0

我试图获得最低需求<400的所有每日需求曲线。数据包括整整一年。我希望曲线按月分组。以下是我的代码。

library(lubridate)
library(ggplot2)
library(dplyr)
library(data.table)
library(viridis)


sa <- read.csv("data/SA_demand_data_2020.csv")

sa$SETTLEMENTDATE <- as.POSIXct(strptime(sa$SETTLEMENTDATE, "%d/%m/%Y %H:%M"), 
                               tz="Australia/Queensland")




 ts <- sa$SETTLEMENTDATE
# Group sa by date
sa1 <- group_by(sa, date(ts))

#Create a data table with minimum demand for each day (sa2)
sa2=data.table(setDT(sa1)[, .SD[which.min(TOTALDEMAND)], by=date(ts)])

# filter and get only the records having min demand<500
MinDem <- filter(sa2, TOTALDEMAND<400)

#Create a column named "date" in dataframe "sa" having ony date field
sa$date <- date(sa$SETTLEMENTDATE)

# Getting a dataframe/data table which included a coulmn with all demand data for only the days with min demand<500
comb <- merge(MinDem, sa, by.x= "date", by.y="date", all.x=TRUE )


#plot daily demand profile for days with min demand <500
ts <- comb$SETTLEMENTDATE.y
  ps <- comb$TOTALDEMAND.y
  hs <- hour(ts) + minute(ts)/60
  ds <-date(ts)
  ms <- month(ts)
  data <- data.frame(x=hs, y=ps, z=ds, m=ms)
  p <- ggplot(data, aes(x=x, y=y, group=z, colour=m)) +
       geom_line( aes(colour=m), size=0.1)+
    geom_point(aes(colour=m), size=0.2)+    
    scale_colour_viridis_c(option="D")+
    labs(x="Hour", y="Power (MW)") +
    scale_x_continuous(breaks = c(0, 3, 6, 9, 12, 15, 18, 21, 24)) +
   scale_y_continuous(limits=c(0, 1600), breaks=seq(0, 1600, by= 100))+
    theme(legend.position="right")
  print(p)

我获得的图没有显示月份名称。相反，它显示一个编号的比例。我想在规模上可视化月份

谢谢

“sa”数据框的第一行如下所示。

structure(list(Source.Name = c("PRICE_AND_DEMAND_202001_SA1.csv", 
"PRICE_AND_DEMAND_202001_SA1.csv", "PRICE_AND_DEMAND_202001_SA1.csv", 
"PRICE_AND_DEMAND_202001_SA1.csv", "PRICE_AND_DEMAND_202001_SA1.csv", 
"PRICE_AND_DEMAND_202001_SA1.csv", "PRICE_AND_DEMAND_202001_SA1.csv", 
"PRICE_AND_DEMAND_202001_SA1.csv", "PRICE_AND_DEMAND_202001_SA1.csv", 
"PRICE_AND_DEMAND_202001_SA1.csv", "PRICE_AND_DEMAND_202001_SA1.csv", 
"PRICE_AND_DEMAND_202001_SA1.csv", "PRICE_AND_DEMAND_202001_SA1.csv", 
"PRICE_AND_DEMAND_202001_SA1.csv", "PRICE_AND_DEMAND_202001_SA1.csv", 
"PRICE_AND_DEMAND_202001_SA1.csv", "PRICE_AND_DEMAND_202001_SA1.csv", 
"PRICE_AND_DEMAND_202001_SA1.csv", "PRICE_AND_DEMAND_202001_SA1.csv", 
"PRICE_AND_DEMAND_202001_SA1.csv"), REGION = c("SA1", "SA1", 
"SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", 
"SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1"
), SETTLEMENTDATE = structure(c(1577802600, 1577804400, 1577806200, 
1577808000, 1577809800, 1577811600, 1577813400, 1577815200, 1577817000, 
1577818800, 1577820600, 1577822400, 1577824200, 1577826000, 1577827800, 
1577829600, 1577831400, 1577833200, 1577835000, 1577836800), class = c("POSIXct", 
"POSIXt"), tzone = "Australia/Queensland"), TOTALDEMAND = c(1419.45, 
1361.94, 1256.3, 1202.3, 1170.07, 1151.99, 1133.61, 1125.55, 
1118.56, 1120.8, 1124.89, 1119.88, 1089.95, 1049.18, 991.23, 
927.15, 848.82, 761.16, 686.57, 623.05), RRP = c(68.33, 68.33, 
68.76, 68.42, 68.25, 68, 68, 65.65, 60.66, 57.42, 59.95, 56.87, 
45.85, 36.27, 42.56, 38.79, 31.55, 6.4, 21.7, 11.32), PERIODTYPE = c("TRADE", 
"TRADE", "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", 
"TRADE", "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", 
"TRADE", "TRADE", "TRADE", "TRADE", "TRADE"), date = structure(c(18262, 
18262, 18262, 18262, 18262, 18262, 18262, 18262, 18262, 18262, 
18262, 18262, 18262, 18262, 18262, 18262, 18262, 18262, 18262, 
18262), class = "Date")), row.names = c(NA, 20L), class = "data.frame")

