Working in R, I am having difficulty building a JSON file that I would use in an API call.
The required format for the JSON file can be seen here:
https://developer.trimblemaps.com/restful-apis/routing/route-reports/post-route-reports/
The input to the exercise is a dataframe like so:
Shipper_Latitude <- c(1,2,3,4)
Shipper_Longitude <- c(1,2,3,4)
r_combine.NewShipperLat <- c(1,2,3,4)
r_combine.NewShipperLon <- c(1,2,3,4)
r4 <- data.frame(Shipper_Latitude,Shipper_Longitude,r_combine.NewShipperLat,r_combine.NewShipperLon)
My attempt at building the required JSON file is as follows:
# assemble lat and long for starting location:
tempfuna <- function(Lat,Lon) {list(Coords = list(Lat = Lat,Lon = Lon))}
df_jsona <- mapply(FUN = tempfuna,Lat = r4$Shipper_Latitude, Lon = r4$Shipper_Longitude)
df_jsona <- lapply(df_jsona, function(x) {list(Coords = x)})
# assemble lat and long for ending location:
tempfunb <- function(Lat,Lon) {list(Coords = list(Lat = Lat,Lon = Lon))}
df_jsonb <- mapply(FUN = tempfunb,Lat = r4$r_combine.NewShipperLat, Lon = r4$r_combine.NewShipperLon)
df_jsonb <- lapply(df_jsonb, function(x) {list(Coords = x)})
# assemble list of ReportRoutes:
tempfunc <- function(A,B) {list(ReportRoutes = list(Stops = list(A,B)))}
df_jsonc <- mapply(FUN = tempfunc,A = df_jsona, B = df_jsonb)
# create final list:
post_body <- list(ReportRoutes = df_jsonc)
I get an error when I use the resulting file in an API call.
I think the problem is that the list items in the ReportRoutes list are incorrectly named. For example, the first item is named “Coords.ReportRoutes” instead of [[1]]].
How can I rework the above to produce the required JSON file?
Related
Using the following snippet it is possible to iterate two api call in json format
At the end of the loop there is a command with transforms json to data frame
How is it possible to keep in every iteration all these variables and fill NA if a value in the specific variable does not exist in a specific iteration?
library(jsonlite)
library(httpuv)
library(httr)
myapp <- oauth_app(appname = "insert_your_credentials",
key = "insert_your_credentials",
secret = "insert_your_credentials")
github_token <- oauth2.0_token(oauth_endpoints("github"), myapp)
gtoken <- config(token = github_token)
df <- data.frame(link = c("https://api.github.com/search/commits?q=%22image%22+AND+%22covid%22?page=1&per_page=100", "https://api.github.com/search/commits?q=%22image%22+AND+%22covid%22?page=2&per_page=100"))
for (i in 1:nrow(df)) {
req <- GET(df$link[i])
# Extract content from a request
json1 = content(req)
# Convert to a data.frame
char <- rawToChar(req$content)
dfcollection <- jsonlite::fromJSON(char)
}
It may be wrapped with tryCatch or possibly from purrr. Below code uses possibly
library(purrr)
library(jsonlite)
convertToJSON <- function(x)
{
req <- GET(x)
# Extract content from a request
json1 = content(req)
# Convert to a data.frame
char <- rawToChar(req$content)
dfcollection <- jsonlite::fromJSON(char)
return(dfcollection)
}
pconvertToJSON <- possibly(convertToJSON, otherwise = NA)
out <- map(df$link, pconvertToJSON)
I have tried several technics to push json object into an array and to save in the same format of the below example, but without success.
Is anyone has a solution to do it in R ?
