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I want the dates on the x-axis to appear as mm-dd-yy using lattice. Only every month needs to be shown ex: 10/1/2022, 11/1/2022 etc.
I think I may have to use format(pretty(df$date), "%d-%m-%y") based on another post but when I try I get an error:
Error in multiple && !outer : invalid 'x' type in 'x && y'
Here is my code:
library(lattice)
library(latticeExtra)
obj1 <- xyplot(Nconc + Sconc ~ date, df, type = "l", main="Title", lwd=2, col= c("red", "steelblue"))
obj2 <- xyplot(CountyCounts ~ date, df, type = "l", lwd=2, col="green")
p <- doubleYscale(obj1, obj2, use.style=FALSE, add.ylab2 = TRUE)
p
Here is a sample of my data:
structure(list(date = structure(c(1634688000, 1634774400, 1634860800,
1635033600, 1635120000, 1635206400, 1635379200, 1635465600, 1635638400,
1635811200, 1635897600, 1636070400, 1636416000, 1636502400, 1636588800,
1636675200, 1636934400, 1637020800, 1637107200, 1637280000, 1637366400,
1637625600, 1637712000, 1637971200, 1638057600, 1638144000, 1638230400,
1638316800, 1638403200), class = c("POSIXct", "POSIXt"), tzone = "UTC"),
Nconc = c(2.63e-05, 2.4e-05, 1.83e-05, 1.47e-05, 2.11e-05,
2.09e-05, 3.99e-05, 5.22e-05, 9.17e-06, 2.89e-05, 4.79e-05,
1.9e-05, 3.12e-05, 1.81e-05, 5.79e-06, 4.49e-05, 7.61e-06,
1.51e-05, 3.61e-05, 1.46e-05, 1.16e-05, 3.53e-05, 0.000232,
3.09e-05, 1.31e-06, 1.24e-05, 4.99e-05, 7.76e-05, 0.00016
), Sconc = c(2.98e-05, 2.79e-05, 1.75e-05, 2.2e-05, 2.62e-05,
2.56e-05, 4.27e-05, 5.6e-05, 1.26e-05, 3.92e-05, 6.11e-05,
1.42e-05, 2.53e-05, 2.12e-05, 4.31e-06, 4.57e-05, 9.83e-06,
1.07e-05, 3.65e-05, 2.51e-05, 1.23e-05, 2.63e-05, 0.000212,
3.99e-05, 1.42e-06, 1.08e-05, 4.09e-05, 7.89e-05, 0.000113
), CountyCounts = c(46, 45, 47, 17, 49, 49, 29, 38, 19, 20,
30, 25, 38, 24, 19, 27, 27, 30, 39, 17, 11, 23, 21, 19, 21,
43, 45, 42, 28)), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -29L))
You could add
scales = list(x = list(format = "%d-%m-%y"))
to the call creating obj1 to get the format you want. But to control the locations exactly, you will need to specify them via at, e.g.,
scales = list(x = list(at = seq(as.POSIXct("2021-11-01"), by = "1 month", length.out = 5),
format = "%d-%m-%y", at = ))
You could try playing with tick.number = 5 (default) to control the locations, and you might get lucky, but there are no guarantees that you will get exactly 1 tick per month that way.
I have a map which summarizes an indicator of the saturation percentage of real estate by neighborhood in Paris (Observed Price of real estate/maximum price set by law). I would like to add hatched on neighborhoods which have less than 5 observations included in my dataset.
I searched, but I couldn't find a way to do it. Any advice in the right direction is welcomed. Thanks.
