I'm trying to use the eventstudies package but I get a strange error message when running the function despite following the instructions here.
My code is such as :
> datesevents <-data.frame("name"=c("Aaa negative","Aaa stable","Aaa negative ", "Aa1 stable", "Aa1 stable"), "Date"=c("2012-02-13","2014-0-28","2015-10-23", "2016-06-24","2018-05-25"))
> datesevents$name<-as.character(datesevents$name)
> datesevents$Date<-as.character(datesevents$Date)
> fiveCDS <- read.csv(file.choose())
> colnames(fiveCDS)<-c("Date", "Austria")
> dataCDS <- c(NA,diff(log(as.numeric(fiveCDS$Austria)), lag=1))
> fiveCDS$CDS = dataCDS
> datazoo <- read.zoo(fiveCDS)
> eventstudy(firm.returns = datazoo, event.list = datesevents, event.window = 5,type = "constantMeanReturn", to.remap = TRUE, remap = "cumsum", inference = TRUE, inference.strategy = "bootstrap", model.args = NULL)
And I get the following message
Error in phys2eventtime(z = returns$firm.returns, events = event.list[i, :
events$when should be one of 'Date' or 'date-time' classes.
So, from my understing it means that the 2 columns with the dates in my data.frame() isn't considered as a class of dates ?
In any case, how can I fix this ?
Thank you !
Probably you need the Date column to be of the class Date as well. Try
datesevents$Date = as.Date(datesevents$Date)
See ?Date for info about the Date class, and ?as.Date for info about the conversion function.
Related
I`m trying to visualise data of the following form:
date volaEUROSTOXX volaSA volaKENYA25 volaNAM volaNIGERIA
1 10feb2012 0.29844454 0.1675901 0.007862087 0.12084170 0.10247617
2 17feb2012 0.31811157 0.2260064 0.157017220 0.33648935 0.22584127
3 24feb2012 0.30013672 0.1039974 0.083863921 0.11694768 0.16388161
To do so, I first converted the date (stored as a character in the original data frame) into a date-format. Which works just fine:
vola$date <- as.Date(vola$date)
str(vola$date)
Date[1:543], format: "2012-02-10" "2012-02-17" "2012-02-24" "2012-03-02" "2012-03-09"
However, if I now try to graph my data by using the chart.TimeSeries command, I get the following:
chart.TimeSeries(volatility_annul_stringdate,lwd=2,auto.grid=F,ylab="Annualized Log Volatility",xlab="Time",
main="Log Volatility",lty=1,
legend.loc="topright")
Error in if (class(x) == "numeric") { : the condition has length > 1
I tried:
Converting my date variable (in the date format) further into a time series object:
vola$date <- ts(vola$date, frequency=52, start=c(2012,9)) #returned same error from above
Converting the whole data set using its-command:
vol.xts <- xts(vola, order.by= vola$date, unique = TRUE ) # which then returned:
order.by requires an appropriate time-based object
#even though date is a time-series
What am I doing wrong? I am rather new to RStudio.. I really want to use the chart.TimeSeries command. Can someone help me?
Thanks in advance!
My MRE:
library(PerformanceAnalytics)
vola <- structure(list(date_2 = c("2012-02-10", "2012-02-17", "2012-02-24",
"2012-03-02"), volaEUROSTOXX = c(0.298444539308548, 0.318111568689346,
0.300136715173721, 0.299697518348694), volaKENYA25 = c(0.00786208733916283,
0.157017216086388, 0.0838639214634895, 0.152377054095268), volaNAM = c(0.120841704308987,
0.336489349603653, 0.116947680711746, 0.157027021050453), volaNIGERIA = c(0.102476172149181,
0.225841268897057, 0.163881614804268, 0.317349642515182), volaSA = c(0.167590111494064,
0.226006388664246, 0.103997424244881, 0.193037077784538), date = structure(c(1328832000,
1329436800, 1330041600, 1330646400), tzone = "UTC", class = c("POSIXct",
"POSIXt"))), row.names = c(NA, -4L), class = c("tbl_df", "tbl",
"data.frame"))
vola <- subset(vola, select = -c(date))
vola$date_2 <- as.Date(vola$date_2)
chart.TimeSeries(vola,lwd=2,auto.grid=F,ylab="Annualized Log Volatility",xlab="Time",
main="Log Volatility",lty=1,
legend.loc="topright")
#This returns the above mentioned error message.
#Thus, I tried the following:
vola$date_2 <- ts(vola$date_2, frequency=52, start=c(2012,9))
chart.TimeSeries(vola,lwd=2,auto.grid=F,ylab="Annualized Log Volatility",xlab="Time",
main="Log Volatility",lty=1,
legend.loc="topright")
#Which returned a different error (as described above)
#And I tried:
vol.xts <- xts(vola, order.by= vola$date_2, unique = TRUE )
#This also returned an error message.
