I am trying to plot WaterLevel vs Datetime (I formatted the datetime), however I get an error like
Error in seq.int(0, to0 - from, by) : 'to' must be a finite number
library(ggplot2)
library(scales)
library(shiny)
library(stringi)
file = "http://dd.weather.gc.ca/hydrometric/csv/SK/hourly/SK_hourly_hydrometric.csv"
skdat <- read.csv(file, head=T, sep=",", dec=".", stringsAsFactors = F)
colnames(skdat) <- c("ID", "Date", "WaterLevel", "Grade1", "Symbol1",
"QAQC-1", "DischargeDebit", "Grade2", "Symbol2",
"QAQC-2")
subds <- subset(skdat, ID=='05EF001')
subds$datetime <- as.POSIXct(subds$Date, format = "%Y-%m-%dT%H%m%S-06:00")
p2 <- ggplot(subds, aes(x = datetime, y = WaterLevel)) + geom_line()
p2
I have tried different formats and I know the data is good as it plots in a simple plot as well.
Use -
subds$datetime <- as.POSIXct(subds$Date, format = "%Y-%m-%dT%H:%M:%OS")#"%Y-%m-%dT%H:%m:%S-06:00")
This would cast your date properly to give the datetime column and not give NAs.
After this the plot will get generated -
Related
I have sample file with csv that describe some stock exchange indexes. I have already managed to:
Create for loop statement to tidy the data in a way that I have those data as DFs in a list.
In each index I calculated using loop OLSSlope, Log values, Percent Change, STDSlope etc.
Create XTS objects that are stored inside list.
I want to write such for loop/ lapply code that will take each xts object inside list, create plot using (dygraph) library and then save this graph in an output file. So that the goal is to have graph for each index that is inside this list of xts objects. I don't have problem with creating one graph for one object but to make it universal inside loop. Code for graph that I want is:
wig20tr_d_xts <- xts(x = wig20tr_d$Zamkniecie,
order.by = wig20tr_d$Date)
wig20tr_d_ols <- xts(x = wig20tr_d$OLSSlope,
order.by = wig20tr_d$Date)
wig20tr_d_stdup <- xts(x = wig20tr_d$OneSTDup,
order.by = wig20tr_d$Date)
wig20tr_d_stduptwo <- xts(x = wig20tr_d$TwoSTDup,
order.by = wig20tr_d$Date)
wig20tr_d_stddown <- xts(x = wig20tr_d$OneSTDdown,
order.by = wig20tr_d$Date)
wig20tr_d_stddowntwo <- xts(x = wig20tr_d$TwoSTDdown,
order.by = wig20tr_d$Date)
wig20 <- cbind(wig20tr_d_xts, wig20tr_d_ols, wig20tr_d_stdup, wig20tr_d_stduptwo, wig20tr_d_stddown, wig20tr_d_stddowntwo)
wig20_graph <- dygraph(wig20, main = "WIG 20 TR", ylab = "Total return in zł") %>%
dySeries("wig20tr_d_xts", color = "black") %>%
dySeries("wig20tr_d_ols", strokeWidth = 2, strokePattern = "dashed", color = "blue") %>%
dySeries("wig20tr_d_stdup", color = "green") %>%
dySeries("wig20tr_d_stduptwo", color = "green") %>%
dySeries("wig20tr_d_stddown", color = "red") %>%
dySeries("wig20tr_d_stddowntwo", color = "red") %>%
dyRangeSelector() %>%
dyUnzoom() %>%
dyOptions(axisLineColor = "navy",
gridLineColor = "lightblue") %>%
dyCrosshair(direction = "vertical")
wig20_graph
htmltools::save_html(wig20_graph, file = "C:/DATA_output/wig20_graph.html")
As you can see I use this addition to the graph:
dyCrosshair <- function(dygraph,
direction = c("both", "horizontal", "vertical")) {
dyPlugin(
dygraph = dygraph,
name = "Crosshair",
path = system.file("plugins/crosshair.js",
package = "dygraphs"),
options = list(direction = match.arg(direction))
)
}
Loop to create list of xts objects is like this:
for(i in 1:length(xts_list)){
df <- xts_list[i]
df <- as.data.frame(df)
colnames(df) <- c("Date", "Zamkniecie", "Trend", "OLSSlope", "LogClose", "LogCloseOLS", "LogCloseOLSSlope", "PercentChange", "LogChange", "OneSTDup", "OneSTDdown", "TwoSTDup", "TwoSTDdown")
time_series <- xts(x = df$Zamkniecie,
order.by = df$Date)
ols <- xts(x = df$OLSSlope,
order.by = df$Date)
stdup <- xts(x = df$OneSTDup,
order.by = df$Date)
stduptwo <- xts(x = df$TwoSTDup,
order.by = df$Date)
stddown <- xts(x = df$OneSTDdown,
order.by = df$Date)
stddowntwo <- xts(x = df$TwoSTDdown,
order.by = df$Date)
time_series_full <- cbind(time_series, ols, stdup, stduptwo, stddown, stddowntwo)
xts_list[[i]] <- time_series_full
print(i)
}
I have problem with adding part with graph inside this last for loop. So that the HTML graph would be named after the index. In this example the index is wig20tr_d
I need to highlight some dates ranges in my time series chart, but I can´t go ahead.
