Change y axis values and scale - r

I am using RStudio.
I´m trying to change the values of the x-axis to 20 - 35 and with an interval of 0,625. However, I don´t seem to find the right code. if I use this code:
ggplot(a1diurnalInflow, aes(x=Time, y=Potential.Air.Temperature....C.,group=1)) +
geom_point() +
geom_line() +
coord_cartesian(ylim = c(0, 35))
The output is weird (see picture two)
Picture one is the plot how it is right now with this code
ggplot(a1diurnalInflow, aes(x=Time, y=Potential.Air.Temperature....C.,group=1)) +
geom_point() +
geom_line()
Kind regards,
Giorgia
♦Current output
Wrong output

Related

Manually applying different colors in R ggplot

ggplot(data = s2[1:39,], aes(x=Month, y=Users, group=Year, col=Year)) + geom_line(size=1.3) + geom_point(size=4.5) + geom_point(size=4.0, color='#FFFFFF') + ggtitle("Seoul_year") + scale_x_continuous(breaks=c(1,2,3,4,5,6,7,8,9,10,11,12)) + scale_y_continuous(labels = scales::comma)
From the upper code I keep getting same blueish colors(per year) in plotting line graph in R.
However, I want to apply different color of lines in the graph.
Which code line should I fix?

try
scale_color_gradient(low="red",high="black")
while red or black can be whatever, including HEX code.
It still means your Year variable is numeric though.

ggplot2: geom_text() in geom_col() with POSIXt x axis [duplicate]

I would like to plot a time series using bar charts and have the Bin Width set to 0.9. I cannot seem to be able to do that however. I have searched around but could not find anything helpful so far. Is this a limitation if the stat="identity ?
Here is a sample data and graph.
Cheers !
time <- c('2015-06-08 00:59:00','2015-06-08 02:48:00','2015-06-08 06:43:00','2015-06-08 08:59:00','2015-06-08 10:59:00','2015-06-08 12:59:00','2015-06-08 14:58:00','2015-06-08 16:58:00','2015-06-08 18:59:00','2015-06-08 20:59:00','2015-06-08 22:57:00','2015-06-09 00:59:00','2015-06-09 01:57:00','2015-06-09 03:22:00','2015-06-09 06:14:00','2015-06-09 08:59:00','2015-06-09 10:59:00','2015-06-09 12:59:00','2015-06-09 14:59:00','2015-06-09 16:59:00','2015-06-09 18:59:00','2015-06-09 20:59:00','2015-06-09 22:58:00','2015-06-10 00:57:00','2015-06-10 02:34:00','2015-06-10 04:45:00','2015-06-10 06:24:00','2015-06-10 08:59:00','2015-06-10 10:59:00','2015-06-10 12:59:00','2015-06-10 14:59:00','2015-06-10 16:59:00','2015-06-10 18:59:00','2015-06-10 20:58:00','2015-06-10 22:52:00','2015-06-11 00:59:00','2015-06-11 02:59:00','2015-06-11 04:59:00','2015-06-11 06:59:00','2015-06-11 08:59:00','2015-06-11 10:59:00','2015-06-11 12:59:00','2015-06-11 14:59:00','2015-06-11 16:58:00','2015-06-11 18:58:00','2015-06-11 20:56:00','2015-06-11 21:49:00','2015-06-12 00:59:00','2015-06-12 02:59:00','2015-06-12 04:20:00','2015-06-12 08:55:00','2015-06-12 10:55:00','2015-06-12 12:59:00','2015-06-12 14:59:00','2015-06-12 16:59:00','2015-06-12 18:59:00','2015-06-12 20:55:00','2015-06-12 22:50:00','2015-06-13 00:16:00','2015-06-13 12:59:00','2015-06-13 14:35:00','2015-06-13 16:56:00','2015-06-13 18:59:00','2015-06-13 20:59:00','2015-06-13 22:44:00','2015-06-13 23:19:00','2015-06-14 08:53:00','2015-06-14 10:14:00','2015-06-14 12:59:00','2015-06-14 14:59:00','2015-06-14 16:56:00','2015-06-14 18:58:00','2015-06-14 20:57:00','2015-06-14 22:31:00','2015-06-14 23:59:00')
count <- c(59,63,9,13,91,80,97,210,174,172,167,74,43,18,18,29,136,157,126,170,188,135,207,216,163,163,126,111,172,213,209,265,203,205,195,201,171,157,153,176,187,252,227,223,171,162,146,161,136,124,155,239,233,157,158,125,138,45,45,1,2,6,6,46,48,4,1,1,12,56,65,122,81,110,42)
level <- c('low','low','low','low','low','low','low','high','normal','normal','normal','low','low','low','low','low','low','normal','low','normal','normal','low','high','high','normal','normal','low','low','normal','high','high','high','high','high','normal','high','normal','normal','normal','normal','normal','high','high','high','normal','normal','low','normal','low','low','normal','high','high','normal','normal','low','low','low','low','low','low','low','low','low','low','low','low','low','low','low','low','low','low','low','low')
DF = data.frame(time, count, level)
DF$time = as.POSIXct(DF$time)
ggplot(DF, aes(x=time, y=count, fill=level), width=0.9) +
geom_bar(stat="identity") +
scale_x_datetime(labels = date_format("%D"), breaks = date_breaks("day")) +
xlab("myXlabel") +
ylab("myYlabel") +
ggtitle("myTitle")