#My intention was to then run:
#chart.TimeSeries(vol.xts,lwd=2,auto.grid=F,ylab="Annualized Log Volatility",xlab="Time",
main="Log Volatility",lty=1,
legend.loc="topright")
The documentation of PerformanceAnalytics::chart.TimeSeries is a bit vague. The issue is that when passing a dataframe you have to set the dates as row.names. To this end I first converted your data (which is a tibble) to a data.frame. Afterwards I add the dates as rownames and drop the date column:
library(PerformanceAnalytics)
vola <- as.data.frame(vola)
vola <- subset(vola, select = -c(date))
row.names(vola) <- as.Date(vola$date_2)
vola$date_2 <- NULL
chart.TimeSeries(vola,
lwd = 2, auto.grid = F, ylab = "Annualized Log Volatility", xlab = "Time",
main = "Log Volatility", lty = 1,
legend.loc = "topright"
)
I want to download the occurrence data from gbif website and I use the following R script. When I run the script, I got an error with the following message "Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, : arguments imply differing number of rows: 1, 0)". It would be highly appreciated if anyone could help me with this.
My data: data
My R script:
flist<-read_excel("Mekong fish.xlsx",sheet="Sheet1")
##Loop
fname<-list()
Occ<-list()
datfish<-list()
name_list<-unique(flist$Updated_name)
# create for loop to produce ggplot2 graphs
for (i in seq_along(name_list)) {
# create plot for each Occurrence in df
Occ[[i]] <-occ_search(scientificName = name_list[i], limit=2)
fname[[i]]<-occ_search(scientificName = name_list[i],
fields = c("species", "country","decimalLatitude", "decimalLongitude"),
hasCoordinate=T, limit= Occ[[i]]$meta[4],return ="data")
datfish[[i]]<-as.data.frame(fname[[i]]$data)
}
I got a different error:
Expecting logical in D1424 / R1424C4: got 'in Lao'Expecting logical in D1426 / R1426C4: got 'in China'Expecting logical in D1467 / R1467C4: got 'only Cambodia'Expecting logical in D1469 / R1469C4: got 'only in VN'Expecting logical in D1473 / R1473C4: got 'only in China'Expecting logical in D1486 / R1486C4: got 'only in Malaysia'Expecting logical in D1488 / R1488C4: got 'only 1 point in VN'
I think the problem is caused in some fields in the 4th column. I don't have the right packages installed to run your code. But I got a different error (package missing) once i dropped the fourth column.
flist<-read_excel("~/Downloads/Mekong fish.xlsx",sheet="Sheet1")
flist <=subset(flist, select = -4)
...
EDIT:
This worked for me. read_excel assigned column 4 the type boolean. When I explicitly set it to text it worked.
library(readxl)
library(rgbif)
library(raster)
flist<-read_excel("~/Downloads/Mekong fish.xlsx",
sheet="Sheet1",
col_types = c("numeric", "text", "numeric", "text"))
flist
##Loop
fname<-list()
Occ<-list()
datfish<-list()
name_list<-unique(flist$Updated_name)
# create for loop to produce ggplot2 graphs
for (i in seq_along(name_list[1:2])) {
message(i)
# # create plot for each Occurrence in df
Occ[[i]] <-occ_search(scientificName = name_list[i], limit=2)
message(Occ[[i]])
fname[[i]]<-occ_search(scientificName = name_list[i],
fields = c("species", "country","decimalLatitude", "decimalLongitude"),
hasCoordinate=T, limit= Occ[[i]]$meta[4],return ="data")
message(fname[[i]])
datfish[[i]]<-as.data.frame(fname[[i]]$data)
message(datfish[[i]])
}
> 1
> list(offset = 0, limit = 2, endOfRecords = FALSE, count = >15)list(list(name = c("Animalia", "Chordata", "Actinopterygii",
> "Cypriniformes", "Cyprinidae", "Aaptosyax", "Aaptosyax grypus"), key = > > c("1", "44", "204", "1153", "7336", "2363805", "2363806"),
> etc...
I was trying to analyze my RR intervals using the RHRV package.
I have used:
hrv.data = CreateHRVData()
hrv.data = SetVerbose(hrv.data, TRUE)
hrv.data = LoadBeatRR(hrv.data, "dataset.txt", RecordPath = "#the path of dataset.txt here", datetime = "1/1/1900 0:0:0", verbose = NULL)
Unfortunately, when I do this I get the warning message :
"NAs introduced by coercion".
And all my following analyses do not work.
I do not see what the problem could be.
You should make sure the time, hr and rr variables are named as such: "Time", "niHR", and "RR" respectively.
