Reputation: 37
I have a heatmap drawing a dataframe that has 3 columns and 100 rows. X and Y axes are representing X and Y coordinates. When I create the map, it shows every location and becomes unreadable.
Both axis range from 0-100. I would like both axis to just go 0,10,20,30,40,50,60,70,80,90,100. Can anyone help me clean this up? Thanks.
ggplot( data = CombinedDF, mapping = aes( x = factor(allPoints.xLocs), y = factor(allPoints.yLocs) ) ) +
geom_tile( aes( fill = sum_patch ), colour = "white") + labs( x = "X-Coordinate", y = "Y-Coordinate") +
theme_bw() + theme(axis.text.x = element_text(angle = 45, hjust = 1))
Here is the sample of the input dataframe "CombinedDF"
allPoints.xLocs allPoints.yLocs sum_patch
1 74.106128071 62.2365805 13
2 70.786698116 58.8928561 13
3 65.543694422 33.8426416 3
4 8.647094783 50.1071865 2
5 95.822909172 11.3294181 4
6 91.324434988 42.4157078 5
7 96.444815141 68.6108005 13
8 13.105758978 83.1488258 7
9 92.958515161 74.3948395 13
10 76.149455458 98.8090307 4
When I remove "factor" I get this (axis are correct but no data?):
Upvotes: 0
Views: 5261
Reputation: 16178
Your data are not fully complete to make a heatmap. You don't have a single value for each combinations of X and Y.
Here, I reproduce your example by doing:
DF <- data.frame(X = runif(100,0,100),
Y = runif(100,0,100),
sum = sample(0:30,100, replace =TRUE))
You can plot them as point:
ggplot(DF,aes(x = X, y = Y, color= sum))+
geom_point()
An another possibility if you want to make an heatmap is to create some group intervals (0-10 / 10-20 / ...). You can do that by using cut
functions:
library(dplyr)
DF <- DF %>% mutate(CutX = cut(X,seq(0,100, by = 10)),
CutY = cut(Y,seq(0,100, by = 10)))
X Y sum CutX CutY
1 19.48048 79.1970915 17 (10,20] (70,80]
2 42.47574 34.1226793 10 (40,50] (30,40]
3 43.99754 25.7454872 7 (40,50] (20,30]
4 90.88465 0.3961523 18 (90,100] (0,10]
5 46.26645 38.0338865 25 (40,50] (30,40]
6 93.15978 59.9426569 15 (90,100] (50,60]
Then, you need to expand this dataframe for each combinations of X and Y by doing:
Expand_DF <- expand.grid(CutX = unique(DF$CutX), CutY = unique(DF$CutY))
Expand_DF$Sum <-NA
CutX CutY Sum
1 (10,20] (70,80] NA
2 (40,50] (70,80] NA
3 (90,100] (70,80] NA
4 (30,40] (70,80] NA
5 (80,90] (70,80] NA
6 (70,80] (70,80] NA
Finally, you can bind them together and if several values are in the same interval, you can calculate the mean and finally plot them in ggplot by doing:
library(dplyr)
library(ggplot2)
DF %>% bind_rows(.,Expand_DF) %>%
group_by(CutX, CutY) %>%
summarise(Sum = mean(sum,na.rm = TRUE)) %>%
ggplot(aes(x = CutX, y = CutY, fill = Sum))+
geom_tile(color = "black")+
scale_fill_gradient(na.value = "white")
Does it answer your question ?
Upvotes: 1
Reputation: 859
Add
scale_x_continuous(n.breaks=10, limits=c(0,100))+
scale_y_continuous(n.breaks=10, limits=c(0,100))
to your ggplot.
Add labes=seq(1,100,10)
to both scale functions to modify the label text to be 0-100 with steps of 10.
Upvotes: 1