The dataset used is following:
library(dplyr)
library(xts)
library(zoo)
df <- read.csv("https://github.com/rhozon/datasets/raw/master/dataset_1a.csv", header = TRUE, sep =",") %>%
mutate(
dates = as.Date(dates)
) %>%
filter(
dates >= "2019-01-01"
) %>%
glimpse()
df_xts <- xts(df[,-1, drop = FALSE], order.by = df[,1]) %>% as.xts()
class(df_xts)
head(df_xts)
Then I tryed the following PerfomanceAnalytics commands:
library(PerformanceAnalytics)
# Create period to hold the 3 months of 2020
period <- c("2020-01/2020-03")
# Highlight the first three months of 2020
chart.TimeSeries(df$prices_usa, period.areas = period, period.color = "lightgrey")
with no success...
Error in try.xts(x, error = "'x' needs to be timeBased or xtsible") :
'x' needs to be timeBased or xtsible
By using the dygraphs package...
library(dygraphs)
dygraph( df$prices_usa ) %>%
dyShading(from = "2020-06-30", to = "2020-09-01") %>%
dyAnnotation("2020-08-01", text = "X", tooltip = "date range") %>%
dyAxis("x", drawGrid = TRUE) %>%
dyEvent("2020-06-30", "Jul 2020", labelLoc = "bottom") %>%
dyEvent("2020-09-01", "Sep 2020", labelLoc = "bottom") %>%
dyOptions(drawPoints = FALSE, pointSize = 2) #%>%
And again I found another issue:
Error in dygraph(df$prices_usa) : Unsupported type passed to argument 'data'.
I didn´t tryed with the ggplot2 package because I need to use it with interaticvity.
Could someone recommend me a solution to these issues or something that is simpler to do (even with ggplot2+plotly) that can be useful for me to demarcate or highlight some ranges of dates/periods in my time series graphs?
Using the reproducible xts object in the Note at the end use plot and xblocks. To specify a different color use something like adjustcolor("blue", 0.2) in place of grey(...). For many other approaches google R shading recessions
library(xts)
plot(as.zoo(aapl))
xblocks(aapl, ifelse(time(aapl) %in% time(aapl[period]), grey(.2, .2), NA))
Note
library(quantmod)
getSymbols("AAPL")
period <- "2020-01/2020-03"
aapl <- Cl(AAPL)
I want to plot the stock price time series for several stocks on individual plots. I've used plotfun but am unable to change to x-axis from Index to Date. I was wondering if I've missed something or is there better way to achieve this. Below is the code that I've created thus far and one of the two plotfun plots.
enter image description hereThanks for your time and consideration in advance.