Found it ! Actually, the width is supported, though the scale is in seconds since I'm plotting a time series where the X axis is formatted as a POSIX date. Therefore, a width=0.9 means the bin width is 0.9 seconds. Since my bins are 2hrs eachs then a width of "1" is actually 7200. So here is the code that works.
ggplot(DF, aes(x=time, y=count, width=6000, fill=level)) +
geom_bar(stat="identity", position="identity", color="grey") +
scale_x_datetime(labels = date_format("%D"), breaks = date_breaks("day")) +
xlab("myXlabel") +
ylab("myYlabel") +
ggtitle("myTitle")
Results as below. There are some averlaps in the bars, I just need to aligh my data, say to the next hour.

If what you are trying to achieve is widening the bars in the plot, ggplot doesn't seem to support that for geom_bar. However, it is pretty straightforward to implement a barplot using geom_rect.
Since many of the datapoints seem to be spaced roughly two hours apart, I am assuming here that the 0.9 width you want to achieve is 0.9 hours to either side of the given time (so basically smushing out most of the space between the bars.
If that's what you want, the following code should work:
library(lubridate)
ggplot(DF, aes(xmin=time-minutes(54), xmax=time+minutes(54), ymin=0, ymax=count,
fill=level)) +
geom_rect(color="#666666")

I am also trying to wrap my head around R.
I have worked on a solution and found a solution that also provided me with a warning pointing at the problem - overlapping time x intervals. The error disappears at width = 2000. By supplementing with position = "dodge": "places overlapping objects directly beside one another" - https://r4ds.had.co.nz/data-visualisation.html - you can achieve a reasonable plot.
# Original file
ggplot(DF, aes(x=time, y=count, fill=level, width=2000), position = "dodge") +
geom_bar(stat="identity") +
scale_x_datetime(labels = date_format("%D"), breaks = date_breaks("day")) +
xlab("myXlabel") +
ylab("myYlabel") +
ggtitle("myTitle")
PREVIOUS VERSION NOT SO GOOD Here is another solution:
ggplot(DF, aes(x=time, y=count, colour = level)) +
geom_bar(stat="identity") +
scale_x_datetime(labels = date_format("%D"), breaks = date_breaks(width = "day")) +
xlab("myXlabel") +
ylab("myYlabel") +
ggtitle("myTitle")
colour=level gives wider columns

No line in plot chart despite + geom_line()

I've read documentation and I think that my code should be right, but still there is no line between the points in the output. What is wrong?
The x'axis is discrete and y'axis is continuous.
My code
point.sqrmPrice <- ggplot(overview.df, aes(x = areaSize, y = sqrmPrice)) +
geom_line() +
geom_point() +
scale_y_continuous(breaks = c(seq(min(overview.df$sqrmPrice), max(overview.df$sqrmPrice), by = 10000) )) +
theme_bw()

The underlying issue here is a duplicate of this stack post.
Here's a reproducible example showing what #SN248 meant about adding group to the code
ggplot(iris, aes(x = factor(Sepal.Length), y = Sepal.Width)) +
geom_line(aes(group=1)) + geom_point() + theme_bw()

You are not getting a line because areaSize is a factor. Convert to numeric with
overview.df$areaSize <- as.numeric(as.character(overview.df$areaSize))
and then make the plot.

