I’m working in Power BI and am using R-script to insert a dynamic date in a URL.
The URL in question is as following
Tests <- read.csv(file=paste0("https://www,testtest/getCsv?startdate_Day=1&startdate_Month=01&startdate_Year=2016"), header=TRUE, sep=";")
My problem is that the day month and year value has to always be the current date
I have tried or example
Year<-Sys.Date() format(Year, format="%Y")
Month<-Sys.Date() format(Month, format="%m")
Day<-Sys.Date() format(Day, format="%d")
<- read.csv(file=paste0("read.csv(file=paste0("https://www,testtest/getCsv??startdate_Day=", Day,"&startdate_Month=", Month,"&startdate_Year=", Year"), header=TRUE, sep=",")
But then I get the following error:
startdate_Day=2016-08-12&startdate_Month=2016-08-12&startdate_Year=2016-08-12
My question is how I fill Startdate_Day, Startdate_Month and Startdate_Year automatically with the current Day, Month and Year?
If that's the exact code you're running, then you're having a few problems:
As noted, you have a comma in your url (www.test), do you mean to?
Your calls to Sys.Date() and format aren't written properly.
Try this:
# Get the date parts we need
Year <-format(Sys.Date(), format="%Y")
Month <- format(Sys.Date(), format="%m")
Day <- format(Sys.Date(), format="%d")
# Create the file string
file_string <- paste0("https://www.testtest/getCsv??startdate_Day=", Day,"&startdate_Month=", Month,"&startdate_Year=", Year)
# Run read.csv
EnergyStockVolumeData <- read.csv(file_string, header = TRUE, sep = ";")
Related
I'm really struggling to extract the proper information from several thousands PDF files from NTSB (some Dates and numbers to be specific); these PDFs don't require to be OCRed and each report is almost identical in length and layout information.
I need to extract the date and the time of the accident (first page) and some other information, like Pilot's age or its Flight experience. What I tried does the job for several files but is not working for each file the since code I am using is poorly written.
# an example with a single file
library(pdftools)
library(readr)
# Download the file and read it row by row
file <- 'http://data.ntsb.gov/carol-repgen/api/Aviation/ReportMain/GenerateNewestReport/89789/pdf' # less than 100 kb
destfile <- paste0(getwd(),"/example.pdf")
download.file(file, destfile)
pdf <- pdf_text(destfile)
rows <-scan(textConnection(pdf),
what="character", sep = "\n")
# Extract the date of the accident based on the 'Date & Time' occurrence.
date <-rows[grep(pattern = 'Date & Time', x = rows, ignore.case = T, value = F)]
date <- strsplit(date, " ")
date[[1]][9] #this method is not desirable since the date will not be always in that position
# Pilot age
age <- rows[grep(pattern = 'Age', x = rows, ignore.case = F, value = F)]
age <- strsplit(age, split = ' ')
age <- age[[1]][length(age[[1]])] # again, I'm using the exact position in that list
age <- readr::parse_number(age) #
The main issue I got is when I am trying to extract the date and time of the accident. Is it possible to extract that exact piece of information by avoiding using a list as I did here?
I think the best approach to achieve what you want is to use regex.
In this case I use stringr library. The main idea with regex is to find
the desire string pattern, in this case is the date 'July 29, 2014, 11:15'
Take on count that you'll have to check the date format for each pdf file
library(pdftools)
library(readr)
library(stringr)
# Download the file and read it row by row
file <- 'http://data.ntsb.gov/carol-repgen/api/Aviation/ReportMain/GenerateNewestReport/89789/pdf' # less than 100 kb
destfile <- paste0(getwd(), "/example.pdf")
download.file(file, destfile)
pdf <- pdf_text(destfile)
## New code
# Regex pattern for date 'July 29, 2014, 11:15'
regex_pattern <- "[T|t]ime\\:(.*\\d{2}\\:\\d{2})"
# Getting date from page 1
grouped_matched <- str_match_all(pdf[1], regex_pattern)
# This returns a list with groups. You're interested in group 2
raw_date <- grouped_matched[[1]][2] # First element, second group
# Clean date
date <- trimws(raw_date)
# Using dplyr
library(dplyr)
date <- pdf[1] %>%
str_match_all(regex_pattern) %>%
.[[1]] %>% # First list element
.[2] %>% # Second group
trimws() # Remove extra white spaces
You can make a function to extract the date changing the regex pattern for different files
Regards
Wish to scrape weather data from
https://www.wetterzentrale.de/weatherdata.php?station=260&jaar=2019&maand=1&dag=1
From 2019-01-01 until today, yet I don't know how to write a code that changes jaar=2019 (i.e., year=2019), maand=1 (i.e., month=1) and dag=1 (i.e., day=1) to the desired days.
