How can I make time series plot?

Question

I created a dataset with these variables. But Date variable should be the first 128 day of the year. My problems are:

1. I could not convert the Date variable.
2. How can I plot wheat, hazelnut and corn in time?
3. How can I make subplot by repeating the previous plot with only two months data?

Can you help me please.

a <- 1
b <- 3
c <- 0

Date <- c(1:128)
Wheat <- rnorm(128, mean = a, sd = b)
Hazelnut <- runif(128, a ,b)
Corn <- rnorm(128, mean = c, sd = b)

df <- as.data.frame(cbind(Date, Wheat, Hazelnut, Corn))
df$Date <- as.Date(df$Date)

Answer 1

How about this:

library(ggplot2)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(lubridate)
#> 
#> Attaching package: 'lubridate'
#> The following objects are masked from 'package:base':
#> 
#>     date, intersect, setdiff, union
library(tidyr)
a <- 1
b <- 3
c <- 0
Date <- seq(ymd("2022-01-01"), ymd("2022-01-01")+127, by=1)
Wheat <- rnorm(128, mean = a, sd = b)
Hazelnut <- runif(128, a ,b)
Corn <- rnorm(128, mean = c, sd = b)

df <- data.frame(Date=Date, 
                    Wheat=Wheat, 
                    Hazelnut=Hazelnut, 
                    Corn=Corn)

df <- df %>% 
  pivot_longer(c("Wheat", "Hazelnut", "Corn"), 
               names_to="crop",
               values_to="vals")


ggplot(df, aes(x=Date, y=vals)) + 
  geom_line() + 
  facet_wrap(~crop, ncol=1) + 
  theme_classic()

df %>% filter(Date <= ymd("2022-02-28")) %>% 
ggplot(aes(x=Date, y=vals)) + 
  geom_line() + 
  facet_wrap(~crop, ncol=1) + 
  theme_classic()

^{Created on 2022-04-19 by the reprex package (v2.0.1)}

To make them in a single plot, use:

ggplot(df, aes(x=Date, y=vals, color=crop)) + 
  geom_line() + 
  theme_classic()

Answer 2

First, better use data.frame() to create your data frame to not unnecessarily pollute your workspace with variables you only need once.

For the date you want an origin= which starts at the day before the time series start in this case.

a <- 1; b <- 3; c <- 0; t1 <- 128

set.seed(42)  ## for sake of reproducibility
              ## always use seed when stochastic processes are involved
dat <- data.frame(Date=as.Date(c(1:t1), origin='2021-12-31'),
                  Wheat=rnorm(t1, mean=a, sd=b),
                  Hazelnut=runif(t1, a, b),
                  Corn=rnorm(t1, mean=c, sd=b))

Looks like this.

head(dat, 3)
#         Date      Wheat Hazelnut      Corn
# 1 2022-01-01 -0.4537862 1.780596 -3.386932
# 2 2022-01-02  1.5673864 1.140588 -0.263794
# 3 2022-01-03  1.1530190 2.415013  6.725711

Then you may use matplot without the date column, which we need in second step to create axis and mtext. Finally we can add a nice legend.

matplot(dat[-1], type='l', ylab='foo', col=2:4, lty=1, xaxt='n', main='This year')
subs <- !duplicated(substr(dat$Date, 6, 7))
axis(1, seq_along(dat$Date)[subs], labels=F)
mtext(months(dat$Date)[subs], 1, 1, at=seq_along(dat$Date)[subs], cex=.8)
legend('top', legend=names(dat)[-1], lty=1, col=2:4, horiz=TRUE, bty='n', cex=.8)

To create the plot only for two months, just subset the data in the code above, e.g.

matplot(dat[dat$Date < as.Date('2022-03-01'), -1], ...)

In case you want to create an actual time-series object, use ts,

(df_ts <- ts(with(df, data.frame(Wheat, Hazelnut, Corn)), frequency=365,
             start=2022))
# Time Series:
# Start = c(2022, 1) 
# End = c(2022, 128) 
# Frequency = 365 
# Wheat Hazelnut        Corn
# 2022.000  5.11287534 1.220670  0.75783511
# 2022.003 -0.69409451 2.079597 -3.88200740
# 2022.005  2.08938523 2.142468 -2.87751133
# 2022.008  2.89858781 2.237903  3.25732456
# [...]
# 2022.340  0.99453216 2.162396 -2.35466343
# 2022.342 -0.28477664 1.940185  0.49024896
# 2022.345 -0.84101482 1.730028 -3.71014271
# 2022.348 -5.07403354 1.560249  3.13762133

where

class(df_ts)
# [1] "mts"    "ts"     "matrix"

and plot it.

plot(df_ts)