A work-around would to just to manually create the beat object.
hrv.data$Beat <- readr::read_delim("txt file") %>%
dplyr::rename("Time" = time, "niHR" = hr, "RR" = rr) %>%
dplyr::select(Time, niHR, RR)
hrv.data <- RHRV::BuildNIHR(hrv.data)
I am trying to calculate the Gini index for each row of my database. Each row is a customer and each column is a monthly session. So what i need to do is to add a column with the Gini index by row, for each customer throughout the 12 months.
See example attached
I found some examples online and did this:
Gini_index <- apply(DT_file[,c('sessions_201607_pct','sessions_201608_pct', 'sessions_201609_pct','sessions_201610_pct','sessions_201611_pct','sessions_201612_pct','sessions_201701_pct','sessions_201702_pct','sessions_201703_pct','sessions_201704_pct','sessions_201705_pct','sessions_201706_pct')], 1, gini)
However, I get the following error:
Error in match.fun(FUN) : object 'gini' not found
I have installed both Ineq and Reldist (and libraries) so I don't know why this isn't working.
Try to do this to have your gini's coeff by column :
library(ineq)
coeff= NULL
for (i in colnames(your_data[,-1])){
coeff= c(coeff,round(ineq(your_data[,i],type = 'Gini'),4))
}
data_coeff = data.frame(cbind(coeff,colnames(your_data[,-1])))
colnames(data_coeff) = c("Coeff","Colnames")
If you want it by for each rows try this :
your_new_data = as.data.frame(t(your_data[,-1]), row.names =T)
colnames(your_new_data) = your_data[,1]
ind = NULL
for (i in colnames(your_new_data)){
ind = c(ind,round(ineq(your_new_data[,i],type = 'Gini'),4))
}
data_coeff= data.frame(cbind(ind,colnames(your_new_data)))
colnames(data_coeff) = c("Coeff","customer")
Finaly you add your coeffs at the end of your data_frame with a merge for instance :
your_data_final = merge(your_data,data_coeff, by = "customer" )
I am currently facing an error mentioned below which is related to NULL values being coerced to a data frame. The data set does contain nulls, however I have tried both is.na() and is.null() functions to replace the null values with something else. The data is stored on hdfs and is stored in a pig.hive format. I have also attached the code below. The code works fine if I remove v[,25] from the key.
Code:
AM = c("AN");
UK = c("PP");
sample.map <- function(k,v){
key <- data.frame(acc = v[!which(is.na(v[,1],1],
year = substr(v[!which(is.na(v[,1]),2],1,4),
month = substr(v[!which(is.na(v[,1]),2],5,6))
value <- data.frame(v[,3],count=1)
keyval(key,value)
}
sample.reduce <- function(key,v){
AT <- sum(v[which(v[,1] %in% AM=="TRUE"),2])
UnknownT <- sum(v[which(v[,1] %in% UK=="TRUE"),2])
Total <- AT + UnknownT
d <- data.frame(AT,UnknownT,Total)
keyval(key,d)
}
out <- mapreduce(input ="/user/hduser/input",
output = "/user/hduser/output",
input.format = make.input.format("pig.hive", sep = "\u0001")
output.format = make.output.format("csv", sep = ","),
map= sample.map)
reduce = sample.reduce)
Error:
Warning in asMethod(object) : NAs introduced by coercion
Warning in split.default(1:rmr.length(y), unique(ind), drop = TRUE) : data length is not a multiple of split variable
Warning in rmr.split(x, x, FALSE, keep.rownames = FALSE) : number of items to replace is not a multiple of replacement length Warning in split.default(1:rmr.length(y), unique(ind), drop = TRUE) :
data length is not a multiple of split variable
Warning in rmr.split(v, ind, lossy = lossy, keep.rownames = TRUE) : number of items to replace is not a multiple of replacement length
Error in as(x, class(k)) :
no method or default for coercing “NULL” to “data.frame”
Calls: <Anonymous> ... apply.reduce -> c.keyval -> reduce.keyval -> lapply -> FUN -> as No traceback available
UPDATE
I have added the sample data and edited the code above. Hope this helps!
Sample Data:
NULL,"2014-03-14","PP"
345689202,"2014-03-14","AN"
234539390,"2014-03-14","PP"
123125444,"2014-03-14","AN"
NULL,"2014-03-14","AN"
901828393,"2014-03-14","AN"
There are some issues with as which have been identified recently. I don't see why as can't handle this by default, but you can modify coerce which handles the conversion with an S4 method to call as.data.frame.
setMethod("coerce",c("NULL","data.frame"), function(from, to, strict=TRUE) as.data.frame(from))
[1] "coerce"
as(NULL,"data.frame")
data frame with 0 columns and 0 rows