I have this data.table which has 3 columns. the first one is about MonthlySalesMean , the second is the year and then the month.
> data[,MonthlySalesMean:=mean(StoreMean),by=c("DateMonth","DateYear")][,c("MonthlySalesMean","DateYear","DateMonth")]
MonthlySalesMean DateYear DateMonth
1: 6839.340 2015 7
2: 6839.340 2015 7
3: 6839.340 2015 7
4: 6839.340 2015 7
5: 6839.340 2015 7
---
641938: 6852.171 2013 1
641939: 6852.171 2013 1
641940: 6852.171 2013 1
641941: 6852.171 2013 1
641942: 6852.171 2013 1
I need to plot a graph of three lines because I have 3 years:
> unique(data[,DateYear])
[1] 2015 2014 2013
>
And For each year or each line, it should be plotted across all months of a year the MonthlySalesMean values. In another word it should be like this graph:
How can I do this, please?
thank you for advance!
Without a reproducible example, I can't test with your data, but here's the idea. You plot a path, with aesthetics of sales (y) against month (x) grouped by year (color)
library(tidyverse)
example_data <- tibble(
MonthlySalesMean = rnorm(36, 100, 20),
DateYear = c(rep(2013, 12), rep(2014, 12), rep(2015, 12)),
DateMonth = c(1:12, 1:12, 1:12)
)
ggplot(example_data, aes(x = DateMonth, y = MonthlySalesMean, color = as.factor(DateYear))) +
geom_path() +
geom_point(size = 2) +
geom_text(aes(label = DateYear),
data = filter(example_data, DateMonth == 1),
nudge_x = -0.5) + # plot year numbers
scale_x_continuous(breaks = 1:12, labels = month.abb) +
scale_colour_manual(guide = FALSE, # hides legend
values = c("red", "green", "blue")) + # custom colors
expand_limits(x = 0.5) + # adds a space before January
labs(x = "Month", y = "Sales") +
theme_bw() +
theme(panel.grid = element_blank()) # removes gridlines
Related
I am trying to graph two different datasets, reconstructed temperatures (10-16) and charcoal data (0-140), with two different time series values, using ggplot. Is this possible?
I used this code (see below) but unfortunately it produced a plot (see below) that limits the variability of the temperature reconstruction. Is there a way to adjust the y axis so we can see more variability in the temperature record?
Thank you very much for your support.
R code
df <- data.frame(Charfiretempdata$AGETEMPS, Charfiretempdata$FIREAGE, Charfiretempdata$Comp2TEMPS,Charfiretempdata$Char.Acc.Rate..Char...cm.2.yr.1.)
ggplot(df) +
geom_col(mapping = aes(x = Charfiretempdata$FIREAGE,
y = Charfiretempdata$Char.Acc.Rate..Char...cm.2.yr.1. * 16/150), size = 2, color = "darkblue",
fill = "white") +
geom_line(mapping = aes(x = Charfiretempdata$AGETEMPS, y = Charfiretempdata$Comp2TEMPS)) +
geom_point(mapping = aes(x = Charfiretempdata$AGETEMPS, y = Charfiretempdata$Comp2TEMPS), size
= 3, shape = 21, fill = "white")+
scale_y_continuous(
name = expression("Temperature ("~degree~"C)"),
sec.axis = sec_axis(~ . * 150/16 , name = "Charcoal (mm)"))
R plot
I create a random sample data that would share similar characteristics to your data.
library(dplyr)
library(ggplot2)
set.seed(282930)
df <- tibble(x_axis = c(1400, 1500, 1600, 2000, 2001, 2002, 2003, 2004, 2005, 2006,
2007, 2008, 2009, 2010, 2011, 2012, 2013, 2015, 2016, 2017),
y_axis_1 = runif(20, min = 10, max = 16),
y_axis_2 = runif(20, min = 0, max = 150))
Here is the df
> df
# A tibble: 20 x 3
x_axis y_axis_1 y_axis_2
<dbl> <dbl> <dbl>
1 1400 15.7 5.28
2 1500 11.8 141.
3 1600 14.5 149.
4 2000 11.6 121.
5 2001 15.6 37.3
6 2002 15.0 72.5
7 2003 10.7 130.
8 2004 15.4 84.7
9 2005 11.5 118.
10 2006 10.4 17.4
11 2007 11.3 124.