What you have to think about it is, do you expect a single line to connect all the dots?
Else, how many lines do you expect, that will tell you how many groups will you need to have.
You are missing the group aesthetic required for geom_line(), because you haven't specified how many groups (lines) you want in your plot.

Draw mean and outlier points for box plots using ggplot2

I am trying to plot the outliers and mean point for the box plots in below using the data available here. The dataset has 3 different factors and 1 value column for 3600 rows.
While I run the below the code it shows the mean point but doesn't draw the outliers properly
ggplot(df, aes(x=Representations, y=Values, fill=Methods)) +
geom_boxplot() +
facet_wrap(~Metrics) +
stat_summary(fun.y=mean, colour="black", geom="point", position=position_dodge(width=0.75)) +
geom_point() +
theme_bw()
Again, while I am modify the code like in below the mean points disappear !!
ggplot(df, aes(x=Representations, y=Values, colour=Methods)) +
geom_boxplot() +
facet_wrap(~Metrics) +
stat_summary(fun.y=mean, colour="black", geom="point", position=position_dodge(width=0.75)) +
geom_point() +
theme_bw()
In both of the cases I am getting the message: "ymax not defined: adjusting position using y instead" 3 times.
Any kind suggestions how to fix it? I would like to draw the mean points within individual box plots and show outliers in the same colour as the plots.
EDIT:
The original data set does not have any outliers and that was reason for my confusion. Thanks to MrFlick's answer with randomly generated data which clarifies it properly.

Rather than downloading the data, I just made a random sample.
set.seed(18)
gg <- expand.grid (
Methods=c("BC","FD","FDFND","NC"),
Metrics=c("DM","DTI","LB"),
Representations=c("CHG","QR","HQR")
)
df <- data.frame(
gg,
Values=rnorm(nrow(gg)*50)
)
Then you should be able to create the plot you want with
library(ggplot2)
ggplot(df, aes(x=Representations, y=Values, fill=Methods)) +
geom_boxplot() +
stat_summary(fun.y="mean", geom="point",
position=position_dodge(width=0.75), color="white") +
facet_wrap(~Metrics)
which gave me
I was using ggplot2 version 0.9.3.1

ggplot removes all my data when I set x and y limits

I'm using R to generate a plot from a table.
I used the command a <- read.table("table.txt") and that worked fine. When I type "a" it prints out my full table correctly.
I also entered library(ggplot2) so I could use ggplot.
Here was my first command:
ggplot(a, aes(x=V2, y=V5, group=V7)) +
geom_point(size=4, aes(col=V7)) + xlab("Rank") +
ylab("Inter-helix angle (Degree)") +
opts(legend.position="none")
this command generated all the points, but when I added xlim(0,110) + ylim(0,110) to the end, it gave me a warning and said "Removed 101 Rows containing missing values" (my table is 101 rows long). The plot that was generated was completely empty. What happened?

I'm guessing perhaps your data falls out of the ranges you have specified in xlim and ylim e.g.:
library(ggplot2)
df <- data.frame(x=1:10,y=1:10)
ggplot(a, aes(x=x, y=y)) +
geom_point(size=4) + xlab("Rank") +
ylab("Inter-helix angle (Degree)")
works fine, but:
ggplot(df, aes(x=x, y=y)) +
geom_point(size=4) + xlab("Rank") +
ylab("Inter-helix angle (Degree)") + xlim(0,0.1) + ylim(0,0.1)
gives the same error as you get because no values fall between 0 and 0.1
Warning message:
Removed 10 rows containing missing values (geom_point).
Although without your data this is just the most likely answer. By the way in general folk tend to use coord_cartesian:
ggplot(df, aes(x=x, y=y)) +
geom_point(size=4) + xlab("Rank") +
ylab("Inter-helix angle (Degree)") + coord_cartesian(xlim=c(0,0.1)) +
coord_cartesian(ylim=c(0,0.1))

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