library("quantmod")
library("ggplot2")
library("BatchGetSymbols")
library("magrittr")
library("broom")
library("dplyr")
library("zoo")
library("xts")
library("tidyverse")
library("tidyquant")
library("TSstudio")
library("rlang")
GetMySymbols <- function(x) {
getSymbols(x,
src ="yahoo",
from = "2010-07-01",
to = "2016-06-30",
auto.assign = FALSE)}
tickers <- c('TLS.AX','WOW.AX')
prices_Close <- map(tickers, GetMySymbols) %>% map(Cl) %>% reduce(merge.xts)
names(prices_Close) <- tickers
##plot.zoo(prices_Close, plot.type = 'multiple')
##plot.xts(prices_Close)
##plot.ts(df)
##df <- fortify(prices_Close)
mydf <- as.Data.frame(prices_Close)
plotfun <- function(col)
plot(mydf[,col], ylab = names(mydf[col]), type = "l")
par(ask = FALSE)
sapply(seq(1, length(mydf), 1), plotfun)
I've found the solution to the problem above:
for (i in 2:ncol(df)){
print(ggplot(df, aes_string(x = "Index", y= df[,i])) + geom_line() + xlab("Date"))
}
I have two data frame as below:
PickUP <- data.frame(pickuplong = c(-73.93909 ,-73.94189 ,-73.93754,-73.91638,-73.92792 ,-73.88634), pickuplat =c(40.84408,40.83841,40.85311,40.84966,40.86284,40.85628))
Dropoff <- data.frame(pickuplong = c(-73.93351 ,-73.93909 ,-73.93909 ,-73.80747,-73.95722,-73.91880), pickuplat =c(40.76621,40.84408,40.85311,40.69951,40.68877,40.75917), Droplong =c(-73.91300,-73.96259 ,-73.94870,-73.93860,-73.93633, -73.90690), Droplat =c(40.77777,40.77488 ,40.78493,40.84463,40.75977,40.77013))
I try to find the pickup coordinations (longtitude and latitude) in the pickup data frame which are repeated in dropoff dataframe. I have the below code but I got the error on this:
library(sp)
library(rgdal)
library(leaflet)
library(mapview)
library(dplyr)
a <- semi_join(Dropoff , PickUP , by = c("pickuplong","pickuplat"))
a$ID <- 1:nrow(a)
Dropoff_p <- a[, c("ID", "Pickup_longitude", "Pickup_latitude")]
Dropoff_d <- a[, c("ID", "Dropoff_longitude", "Dropoff_latitude")]
coordinates(Dropoff_p) <- ~Pickup_longitude + Pickup_latitude
coordinates(Dropoff_d) <- ~Dropoff_longitude + Dropoff_latitude
proj4string(Dropoff_p) <- CRS("+init=epsg:4326")
proj4string(Dropoff_d) <- CRS("+init=epsg:4326")
map_p <- mapview(Dropoff_p, color = "red")
map_d <- mapview(Dropoff_d, color = "blue")
map_p + map_d
My error is:
Error in $<-.data.frame (tmp, "ID", value = c(1L, 0L)) :
replacement has 2 rows, data has 0 Error during wrapup: cannot open the
connection
When subsetting the data frame, you have to use the same column names. I changed the column name in the Dropoff_p, Dropoff_d, coordinates(Dropoff_p), and proj4string(Dropoff_d), and then your script works.
In addition, the mapview package just has a new update. If you want, you can update your mapview to version 2.0.1. You can also add col.regions = "red" and col.regions = "blue" because it seems like under the new version the color argument will only change the outline of a point. To change the fill color, use col.regions.
library(sp)
library(rgdal)
library(leaflet)
library(mapview)
library(dplyr)
a <- semi_join(Dropoff , PickUP , by = c("pickuplong","pickuplat"))
a$ID <- 1:nrow(a)
Dropoff_p <- a[, c("ID", "pickuplong", "pickuplat")]
Dropoff_d <- a[, c("ID", "Droplong", "Droplat")]
coordinates(Dropoff_p) <- ~pickuplong + pickuplat
coordinates(Dropoff_d) <- ~Droplong + Droplat
proj4string(Dropoff_p) <- CRS("+init=epsg:4326")
proj4string(Dropoff_d) <- CRS("+init=epsg:4326")
map_p <- mapview(Dropoff_p, color = "red", col.regions = "red")
map_d <- mapview(Dropoff_d, color = "blue", col.regions = "blue")
map_p + map_d
This is a beginner question. I have spent most of the day trying to work out how to facet my data, but all of the examples of faceting that I have come across seem unsuited to my dataset.
Here are the first five rows from my data:
Date Germany.Yield Italy.Yield Greece.Yield Italy_v_Germany.Spread Greece_v_Germany.Spread
2020-04-19 -0.472 1.820 2.287 2.292 2.759
2020-04-12 -0.472 1.790 2.112 2.262 2.584
2020-04-05 -0.345 1.599 1.829 1.944 2.174
2020-03-29 -0.441 1.542 1.972 1.983 2.413
2020-03-22 -0.475 1.334 1.585 1.809 2.060
I simply want to create two line charts. On both charts the x-axis will be the date. On the first chart, the y-axis should be Italy_v_Germany.Spread and on the second, the y-axis should be Greece_v_Germany.Spread.