12 2008 13.6 22.6
13 2009 13.0 14.5
14 2010 15.9 142.
15 2011 12.3 103.
16 2012 10.3 131.
17 2013 12.6 93.6
18 2015 14.6 12.4
19 2016 11.4 27.9
20 2017 15.3 116.
Here is the ggplot similar to your but with the different Axis adjustment
ggplot(df,
# as they sharing same X-axis you can define share variable aes in the
# main call of ggplot
aes(x = x_axis)) +
geom_col(mapping =
# added 10 to 2nd axis value as will scale from 10 instead of 0
aes(y = (y_axis_2 * 10 / 150) + 10),
# the size here is size of the border - and due to the nature of
# your data, the col suppose to be very thin to match with that one
# tick on x-axis - so the inner fill is covered by dark blue border
size = 2, color = "darkblue",
# The fill is not really useful as you cannot see it.
fill = "white") +
geom_line(mapping = aes(y = y_axis_1)) +
geom_point(mapping = aes(y = y_axis_1), size
= 3, shape = 21, fill = "white") +
# Set the main Axis start at 10 instead of 0 so it would allow more zoom into it
coord_cartesian(ylim = c(10, 20), expand = c(0, 0)) +
scale_y_continuous(
name = expression("Temperature ("~degree~"C)"),
# The calculation of second axis lable is calculate base on 1st axis.
# and as the 1st axis start at 10, there fore the fomular need to minus 10
# before multiply back 15 - I keep 150 / 10 so it clear reverse of original
# transform of the 2nd axis value above.
sec.axis = sec_axis(~ (. - 10) * 150 / 10 , name = "Charcoal (mm)"))
Here is the sample output plot
And even with the adjsut y-axis we can hardly see the temperature at the end of the data because there are a lot more data points at the end. I think if you don't need all of data point at the end you may just take every 10 x as the data was on the range of 600 years so you don't need to graph so much details at the end. And if you need details just graph that time frame separately
Filter data at the end to only take every 10 year instead
ggplot(df %>% filter(x_axis <= 2000 | x_axis %% 10 == 0),
aes(x = x_axis)) +
# similar code to above but I use geom_bar instead
geom_bar(mapping =
aes(y = (y_axis_2 * 10 / 150) + 10),
stat = "identity", size = 2, color = "darkblue",
fill = "white") +
geom_line(mapping = aes(y = y_axis_1)) +
geom_point(mapping = aes(y = y_axis_1), size
= 3, shape = 21, fill = "white")+
scale_y_continuous(
name = expression("Temperature ("~degree~"C)"),
sec.axis = sec_axis(~ (. - 10) * 150/10 , name = "Charcoal (mm)")) +
coord_cartesian(ylim = c(10, 20), expand = c(0, 0))
(As you can see that with less data point, we started to see the fill as plot have more space)
Zoom in at the end of the data
ggplot(df %>% filter(x_axis >= 2000),
aes(x = x_axis)) +
# similar code to above but I use geom_bar instead
geom_bar(mapping =
aes(y = (y_axis_2 * 10 / 150) + 10),
stat = "identity", size = 2, color = "darkblue",
fill = "white") +
geom_line(mapping = aes(y = y_axis_1)) +
geom_point(mapping = aes(y = y_axis_1), size
= 3, shape = 21, fill = "white")+
scale_y_continuous(
name = expression("Temperature ("~degree~"C)"),
sec.axis = sec_axis(~ (. - 10) * 150/10 , name = "Charcoal (mm)")) +
coord_cartesian(ylim = c(10, 20), expand = c(0, 0))
(Now we can see both the darkblue border and the white fill inside)
I am a starter in R and would like to plot a bar chart of my rainfall and solar radiation data of two years side by side from January to December (attached data).
data to plot:
I am trying to plot the first row (January) but I am getting this error
Error in -0.01 * height : non-numeric argument to binary operator
How to deal with that? and and which script to use to get my data plotted?