Thanks you
EDIT :
I found the solution.
library(jsonlite)
#Set an empty list
list1 <- vector(mode = 'list', length = 2)
# data example
json_data <- list(object1 = list(birthday = '2000-02-14', Age = '20'),
object2 = list(Candidate_Number = '1999283', first_attempt = TRUE),
object3 = list(name = 'John E.', result = list(), study_hours = 150, GPA = 3.8, exam_infos = list(cost = 800, location = 'F3C6V9', past_exams = list(list(exam_name = 'Science', score = 'passed'), list(exam_name = 'Geometric', score = 'passed')))),
object4 = list(study_manual_used = 'Physics Theory', version_found = list(Digital = '1999-01-01', Paper = '1999-01-01')))
# append data into json
for(i in length(list1)){
list1[[i]] <- json_data
}
# Write to json on his home
write(toJSON(list1, auto_unbox = TRUE, pretty = TRUE), file.path(Sys.getenv()['USERPROFILE'], 'file.json'))
To save object as JSON you can use package rjson.
library("rjson")
# example data
list1 <- list()
list1[[1]] <- c(created_at="1910-02-03", id="212", field="1")
list1[[2]] <- c(created_at="1910-01-02", id="218", field="3")
# to json
toJSON(list1)
and
write(toJSON(list1), "file.json")
If the issue is that you created data.frame and need to make it back into json. You have to make it a list by row as:
# example data
dta <- as.data.frame(rbind(c(created_at="1910-02-03", id="212", field="1"), c(created_at="1910-01-02", id="218", field="3")))
# to json
toJSON(list(dta[1,],dta[2,]))
I am trying to use specan function from warbleR package. I want to pass my own wav file as an argument to the function. I have seen only one example in docs which is not much self explanatory.
wave_file <- readWave("C:/Users/ABC/Downloads/file_example_WAV_1MG.wav", from = 1, to = Inf, units = c("seconds"), header = FALSE, toWaveMC = NULL)
head(wave_file)
mono_file <- mono(wave_file, which = c("both"))
head(mono_file)
auto_file <- autodetec(X = "C:/Users/ABC/Downloads/file_example_WAV_1MG.wav")
head(auto_file)
dataframe <- data.frame(list = c("sound.files", "selec", "start", "end"))
dataframe <- data.frame(wave_file, "abc", 1, Inf)
dataframe
# Existing Example found in R docs
#setwd('C:/Users/ABC/Downloads')
#data1 <- data(list = c("Phae.long1", "Phae.long2", "Phae.long3", "Phae.long4", "selec.table"))
#writeWave(Phae.long1,"Phae.long1.wav")
#writeWave(Phae.long2,"Phae.long2.wav")
#writeWave(Phae.long3,"Phae.long3.wav")
#writeWave(Phae.long4,"Phae.long4.wav")
#writeWave(Phae.long1,"file_example_WAV_1MG.wav")
#writeWave(Phae.long2," ")
#writeWave(Phae.long3,"1")
#writeWave(Phae.long4,"Inf")
getwd()
#file <- specan(X = selec.table, bp = c(0, 22))
#head(file)
file <- specan(X = dataframe, bp = c(0,22))
How to give my own .wav file as argument to the specan function?
Instead of passing the actual wav file to the dataframe, pass the name of that file. So your code should look like this;
dataframe <- data.frame(list = c("sound.files", "selec", "start", "end"))
dataframe <- data.frame("file_example_WAV_1MG.wav", 2, 1, 20)
names(dataframe) <- c("sound.files", "selec", "start", "end")
a <- specan(X=dataframe, bp=c(0,22))
You can then view a. The extracted features will be stored in the dataframe. Make sure your file is stored in the working directory.
I'm currently busy with some data and I need to check their validity.
Therefore, I would like to use a for-loop to go through all my data files.
In this for-loop, I would like to calculate some things (like mean, min,max...).
My code below works but produced an incorrectly written csv file. The problem occurs after the calculations (and their values) are done during csv file creation. CSV:
"c.1..1..1004.89081855716..630.174466667434..461.738905906677.." "c.1..1..950.990843858612..479.98560814955..517.955102920532.."
1 1
1 1
1004.89081855716 950.990843858612
630.174466667434 479.98560814955
461.738905906677 517.955102920532
1535.86795806885 1452.30199813843
-13.3948961645365 3.72026950120926
1259.26423788071 1159.17089223862
Approach/What I'm expecting:
So I start from some data files with eye tracking data in it.
As you can see at the beginning of the code, I try to get some values out of this eye tracking data (validity, new file with only validity == 1 data...). Once I created the filtered_data dataframe, I want to calculate some extra values out of it (mean, sd, min/max).
My plan is to create a new csv file (validity_loop.csv) in which I can find all my calculations (validity_left, validity_right,mean_eye_x, mean_eye_y, min_eye_x,max_eye_x,min_eye_y,max_eye_y). All in a row. One row for each data set (file_list[i]).