Here is my code:
library(sp)
library(sf)
library(rgdal)
library(RColorBrewer)
library(raster)
library(classInt)
library(cartography)
#Importation
setwd("path")
shp <- readOGR(dsn="path/to/file",layer="l_qu_paris")
#Breaks
q10 <- classIntervals(map$saturation2, n=7, style="fixed",
fixedBreaks=c(45,69.999999, 79.9999999, 89.9999999, 99.9999999
,109.99999999, 120))
#Colors
my.palette <- colors()[c(73,26,128,10,652,92)]
#Map
##Scale
scale.parameter = 1.1
xshift = 0
yshift = 0
original.bbox = shp#bbox
edges = original.bbox
edges[1, ] <- (edges[1, ] - mean(edges[1, ])) * scale.parameter + mean(edges[1, ]) + xshift
edges[2, ] <- (edges[2, ] - mean(edges[2, ])) * scale.parameter + mean(edges[2, ]) + yshift
#Saturation
idx <- match(shp$l_qu, map$l_qu)
is.na(idx)
concordance <- map[idx, "saturation2"]
shp$saturation2 <- concordance
spplot(shp, "saturation2",col.regions=my.palette,
col = "black", lwd= 1, at = q10$brks,
main=list(label="% de saturation des meublés 1 pièce",cex=1.2,fontfamily="serif"),
xlim = edges[1, ], ylim = edges[2, ])
grid.text("Saturation moyenne (en%)", x=unit(0.95, "npc"), y=unit(0.50, "npc"), rot=90)
Here is my map:
saturation
Here is an example of a map that i would like to have:
saturation example
Here are the polygons in shapefile format: https://www.data.gouv.fr/fr/datasets/quartiers-administratifs/
And here is my dataset:
map <- structure(list(l_qu = c("Amérique", "Archives", "Arsenal", "Arts-et-Métiers",
"Auteuil", "Batignolles", "Bel-Air", "Belleville", "Bercy", "Bonne-Nouvelle",
"Chaillot", "Champs-Elysées", "Charonne", "Chaussée-d'Antin",
"Clignancourt", "Combat", "Croulebarbe", "Ecole-Militaire", "Enfants-Rouges",
"Epinettes", "Europe", "Faubourg-du-Roule", "Faubourg-Montmartre",
"Folie-Méricourt", "Gaillon", "Gare", "Goutte-d'Or", "Grandes-Carrières",
"Grenelle", "Gros-Caillou", "Halles", "Hôpital-Saint-Louis",
"Invalides", "Jardin-des-Plantes", "Javel", "La Chapelle", "Madeleine",
"Mail", "Maison-Blanche", "Monnaie", "Montparnasse", "Muette",
"Necker", "Notre-Dame", "Notre-Dame-des-Champs", "Odéon", "Palais-Royal",
"Parc-de-Montsouris", "Père-Lachaise", "Petit-Montrouge", "Picpus",
"Place-Vendôme", "Plaine de Monceaux", "Plaisance", "Pont-de-Flandre",
"Porte-Dauphine", "Porte-Saint-Denis", "Porte-Saint-Martin",
"Quinze-Vingts", "Rochechouart", "Roquette", "Saint-Ambroise",
"Saint-Fargeau", "Saint-Germain-des-Prés", "Saint-Gervais",
"Saint-Lambert", "Saint-Merri", "Saint-Thomas-d'Aquin", "Saint-Victor",
"Saint-Vincent-de-Paul", "Sainte-Avoie", "Sainte-Marguerite",
"Saint-Georges", "Salpêtrière", "Sorbonne", "Saint-Germain-l'Auxerrois",
"Ternes", "Val-de-Grâce", "Villette", "Vivienne", "Total"),
saturation2 = c(98.188951329533, 85.4938271604938, 83.8463463463464,
90.1460755525873, 98.1726527090667, 90.2186740262059, 92.8743271072797,
72.8549079897508, 99.2356140350877, 90.1234567901235, 114.057904044022,
NA, 87.2208980972528, 91.2562612612613, 97.9518951016991,
86.2770900920801, 91.0239726151895, 92.8305400372439, 88.6514719848053,
73.876877752942, 108.693318725755, 67.3263578578579, 85.8735259484408,
89.2100224414912, 92, 90.6120989320281, 85.8446948520848,
91.4165103088783, 97.2760978594495, 93.60892313074, 102.471730530348,
95.9062868379746, 96, 92.5484278273071, 95.0066946433545,
85.8187074829932, 101.139150713213, 92.1272297297297, 93.0625144594594,
61.8074324324324, 100.173302938197, 99.720856146949, 84.8732544128823,
84.1911355800245, 85.1122672253259, 91.8422003734504, NA,