Regards,
Here is an example
library(tidyverse)
set.seed(123456)
df <- data.frame(Month = month.abb,
R_2014 = runif(n = 12, min = 0, max = 195),
R_2015 = runif(n = 12, min = 0, max = 295),
S_2014 = runif(n = 12, min = 3, max = 10),
S_2015 = runif(n = 12, min = 4, max = 10))
df
#> Month R_2014 R_2015 S_2014 S_2015
#> 1 Jan 155.56794 267.06645 6.344445 9.714178
#> 2 Feb 146.94519 259.85035 7.903533 9.229704
#> 3 Mar 76.29486 293.18178 9.159223 8.272923
#> 4 Apr 66.60356 264.30712 9.144556 7.632427
#> 5 May 70.45235 259.19979 8.977157 5.352593
#> 6 Jun 38.67722 58.29370 4.161913 8.437571
#> 7 Jul 104.29730 98.82311 6.660781 9.373255
#> 8 Aug 18.82262 229.27586 9.083897 5.766779
#> 9 Sep 192.63015 47.08010 4.618097 7.092115
#> 10 Oct 32.67605 23.79035 3.833566 6.607897
#> 11 Nov 155.60788 39.13185 8.767659 7.450991
#> 12 Dec 115.78983 50.71209 3.561939 8.445736
# convert from wide to long format
# separate columns to get variable and year
df_long <- df %>%
gather(key, value, -Month) %>%
separate(key, into = c("variable", "Year"), "_") %>%
mutate(Month = factor(Month, levels = month.abb))
head(df_long)
#> Month variable Year value
#> 1 Jan R 2014 155.56794
#> 2 Feb R 2014 146.94519
#> 3 Mar R 2014 76.29486
#> 4 Apr R 2014 66.60356
#> 5 May R 2014 70.45235
#> 6 Jun R 2014 38.67722
# facet by year
plt1 <- ggplot(df_long, aes(x = Month, y = value, fill = variable)) +
geom_col(position = "dodge") +
theme_bw() +
theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
facet_wrap(~ Year)
plt1
# facet by variable
plt2 <- ggplot(df_long, aes(x = Month, y = value, fill = Year)) +
geom_col(position = "dodge") +
theme_bw() +
theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
facet_wrap( ~ variable, scales = "free_y")
plt2
Created on 2018-06-01 by the reprex package (v0.2.0).
I created a plot in R using the ggplot library:
library(ggplot2)
ggplot(df, aes(x = yQ, y = value, group =1)) +
geom_line(aes(color = variable), size = 1) +
scale_color_manual(values = c("#00AFBB", "#E7B800"))
I got the plot that I want but the only problem is that variable, yQ values have the format:
1990Q1
1900Q2
1990Q3
1990Q4
......
......
2017Q1
2017Q2
2017Q3
2017Q4
and because there are many years, the x-axis label cannot show all the dates clearly (they overlapped).
Therefore, I want the x-axis label to show only Q1 and Q3 for every 5 years.
So I want the x-axis to be something like this:
1990Q1 1990Q3 1995Q1 1995Q3 ...... 2015Q1 2015Q3
I tried to use scale_x_date but my dates are not in date format (e.g. 1990Q1) and therefore this does not work. How can I fix it?
The question does not provide reproducible input but using df from the Note below with the autoplot.zoo method of ggplot's autoplot generic we can write:
library(ggplot2)
library(zoo)
z <- read.zoo(df, index = "yQ", FUN = as.yearqtr)
autoplot(z) + scale_x_yearqtr()
Note
Test input--
df <- data.frame(yQ = c("1990Q1", "1990Q2", "1990Q3", "1990Q4"), value = 1:4)
The zoo::format.yearqtr() function is quite easy to use with ggplot2.
Try
scale_x_date(labels = function(x) zoo::format.yearqtr(x, "%YQ%q"))
Use function zoo::as.yearqtr (zoo package) to work with quarterly dates.
Generate example data:
year <- 1990:2000
quar <- paste0("Q", 1:4)
foo <- as.vector(outer(year, quar, paste0))
data <- data.frame(dateQ = foo, Y = rnorm(length(foo)))
head(data)
dateQ Y
1 1990Q1 -0.09944705
2 1991Q1 0.14493910
3 1992Q1 0.54856787
4 1993Q1 1.12966224
5 1994Q1 -0.93539302
6 1995Q1 0.24772265
Transform quarterly date to "normal" date:
data$dateNorm <- as.Date(zoo::as.yearqtr(data$dateQ))
head(data)
dateQ Y dateNorm
1 1990Q1 -0.09944705 1990-01-01
2 1991Q1 0.14493910 1991-01-01
3 1992Q1 0.54856787 1992-01-01
4 1993Q1 1.12966224 1993-01-01
5 1994Q1 -0.93539302 1994-01-01
6 1995Q1 0.24772265 1995-01-01
It sets Q1/2/3/4 as the first day of January/April/July/October.