Can someone help me in how to tackle and solve this issue?
Here is my code:
set <- setwd("/Users/Sarah/Documents")
file_list <- list.files(set, pattern = ".csv", all.files = TRUE)
validity_list <- data_list <- vector("list", "length" = length(file_list))
for(i in seq_along(file_list)){
filename = file_list[i]
#read files
data_frame = read.csv(filename, sep = ",", dec = ".",
header = TRUE,
stringsAsFactors = FALSE)
#what has to be done
#validity
validity_left <- mean(is.numeric(data_frame$left_gaze_point_validity))
validity_right <-mean(is.numeric(data_frame$right_gaze_point_validity))
#Zuiver dataframe (validity ==1)
to_keep = which(data_frame$left_gaze_point_validity == 1 &
data_frame$right_gaze_point_validity==1)
filtered_data = data_frame[to_keep,]
filtered_data$left_eye_x = as.numeric(filtered_data$left_eye_x)
filtered_data$left_eye_y = as.numeric(filtered_data$left_eye_y)
filtered_data$right_eye_x = as.numeric(filtered_data$right_eye_x)
filtered_data$right_eye_y = as.numeric(filtered_data$right_eye_y)
#1 eye-data
filtered_data$eye_x <- (filtered_data$left_eye_x+filtered_data$right_eye_x)/2
filtered_data$eye_y <- (filtered_data$left_eye_y+filtered_data$right_eye_y)/2
#Pixels
filtered_data$eye_x <- (filtered_data$eye_x)*1920
filtered_data$eye_y <- (filtered_data$eye_y)*1080
#SD and Mean + min-max
mean_eye_x<- mean(filtered_data$eye_x)
mean_eye_y <- mean(filtered_data$eye_y)
sd_eye_x <- sd(filtered_data$eye_x)
sd_eye_y <- sd(filtered_data$eye_y)
min_eye_x <- min(filtered_data$eye_x)
min_eye_y <- min(filtered_data$eye_y)
max_eye_x <- max(filtered_data$eye_x)
max_eye_y <- max(filtered_data$eye_y)
#add everything to new file
validity_list[[i]] <- c(validity_left, validity_right,
mean_eye_x, mean_eye_y,
min_eye_x, min_eye_y,
max_eye_x, max_eye_y)
}
#new document
write.table(validity_list,
file = "Master T&O/Thesis /Loop/Validity/validity_loop.csv",
col.names = TRUE, row.names = FALSE)
I managed to get a new data frame in R, which contains the value of my validity_list as a matrix form.
#FOR LOOP poging 2
set <- setwd("/Users/Sarah/Documents/Master T&O/Thesis /Loop")
file_list <- list.files(set, pattern = ".csv", all.files = TRUE)
validity_list <- vector("list", "length" = length(file_list))
for(i in seq_along(file_list)){
filename = file_list[i]
#read files
data_frame = read.csv(filename, sep = ",", dec = ".", header = TRUE, stringsAsFactors = FALSE)
#what has to be done
#validity
validity_left <- mean(is.numeric(data_frame$left_gaze_point_validity))
validity_right <-mean(is.numeric(data_frame$right_gaze_point_validity))
#Zuiver dataframe (validity ==1)
to_keep = which(data_frame$left_gaze_point_validity == 1 & data_frame$right_gaze_point_validity==1)
filtered_data = data_frame[to_keep,]
filtered_data$left_eye_x = as.numeric(filtered_data$left_eye_x)
filtered_data$left_eye_y = as.numeric(filtered_data$left_eye_y)
filtered_data$right_eye_x = as.numeric(filtered_data$right_eye_x)
filtered_data$right_eye_y = as.numeric(filtered_data$right_eye_y)
#1 eye-data
filtered_data$eye_x <- (filtered_data$left_eye_x+filtered_data$right_eye_x)/2
filtered_data$eye_y <- (filtered_data$left_eye_y+filtered_data$right_eye_y)/2
#Pixels
filtered_data$eye_x <- (filtered_data$eye_x)*1920
filtered_data$eye_y <- (filtered_data$eye_y)*1080
#SD and Mean + min-max
mean_eye_x<- mean(filtered_data$eye_x)
mean_eye_y <- mean(filtered_data$eye_y)
sd_eye_x <- sd(filtered_data$eye_x)
sd_eye_y <- sd(filtered_data$eye_y)
min_eye_x <- min(filtered_data$eye_x)
min_eye_y <- min(filtered_data$eye_y)
max_eye_x <- max(filtered_data$eye_x)
max_eye_y <- max(filtered_data$eye_y)
#add everything to new file
validity_list[[i]] <- c(validity_left, validity_right,mean_eye_x, mean_eye_y, min_eye_x,max_eye_x,min_eye_y,max_eye_y)
validity_matrix <- matrix(unlist(validity_list), ncol = 8, byrow = TRUE)
}
#new document
write.table(validity_matrix, file = "/Users/Sarah/Documents/Master T&O/Thesis /Loop/Validity/validity_loop.csv", dec = ".")