“梳状”数据集的第一行如下所示。

structure(list(date = structure(c(18330, 18330, 18330, 18330, 
18330, 18330, 18330, 18330, 18330, 18330, 18330, 18330, 18330, 
18330, 18330, 18330, 18330, 18330, 18330, 18330), class = "Date"), 
    Source.Name.x = c("PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv"
    ), REGION.x = c("SA1", "SA1", "SA1", "SA1", "SA1", "SA1", 
    "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", 
    "SA1", "SA1", "SA1", "SA1", "SA1"), SETTLEMENTDATE.x = structure(c(1583726400, 
    1583726400, 1583726400, 1583726400, 1583726400, 1583726400, 
    1583726400, 1583726400, 1583726400, 1583726400, 1583726400, 
    1583726400, 1583726400, 1583726400, 1583726400, 1583726400, 
    1583726400, 1583726400, 1583726400, 1583726400), tzone = "Australia/Queensland", class = c("POSIXct", 
    "POSIXt")), TOTALDEMAND.x = c(388.59, 388.59, 388.59, 388.59, 
    388.59, 388.59, 388.59, 388.59, 388.59, 388.59, 388.59, 388.59, 
    388.59, 388.59, 388.59, 388.59, 388.59, 388.59, 388.59, 388.59
    ), RRP.x = c(0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 
    0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 
    0.05, 0.05), PERIODTYPE.x = c("TRADE", "TRADE", "TRADE", 
    "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", 
    "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", 
    "TRADE", "TRADE", "TRADE"), `date(ts)` = structure(c(18330, 
    18330, 18330, 18330, 18330, 18330, 18330, 18330, 18330, 18330, 
    18330, 18330, 18330, 18330, 18330, 18330, 18330, 18330, 18330, 
    18330), class = "Date"), Source.Name.y = c("PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv", "PRICE_AND_DEMAND_202003_SA1.csv", 
    "PRICE_AND_DEMAND_202003_SA1.csv"), REGION.y = c("SA1", "SA1", 
    "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", 
    "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1", "SA1"
    ), SETTLEMENTDATE.y = structure(c(1583676000, 1583677800, 
    1583679600, 1583681400, 1583683200, 1583685000, 1583686800, 
    1583688600, 1583690400, 1583692200, 1583694000, 1583695800, 
    1583697600, 1583699400, 1583701200, 1583703000, 1583704800, 
    1583706600, 1583708400, 1583710200), class = c("POSIXct", 
    "POSIXt"), tzone = "Australia/Queensland"), TOTALDEMAND.y = c(1249.56, 
    1251.44, 1212.15, 1123.59, 1086.58, 1046.36, 1029.07, 1018.48, 
    1020.76, 1016.86, 1041.95, 1035.11, 1062.83, 1077.97, 1085.84, 
    1078.29, 1003.12, 918.83, 841.33, 743.89), RRP.y = c(20.97, 
    7.01, 9.78, 6.23, 0.25, 0, 1.05, 0, 4.3, 10.76, 15.85, 32.4, 
    26.05, 47.78, 63.66, 40.15, 35.51, 32.26, 13.07, 9.45), PERIODTYPE.y = c("TRADE", 
    "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", 
    "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", "TRADE", 
    "TRADE", "TRADE", "TRADE", "TRADE", "TRADE")), class = c("data.table", 
"data.frame"), row.names = c(NA, -20L), .internal.selfref = <pointer: 0x000001fc25e71ef0>, sorted = "date")
4

1 回答 1

0

实现所需结果的一种选择是设置色标标签，通过该标签labels = ~ month.name[.x]将月份从数字转换为名称：

library(ggplot2)
library(viridis)
#> Loading required package: viridisLite

ggplot(data, aes(x = x, y = y, group = z, colour = m)) +
  geom_line(aes(colour = m), size = 0.1) +
  geom_point(aes(colour = m), size = 0.2) +
  scale_colour_viridis_c(option = "D", labels = ~month.name[.x]) +
  labs(x = "Hour", y = "Power (MW)") +
  scale_x_continuous(breaks = c(0, 3, 6, 9, 12, 15, 18, 21, 24)) +
  scale_y_continuous(limits = c(0, 1600), breaks = seq(0, 1600, by = 100)) +
  theme(legend.position = "right")

数据

data <- structure(list(x = c(
  0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5,
  5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5
), y = c(
  1249.56, 1251.44,
  1212.15, 1123.59, 1086.58, 1046.36, 1029.07, 1018.48, 1020.76,
  1016.86, 1041.95, 1035.11, 1062.83, 1077.97, 1085.84, 1078.29,
  1003.12, 918.83, 841.33, 743.89
), z = structure(c(
  18330, 18330,
  18330, 18330, 18330, 18330, 18330, 18330, 18330, 18330, 18330,
  18330, 18330, 18330, 18330, 18330, 18330, 18330, 18330, 18330
), class = "Date"), m = c(
  3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
  3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L
)), class = "data.frame", row.names = c(
  NA,
  -20L
))
于 2021-11-05T09:34:12.893 回答