94.612349767814, 83.2363741480137, 87.0403187718064, 92.0886931496388,
77, 110.943302180685, 100.73486307088, 66.3899425287356,
96.2527514568292, 95.7430893746874, 87.9028997984617, 48,
85.5630809345015, 92.7010730078939, 82.075822827797, 83.1727736726875,
76.2162162162162, 104.534662867996, 98.3510353194912, 78.3333333333333,
103.169134078212, 80.8779605984059, 92.63515704154, 62, 90.3902768982325,
94.1391771653151, 94.8669917042241, 94.4825319797959, 95.4279279279279,
98.2238673533848, 94.0602977590835, 87.5105365473892, 102,
92.5123935729199), numobs = c(6, 4, 4, 6, 36, 15, 4, 4, 3,
2, 16, NA, 36, 3, 32, 9, 22, 13, 11, 6, 31, 5, 15, 14, 4,
22, 3, 64, 29, 58, 7, 18, 4, 13, 23, 2, 8, 4, 47, 12, 16,
49, 50, 9, 33, 26, NA, 15, 10, 10, 23, 2, 13, 15, 2, 12,
8, 31, 1, 17, 22, 42, 7, 3, 4, 74, 4, 7, 13, 6, 2, 23, 18,
16, 17, 1, 24, 44, 8, 4, 1290)), row.names = c(NA, -81L), class = c("tbl_df",
"tbl", "data.frame"))
Neither spplot, nor ggplot2 support textured fillings. Having said that, there is a package called ggpattern which provides custom ggplot2 geoms which support filled areas with geometric and image-based patterns. See developer site for more info on ggpattern: https://coolbutuseless.github.io/package/ggpattern/index.html
With ggpattern you can plot 'hatched' or textured geom fillings. Below is a working example from the developers website:
library(maps)
crimes <- data.frame(state = tolower(rownames(USArrests)), USArrests)
crimesm <- reshape2::melt(crimes, id = 1)
states_map <- map_data("state")
p <- ggplot(crimes, aes(map_id = state)) +
geom_map_pattern(
aes(
# fill = Murder,
pattern_fill = Murder,
pattern_spacing = state,
pattern_density = state,
pattern_angle = state,
pattern = state
),
fill = 'white',
colour = 'black',
pattern_aspect_ratio = 1.8,
map = states_map
) +
expand_limits(x = states_map$long, y = states_map$lat) +
coord_map() +
theme_bw(18) +
labs(title = "ggpattern::geom_map_pattern()") +
scale_pattern_density_discrete(range = c(0.01, 0.3)) +
scale_pattern_spacing_discrete(range = c(0.01, 0.03)) +
theme(legend.position = 'none')
p
I have a dataset df1. I would like to chart a line graph with Date as X and Chart1 and T1. I would like to loop it for all column where I would get the same graph when Y is Chart2 and T2 as well as when Y is Chart3 and T3.
dput(df1) >
structure(list(Date = c(1990, 1991, 1992, 1993, 1994), Chart1 = c(25,
34, 19, 7, 4), T1 = c(23.5, 23.5, 23.5, 23.5, 23.5), Chart2 = c(2,
4, 12, 9, 15), T2 = c(10, 10, 10, 10, 10), Chart3 = c(11, 9,
8, 6, 2), T3 = c(5, 5, 5, 5, 5)), row.names = c(NA, -5L), class = c("tbl_df",
"tbl", "data.frame"))
This is the chart that I would like to get for each column (Chart2,T2) and (Chart3,T3) etc.
ggplot(df1, aes(x=Date)) + geom_line(aes(y=Chart1)) + geom_line(aes(y=T1), color="red")
You may separate out 'Chart' variables and 'T' variables and create list of plots.
library(ggplot2)
chart_cols <- grep('Chart', names(df1), value = TRUE)
t_cols <- grep('T\\d+', names(df1), value = TRUE)
list_plots <- Map(function(x, y) ggplot(df1, aes(x=Date)) +
geom_line(aes(y=.data[[x]])) +
geom_line(aes(y=.data[[y]]), color="red"), chart_cols, t_cols)
I have a boxplot with a group on the left (Baseline.RT) and a group on the right (TBPM.RT). I want to rename Baseline.RT to 1-back and TBPM.RT to TBPM. I also want each group to have a different square frame. I would also like to try black and white options to fill in the values for Neutral, Positive, and Negative.