I tried to work with lapply as:
years <- c("2019", "2020")
urls <- rbindlist(lapply(years, function(x) {
url <- paste(https://www.wetterzentrale.de/weatherdata.php?station=260&jaar=2019&maand=1&dag=1, sep = "")
data.frame(url)
} ))
Hence this only gives the urls for 2019 and 2020. Is there a way to include months and days?
library(lubridate)
allYourDates <- seq(ymd(20190101), Sys.Date(), by = "days")
urls <- paste("https://www.wetterzentrale.de/weatherdata.php?station=260&jaar=", year(allYourDates)
, "&maand=", month(allYourDates)
, "&dag=", day(allYourDates)
, sep = "")
I am trying to complete a problem that pulls from two data sets that need to be combined into one data set. To get to this point, I need to rbind both data sets by the year-month information. Unfortunately, the first data set needs to be tallied by year-month info, and I can't seem to figure out how to change the date so I can have month-year info rather than month-day-year info.
This is data on avalanches and I need to write code totally the number of avalanches each moth for the Snow Season, defined as Dec-Mar. How do I do that?
I keep trying to convert the format of the date to month-year but after I change it with
as.Date(avalancheslc$Date, format="%y-%m")
all the values for Date turn to NA's....help!
# write the webscraper
library(XML)
library(RCurl)
avalanche<-data.frame()
avalanche.url<-"https://utahavalanchecenter.org/observations?page="
all.pages<-0:202
for(page in all.pages){
this.url<-paste(avalanche.url, page, sep=" ")
this.webpage<-htmlParse(getURL(this.url))
thispage.avalanche<-readHTMLTable(this.webpage, which=1, header=T)
avalanche<-rbind(avalanche,thispage.avalanche)
}
# subset the data to the Salt Lake Region
avalancheslc<-subset(avalanche, Region=="Salt Lake")
str(avalancheslc)
avalancheslc$monthyear<-format(as.Date(avalancheslc$Date),"%Y-%m")
# How can I tally the number of avalanches?
The final output of my dataset should be something like:
date avalanches
2000-1 18
2000-2 4
2000-3 10
2000-12 12
2001-1 52
This should work (I tried it on only 1 page, not all 203). Note the use of the option stringsAsFactors = F in the readHTMLTable function, and the need to add names because 1 column does not automatically get one.
library(XML)
library(RCurl)
library(dplyr)
avalanche <- data.frame()
avalanche.url <- "https://utahavalanchecenter.org/observations?page="
all.pages <- 0:202
for(page in all.pages){
this.url <- paste(avalanche.url, page, sep=" ")
this.webpage <- htmlParse(getURL(this.url))
thispage.avalanche <- readHTMLTable(this.webpage, which = 1, header = T,
stringsAsFactors = F)
names(thispage.avalanche) <- c('Date','Region','Location','Observer')
avalanche <- rbind(avalanche,thispage.avalanche)
}
avalancheslc <- subset(avalanche, Region == "Salt Lake")
str(avalancheslc)
avalancheslc <- mutate(avalancheslc, Date = as.Date(Date, format = "%m/%d/%Y"),
monthyear = paste(year(Date), month(Date), sep = "-"))
I downloaded stock market data from Yahoo (code below) - for context, at first I tried with getSymbols(^DJI) but I got error messages possibly related to Yahoo... different issue.
The point is that once downloaded, and imported into R, I massaged it into a format close enough to a time series to be able to run chartSeries(DJI):
require(RCurl)
require(foreign)
x <- getURL("https://raw.githubusercontent.com/RInterested/datasets/gh-pages/%5EDJI.csv")
DJI <- read.csv(text = x, sep =",")
DJI$Date <- as.Date(DJI$Date, format = "%m/%d/%Y") # Formatting Date as.Date
rownames(DJI) <- DJI$Date # Assigning Date to row names
DJI$Date <- NULL # Removing the Date column
chartSeries(DJI, type="auto", theme=chartTheme('white'))
even if the dataset is not really a time series:
> is.ts(DJI)
[1] FALSE
The problem comes about when I try to find out the date of, for instance, the minimum closing value of the Dow. I can do something like
> DJI[DJI$Close == min(DJI$Close),]
Open High Low Close Adj.Close Volume
1985-05-01 1257.18 1262.81 1239.07 1242.05 1242.05 10050000
yielding the entire row, including the row name (1985-05-01), which is the only part I want. However, if I insist on just getting the actual date, I have to juggle a second dataset containing the dates in one of the columns:
require(RCurl)
require(foreign)
x <- getURL("https://raw.githubusercontent.com/RInterested/datasets/gh-pages/%5EDJI.csv")
DJI <- read.csv(text = x, sep =",")
DJI$Date <- as.Date(DJI$Date, format = "%m/%d/%Y") # Formatting Date as.Date
rownames(DJI) <- DJI$Date # Assigning Date to row names
DJI.raw <- DJI # Second dataset for future subsetting
DJI$Date <- NULL # Removing the Date column
which does allow me to run
> DJI.raw$Date[DJI.raw$Close == min(DJI.raw$Close)]
[1] "1985-05-01"
Further, I don't think that turning the dataset into an .xts file would help.