data[grep("1991", data$dateQ), ]
dateQ Y dateNorm
2 1991Q1 0.1449391 1991-01-01
13 1991Q2 1.5878678 1991-04-01
24 1991Q3 -0.1071823 1991-07-01
35 1991Q4 2.2905729 1991-10-01
Now you can plot it or perform other calculations as it's in Date format.
library(ggplot2)
ggplot(data, aes(dateNorm, Y)) +
geom_line()
You can
manipulate x-axis breaks and labels with scale_x_discrete(breaks = ..., labels = ...)
change the angle of text with theme(axis.text.x = element_text(angle = ...))
I generated some data
Combs <- expand.grid(1990:2017, c("Q1", "Q2", "Q3", "Q4"))
df <- data.frame(
yQ = sort(apply(Combs, 1, paste, collapse="")),
value = runif(112)
)
In the first example, I subset yQ values you want with a logical vector - and change the angle of text
library(ggplot2)
pattern <- c(T, F, T, F, rep(F, 16))
ggplot(df, aes(x = yQ, y = value, group =1)) +
geom_line(aes(color = "red"), size = 1) +
scale_x_discrete(breaks = df$yQ[pattern], labels = df$yQ[pattern]) +
theme(axis.text.x = element_text(angle=90))
But notice that ticks marks not specified by break are not shown - so the alternative is to copy yQ values into a vector and make non-relevant years = ""
xVec <- as.character(df$yQ)
xVec[pattern==F] <- ""
ggplot(df, aes(x = yQ, y = value, group =1)) +
geom_line(aes(color = "red"), size = 1) +
scale_x_discrete(breaks = df$yQ, labels = xVec) +
theme(axis.text.x = element_text(angle=90))
I am tryig to add several lines of text to this facet. Sorry about the mess of code
From the object means1 I want to add the values of the variables "pCensCom" "pCensEx" and "pCensReg" for each facet, as described in the following figure
This is the object 'censTot1' used to build the chart
censo censTot tipoAni censAn año pCensAn
1: 2010-01-01 42 Hembra adulta 27 2010 64.285714
2: 2010-01-01 42 Joven 4 2010 9.523810
3: 2010-01-01 42 Macho adulto 1 2010 2.380952
4: 2010-01-01 42 Ternero 10 2010 23.809524
5: 2010-01-02 42 Hembra adulta 27 2010 64.285714
---
7300: 2014-12-30 57 Ternero 16 2014 28.070175
7301: 2014-12-31 57 Hembra adulta 32 2014 56.140351
7302: 2014-12-31 57 Joven 7 2014 12.280702
7303: 2014-12-31 57 Macho adulto 2 2014 3.508772
7304: 2014-12-31 57 Ternero 16 2014 28.070175
The following describes the code used to design the figure
# Plot color background
# %%%%%%%%%%%%%%%%%%%%%%
bg0<-data.table()
for(i in 1:5){
bg<-data.table(xstart=c(as.Date(paste0(años[i],"-01-01"), format="%Y-%m-%d"),as.Date(paste0(años[i],"-03-21"), format="%Y-%m-%d"), as.Date(paste0(años[i],"-06-21"),format = "%Y-%m-%d"),as.Date(paste0(años[i],"-09-21"),format = "%Y-%m-%d"),
as.Date(paste0(años[i],"-12-21"),format = "%Y-%m-%d")),xend=c(as.Date(paste0(años[i],"-03-21"), format="%Y-%m-%d"),
as.Date(paste0(años[i],"-06-21"),format = "%Y-%m-%d"), as.Date(paste0(años[i],"-09-21"),format = "%Y-%m-%d"),
as.Date(paste0(años[i],"-12-21"),format = "%Y-%m-%d"),as.Date(paste0(años[i],"-12-31"),format = "%Y-%m-%d")),
Estacion=c("Invierno","Primavera","Verano","Otoño","Invierno"))
l=list(bg0,bg); bg0<-rbindlist(l, fill=TRUE)
}
bg0<-bg0[,Estacion:=factor(ordered(Estacion,levels=c("Invierno","Primavera", "Verano", "Otoño")))]
cbPalette<-c("#FF3300","#006633","#FFFF00","#0000FF")
plotbg<-ggplot()+ geom_rect(data = bg0, aes(xmin = xstart, xmax = xend, ymin = 0, ymax = Inf, fill = Estacion), alpha = 0.10)+ scale_fill_manual(values=cbPalette)+ guides(fill=FALSE)+theme_bw()
means1<-data.table(tipoAni=c("Hembra adulta","Joven","Macho adulto","Ternero"),pCensCom=c(62.3,17.8,0.9,19.37),pCensEx=c(61.4,16.1,1.9,20.6),pCensReg=c(63.0,17.9,1.6,24.7))
# Plot
# %%%%
plotbg + geom_line(data=censTot1,aes(x=censo,y=pCensAn))+ facet_grid(tipoAni ~ .)+ xlab("Censos diarios") + ylab("Animales (%)") +theme_bw()+ theme(strip.text.x = element_text(size=8),strip.text.y = element_text(size=10, face="bold"),strip.background = element_rect(colour="red", fill="#CCCCFF"))
Please I need help, I tried several times using the functions annotation_custom, grobTree and textGrob and I have not been able to achieve
Here is a simplified answer. First I simulate some data dat, then a second data.table backgr that has the information for the background, and lastly textdt, which holds the information about the text elements.