I have tried several options but did not get the result I wanted. Below is my code. Any help is welcome.
DataFrame:
data.frame(
stringsAsFactors = FALSE,
Participant = c(1, 2, 3, 4, 5, 6),
Sex = c("m", "m", "m", "f", "f", "m"),
Age = c(29, 21, 29, 22, 25, 31),
Stress = c(14, 26, 11, 19, 15, 15),
Dass21.total = c(6, 43, 4, 10, 12, 8),
Dass21Ansie = c(0, 12, 1, 3, 2, 2),
Dass.Depre = c(1, 11, 0, 1, 3, 0),
Dass.Stress = c(5, 20, 3, 6, 7, 6),
Valence = c(0, 1, 2, 0, 1, 2),
Baseline.RT = c(1.17657473346937,
0.656485061072056,0.617504973518475,0.552112912223171,
0.587283706967395,0.569011248952529),
TBPM.RT = c(1.16126499995575,
0.682658424923267,0.643632301167193,0.589782671563839,
0.705303832011063,0.691478784144668),
TotalClockChecks = c(44, 97, 44, 93, 32, 90),
TotalChecks5060 = c(13, 22, 17, 23, 10, 27),
TotalClockResets = c(18, 20, 19, 19, 18, 19),
Correct.Resets = c(16, 16, 18, 18, 12, 19),
Before.55.Resets = c(0, 2, 0, 1, 0, 0),
After.65.Resets = c(2, 2, 1, 0, 6, 0),
MeanResetTime = c(63.0026438647087,
58.9040712799639,60.9928466685597,60.4603108544334,
65.859630879724,60.5522703813385),
Accuracy.Baseline = c(0.987179487179487,
0.991489361702128,0.97907949790795,0.987234042553191,1,
0.987234042553191),
Accuracy.TBPM = c(0.968619246861925,
0.972746331236897,0.989626556016598,0.972515856236786,
0.974736842105263,0.991786447638604),
rau.Baseline = c(112.453264487601,
114.413187265486,109.508971532343,112.475825131896,
122.999999959683,112.475825131896),
rau.TBPM = c(106.447535249234,
107.58519024216,113.516946707831,107.519541719961,
108.163803190644,114.564811317506)
)
Plot:
my44 %>%
select(Participant, Valence, Baseline.RT,TBPM.RT) %>% #Select interest variables
gather(Task,RT, -Valence, -Participant) %>%
ggplot(., aes(factor(Valence), RT)) + #plot
geom_boxplot() + facet_wrap(~ Task) +
scale_x_discrete(name = element_blank(), labels=c("0" = "Neutral", "1" = "Positive", "2" = "Negative")) +
scale_fill_discrete(name="Valence",
breaks=c("0", "1", "2"),
labels=c("Neutral", "Positive",
"Negative"))
The obtained results:
Created on 2020-09-02 by the reprex package (v0.3.0)
It sounds like you're looking for something like this (although your question's input data doesn't produce the values displayed in your plot, and you seem to have a default theme set somewhere).
Your fill colours can be chosen by scale_fill_manual, but you need to map the Valence variable to the fill scale if you want the different boxes to have different colours.
If you want a frame around each facet, theme_bw does this by default, or you can use theme(panel.border = element_rect(colour = "black")).