The first chart looks like this:
So I want the two charts to appear alongside each other, like this:
The one on the left should be Italy_v_Germany.Spread, and the one on the right should be Greece_v_Germany.Spread.
I really have no idea where to start with this. Hoping that someone can point me in the right direction.
In the interest I making the example reproducible, I will share a link to the CSV files which I'm using: https://1drv.ms/u/s!AvGKDeEV3LOsmmlHkzO6YVQTRiOX?e=mukBVy. Unforunately these files convert into excel format when shared via this link, so you may have to export the files to CSVs so that the code works.
Here is the code that I have so far:
library(ggplot2)
library(scales)
library(extrafont)
library(dplyr)
library(tidyr)
work_dir <- "D:\\OneDrive\\Documents\\Economic Data\\Historical Yields\\Eurozone"
setwd(work_dir)
# Germany
#---------------------------------------
germany_yields <- read.csv(file = "Germany 10-Year Yield Weekly (2007-2020).csv", stringsAsFactors = F)
germany_yields <- germany_yields[, -(3:6)]
colnames(germany_yields)[1] <- "Date"
colnames(germany_yields)[2] <- "Germany.Yield"
#---------------------------------------
# Italy
#---------------------------------------
italy_yields <- read.csv(file = "Italy 10-Year Yield Weekly (2007-2020).csv", stringsAsFactors = F)
italy_yields <- italy_yields[, -(3:6)]
colnames(italy_yields)[1] <- "Date"
colnames(italy_yields)[2] <- "Italy.Yield"
#---------------------------------------
# Greece
#---------------------------------------
greece_yields <- read.csv(file = "Greece 10-Year Yield Weekly (2007-2020).csv", stringsAsFactors = F)
greece_yields <- greece_yields[, -(3:6)]
colnames(greece_yields)[1] <- "Date"
colnames(greece_yields)[2] <- "Greece.Yield"
#---------------------------------------
# Join data
#---------------------------------------
combined <- merge(merge(germany_yields, italy_yields, by = "Date", sort = F),
greece_yields, by = "Date", sort = F)
combined <- na.omit(combined)
combined$Date <- as.Date(combined$Date,format = "%B %d, %Y")
combined["Italy_v_Germany.Spread"] <- combined$Italy.Yield - combined$Germany.Yield
combined["Greece_v_Germany.Spread"] <- combined$Greece.Yield - combined$Germany.Yield
#--------------------------------------------------------------------
fl_dates <- c(tail(combined$Date, n=1), head(combined$Date, n=1))
ggplot(data=combined, aes(x = Date, y = Italy_v_Germany.Spread)) + geom_line() +
scale_x_date(limits = fl_dates,
breaks = seq(as.Date("2008-01-01"), as.Date("2020-01-01"), by="2 years"),
expand = c(0, 0),
date_labels = "%Y")
You need to get your data into a long format, for example, by using pivot_wider. Then it should work.
library(dplyr)
library(tidyr)
library(ggplot2)
data <- tribble(~Date, ~Germany.Yield, ~Italy.Yield, ~Greece.Yield, ~Italy_v_Germany.Spread, ~Greece_v_Germany.Spread,
"2020-04-19", -0.472, 1.820, 2.287, 2.292, 2.759,
"2020-04-19", -0.472, 1.820, 2.287, 2.292, 2.759,
"2020-04-12", -0.472, 1.790, 2.112, 2.262, 2.584,
"2020-04-05", -0.345, 1.599, 1.829, 1.944, 2.174,
"2020-03-29", -0.441, 1.542, 1.972, 1.983, 2.413,
"2020-03-22", -0.475, 1.334, 1.585, 1.809, 2.060
)
data %>%
mutate(Date = as.Date(Date)) %>%
pivot_longer(
cols = ends_with("Spread"),
names_to = "country",
values_to = "Spread_v_Germany",
values_drop_na = TRUE
) %>%
ggplot(., aes(x = Date, y = Spread_v_Germany, group = 1)) +
geom_line() +
facet_wrap(. ~ country)