The only problem I have now, is the fact that my values for the validity_list items are wrong, but that's another problem and I'm trying to fix it!
If I get it then the following line grabs all your data together:
validity_list[[i]] <- c (validity_left, validity_right,mean_eye_x,
mean_eye_y, min_eye_x,max_eye_x,min_eye_y,max_eye_y).
if it's like in python then I would have:
validity_list = (validity_left, validity_right,mean_eye_x,
mean_eye_y, min_eye_x,max_eye_x,min_eye_y,max_eye_y)
... whereas the '=' tell the interpreter that everything behind it is a tuple '(', data, ')' ...which makes it one single dataset and if I then write it... it would be end up in one column. If you do a pick using a for-loop I would get "validity_left" writing in a separate column. In your case adding this to your below code an option?
for item in validity_list:
function to process item..etc.
I am facing difficulties after running the code and trying to export the dataset to a spreadsheet or txt.file.
I am newbie to R, so maybe this question is trivial.
After running the following code:
eia_series <- function(api_key, series_id, start = NULL, end = NULL, num = NULL, tidy_data = "no", only_data = FALSE){
# max 100 series
# test if num is not null and either start or end is nut null. Not allowed
# api_key test for character.
# series_id test for character.
# if start/end not null, then check if format matches series id date format
# parse date and numerical data
# parse url
series_url <- httr::parse_url("http://api.eia.gov/series/")
series_url$query$series_id <- paste(series_id, collapse = ";")
series_url$query$api_key <- api_key
series_url$query$start <- start
series_url$query$end <- end
series_url$query$num <- num
# get data
series_data <- httr::GET(url = series_url)
series_data <- httr::content(series_data, as = "text")
series_data <- jsonlite::fromJSON(series_data)
# Move data from data.frame with nested list and NULL excisting
series_data$data <- series_data$series$data
series_data$series$data <- NULL
# parse data
series_data$data <- lapply(X = series_data$data,
FUN = function(x) data.frame(date = x[, 1],
value = as.numeric(x[, 2]),
stringsAsFactors = FALSE))
# add names to the list with data
names(series_data$data) <- series_data$data
# parse dates
series_data$data <- eia_date_parse(series_list = series_data$data, format_character = series_data$series$f)
# tidy up data
if(tidy_data == "tidy_long"){
series_data$data <- lapply(seq_along(series_data$data),
function(x) {cbind(series_data$data[[x]],
series_time_frame = series_data$series$f[x],
series_name = series_data$series$series_id[x],
stringsAsFactors = FALSE)})
series_data$data <- do.call(rbind, series_data$data)
}
# only data
if(only_data){
series_data <- series_data$data
}
return(series_data)
}
After running the function
eia_series(api_key = "XXX",series_id = c("PET.MCRFPOK1.M", "PET.MCRFPOK2.M"))
I tried to "transfer" the data in order to export it but got the following error:
No encoding supplied: defaulting to UTF-8.
I don't understand why. Could you help me out?
That doesn't look like an error, rather a statement. Probably coming from httr::content(series_data, as = "text"). Look in https://cran.r-project.org/web/packages/httr/vignettes/quickstart.html in The body section. It shouldn't be a problem, as long as your data returns what you expect. Otherwise you can try different encoding or there is a bug elsewhere.
Try:
series_data <- httr::content(series_data, as = "text", encoding = "UTF-8")