To re-name facets, I would normally just re-name the faceting variables to the desired names in the input, but here I have shown an alternative method using the labeller parameter in facet_wrap.
my44 %>%
select(Participant, Valence, Baseline.RT,TBPM.RT) %>% #Select interest variables
gather(Task,RT, -Valence, -Participant) %>%
ggplot(., aes(factor(Valence), RT)) +
geom_boxplot(aes(fill = factor(Valence))) +
facet_wrap(~ Task,
labeller = function(x) data.frame(Task = c("1-back", "TBPM"))) +
scale_x_discrete(name = element_blank(),
labels=c("0" = "Neutral", "1" = "Positive", "2" = "Negative")) +
scale_fill_manual(name="Valence",
breaks=c("0", "1", "2"),
labels=c("Neutral", "Positive","Negative"),
values = c("gray50", "gray75", "gray95")) +
theme_bw() +
theme(legend.position = "none",
strip.background = element_blank())
I want to display a scatter plot of points from a csv table with ggplot2. The trick is that I'd like each point, or cross, to have a different colour according to their row number in the csv file (using RColorBrewer's spectral colours).
The dataset (dat) looks like this:
modu mnc eff
1 0.3080473 0 0.4420544
2 0.3110355 4 0.4633741
3 0.3334024 9 0.4653061
So I'd like row 1 to be very blue, row two to be a little less, row three to be kind of green, etc.
Here's my code so far:
library(ggplot2)
library(RColorBrewer)
dat <- structure(list(modu = c(0.30947265625, 0.3094921875, 0.32958984375,
0.33974609375, 0.33767578125, 0.3243359375, 0.33513671875, 0.3076171875,
0.3203125, 0.3205078125, 0.3220703125, 0.28994140625, 0.31181640625,
0.352421875, 0.31978515625, 0.29642578125, 0.34982421875, 0.3289453125,
0.30802734375, 0.31185546875, 0.3472265625, 0.303828125, 0.32279296875,
0.3165234375, 0.311328125, 0.33640625, 0.3140234375, 0.33515625,
0.34314453125, 0.33869140625), mnc = c(15, 9, 6, 0, 10, 12, 14,
9, 5, 11, 0, 15, 0, 2, 14, 13, 14, 17, 11, 12, 13, 6, 4, 0, 13,
7, 10, 12, 7, 13), eff = c(0.492448979591836, 0.49687074829932,
0.49421768707483, 0.478571428571428, 0.493537414965986, 0.493809523809524,
0.49891156462585, 0.499319727891156, 0.495102040816327, 0.492285714285714,
0.482312925170068, 0.498911564625851, 0.479931972789116, 0.492857142857143,
0.495238095238095, 0.49891156462585, 0.49530612244898, 0.495850340136055,
0.50156462585034, 0.496, 0.492897959183673, 0.487959183673469,
0.495605442176871, 0.47795918367347, 0.501360544217687, 0.497850340136054,
0.493496598639456, 0.493741496598639, 0.496734693877551, 0.499659863945578
)), .Names = c("modu", "mnc", "eff"), row.names = c(NA, 30L), class = "data.frame")
dat2 <- structure(list(modu = c(0.26541015625, 0.282734375, 0.28541015625,
0.29216796875, 0.293671875), mnc = c(0.16, 0.28, 0.28, 0.28,
0.28), eff = c(0.503877551020408, 0.504149659863946, 0.504625850340136,
0.505714285714286, 0.508503401360544)), .Names = c("modu", "mnc",
"eff"), row.names = c(NA, 5L), class = "data.frame")
dat$modu = dat$modu
dat$mnc = dat$mnc*50
dat$eff = dat$eff
dat2$modu = dat2$modu
dat2$mnc = dat2$mnc*50
dat2$eff = dat2$eff
res <- do.call(rbind, combn(1:3, 2, function(ii)
cbind(setNames(dat[,c(ii, setdiff(1:3, ii))], c("x", "y")),
var=paste(names(dat)[ii], collapse="/")), simplify=F))
ggplot(res, aes(x=x, y=y))+ geom_point(shape=4) +
facet_wrap(~ var, scales="free")
How should I go about doing this?
Thanks!
res <- do.call(rbind, combn(1:3, 2, function(ii)
cbind(row=seq(nrow(dat)),setNames(dat[,c(ii, setdiff(1:3, ii))], c("x", "y")),
var=paste(names(dat)[ii], collapse="/")), simplify=F))
ggplot(res, aes(x=x, y=y, color=row))+ geom_point(shape=4) +
scale_color_gradientn(colours=rev(brewer.pal(10,"Spectral")))+
facet_wrap(~ var, scales="free")