by = c("elementId")) %>%
dplyr::filter(labelRole == "http://www.xbrl.org/2003/role/label") %>%
dplyr::transmute(elementId, parentId = fromElementId, order, type, balance, labelString)
elements_h <- finstr::get_elements_h(elements)
elements_h %>%
filter(type != "nonnum:domainItemType") %>%
left_join(xbrl_data17$fact, by = "elementId") %>%
left_join(xbrl_data17$context, by = "contextId") %>%
select(id, elementId, order, labelString, fact, unitId, startDate, endDate, type, contextId) %>%
arrange(id)
# ...
from finstr.
Hi,
I want to extract the Balance Sheet,Cash flow and income statement tables from 10-k and 10-q filings.
can this package help me?
from finstr.
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from finstr.