The code looks like this:
library(data.table)
library(ggplot2)
library(scales)
dat <- data.table(x = rep(1:100, 2),
group = rep(LETTERS[1:2], each = 100),
val = rnorm(200))
dat[, price := 100 + cumsum(val), by = group]
# plot empty
ggplot(dat, aes(x = x, y = price)) +
geom_line() +
facet_grid(group~.)
# plot with added polygons
# for the background colors
backgr <- data.table(minval = c(10, 40, 60, 90),
maxval = c(20, 60, 80, 100),
backgroup = LETTERS[1:4])
# for the text elements
textdt <- data.table(xval = c(10, 50, 70),
yval = c(105, 100, 95),
textlabel = c("foo", "bar", "lorum"),
group = c("A", "A", "B"))
# plot
ggplot() +
geom_rect(data = backgr, aes(xmin = minval, xmax = maxval, ymin = -Inf,
ymax = Inf, fill = backgroup)) +
geom_line(data = dat, aes(x = x, y = price)) +
geom_text(data = textdt, aes(x = xval, y = yval, label = textlabel,
group = group)) +
facet_grid(group~.) +
scale_fill_manual(values = alpha(c("red", "green", "blue", "yellow"), 0.5))
Which results in a plot like this, which you can adjust to fit your data:
I'd like to produce a plot with reordered months on the x axis (instead of starting in Jan and ending in Dec, I'd like to start on Apr and end on Mar).
My data is something like:
Month An Fiscal.Year Month.Number Month.Name
1 2009-04-01 40488474 2009 4 Apr
2 2009-05-01 53071971 2009 5 May
3 2009-06-01 24063572 2009 6 Jun
...
44 2012-11-01 39457771 2012 11 Nov
45 2012-12-01 44045572 2012 12 Dec
46 2013-01-01 90734077 2012 1 Jan
My code for producing the plot is:
g <- ggplot(data = data, aes(x = Month.Number, y = An)) +
geom_line(aes(group = Fiscal.Year, colour = factor(Fiscal.Year))) +
scale_x_discrete(
name = "Month",
breaks = data$Month.Number,
labels = data$Month.Name
) +
scale_y_continuous();
but the result is a plot ordered by month from Jan to Dec, not from Apr to Mar as I want.
I've tried the limits option inside scale_x_discrete, but I think this just reorders the x axis labels, not the real data.
Could you please help me?
Thanks in advance for your answer!
You have to reorder the factor levels of Month.Name. Assuming dfis your data.frame:
df$Month.Name <- factor( df$Month.Name, levels = c( "Apr", "May", ..., "Feb", "Mar" ) )
g <- ggplot(data = df, aes(x = Month.Name, y = An) ) +
geom_line(aes(group = Fiscal.Year, colour = factor(Fiscal.Year))) +
scale_x_discrete( name = "Month" ) +
scale_y_continuous();
Alternatively you can just change Month.Number such that, Apr is 1, May is 2 and so on...
Just run before plotting:
data$Month.Number <- ((data$Month.Number+8) %% 12) + 1