I'm not clear what you want but it sounds like you just want the date? You mention xts is not an option (which would have been runnable)
time(as.xts(DJI))[which.min(DJI$Close)] # POSIXct format
# [1] "1985-05-01 EDT"
Otherwise a simple rownames + which.min would get the date for you?
as.Date(rownames(DJI)[which.min(DJI$Close)]) # Date format
# [1] "1985-05-01"
I would like to download daily data from yahoo for the S&P 500, the DJIA, and 30-year T-Bonds, map the data to the proper time zone, and merge them with my own data. I have several questions.
My first problem is getting the tickers right. From yahoo's website, it looks like the tickers are: ^GSPC, ^DJI, and ^TYX. However, ^DJI fails. Any idea why?
My second problem is that I would like to constrain the time zone to GMT (I would like to ensure that all my data is on the same clock, GMT seems like a neutral choice), but I couldn' get it to work.
My third problem is that I would like to merge the yahoo data with my own data, obtained by other means and available in a different format. It is also daily data.
Here is my attempt at constraining the data to the GMT time zone. Executed at the top of my R script.
Sys.setenv(TZ = "GMT")
# > Sys.getenv("TZ")
# [1] "GMT"
# the TZ variable is properly set
# but does not affect the time zone in zoo objects, why?
Here is my code to get the yahoo data:
library("tseries")
library("xts")
date.start <- "1999-12-31"
date.end <- "2013-01-01"
# tickers <- c("GSPC","TYX","DJI")
# DJI Fails, why?
# http://finance.yahoo.com/q?s=%5EDJI
tickers <- c("GSPC","TYX") # proceed without DJI
z <- zoo()
index(z) <- as.Date(format(time(z)),tz="")
for ( i in 1:length(tickers) )
{
cat("Downloading ", i, " out of ", length(tickers) , "\n")
x <- try(get.hist.quote(
instrument = paste0("^",tickers[i])
, start = date.start
, end = date.end
, quote = "AdjClose"
, provider = "yahoo"
, origin = "1970-01-01"
, compression = "d"
, retclass = "zoo"
, quiet = FALSE )
, silent = FALSE )
print(x[1:4]) # check that it's not empty
colnames(x) <- tickers[i]
z <- try( merge(z,x), silent = TRUE )
}
Here is the dput(head(df)) of my dataset:
df <- structure(list(A = c(-0.011489000171423, -0.00020300000323914,
0.0430639982223511, 0.0201549995690584, 0.0372899994254112, -0.0183669999241829
), B = c(0.00110999995376915, -0.000153000000864267, 0.0497750006616116,
0.0337960012257099, 0.014121999964118, 0.0127800004556775), date = c(9861,
9862, 9863, 9866, 9867, 9868)), .Names = c("A", "B", "date"
), row.names = c("0001-01-01", "0002-01-01", "0003-01-01", "0004-01-01",
"0005-01-01", "0006-01-01"), class = "data.frame")
I'd like to merge the data in df with the data in z. I can't seem to get it to work.
I am new to R and very much open to your advice about efficiency, best practice, etc.. Thanks.
EDIT: SOLUTIONS
On the first problem: following GSee's suggestions, the Dow Jones Industrial Average data may be downloaded with the quantmod package: thus, instead of the "^DJI" ticker, which is no longer available from yahoo, use the "DJIA" ticker. Note that there is no caret in the "DJIA" ticker.
On the second problem, Joshua Ulrich points out in the comments that "Dates don't have timezones because days don't have a time component."
On the third problem: The data frame appears to have corrupted dates, as pointed out by agstudy in the comments.
My solutions rely on the quantmod package and the attached zoo/xts packages:
library(quantmod)
Here is the code I have used to get proper dates from my csv file:
toDate <- function(x){ as.Date(as.character(x), format("%Y%m%d")) }
dtz <- read.zoo("myData.csv"
, header = TRUE
, sep = ","
, FUN = toDate
)
dtx <- as.xts(dtz)
The dates in the csv file were stored in a single column in the format "19861231". The key to getting correct dates was to wrap the date in "as.character()". Part of this code was inspired from R - Stock market data from csv to xts. I also found the zoo/xts manuals helpful.
I then extract the date range from this dataset:
date.start <- start(dtx)
date.end <- end(dtx)
I will use those dates with quantmod's getSymbols function so that the other data I download will cover the same period.
Here is the code I have used to get all three tickers.
tickers <- c("^GSPC","^TYX","DJIA")
data <- new.env() # the data environment will store the data
do.call(cbind, lapply( tickers
, getSymbols
, from = date.start
, to = date.end
, env = data # data saved inside an environment
)
)
ls(data) # see what's inside the data environment
data$GSPC # access a particular ticker
Also note, as GSee pointed out in the comments, that the option auto.assign=FALSE cannot be used in conjunction with the option env=data (otherwise the download fails).
A big thank you for your help.
Yahoo doesn't provide historical data for ^DJI. Currently, it looks like you can get the same data by using the ticker "DJIA", but your mileage may vary.
It does work in this case because you're only dealing with Dates
the df object your provided is yearly data beginning in the year 0001. So, that's probably not what you wanted.
Here's how I would fetch and merge those series (or use an environment and only make one call to getSymbols)
library(quantmod)
do.call(cbind, lapply(c("^GSPC", "^TYX"), getSymbols, auto.assign=FALSE))