In base R, I like to make plots with time on the x-axis where the labels are shown in between long tick marks. For example, there may be tick marks at June 1 and June 31, but the text "June" shows up in between, centered around June 15. In base R, I simply draw 2 axes, one with the ticks and one with the labels.
However, I haven't been able to figure out how to make this style of axis in ggplot2.
Simply offsetting the text adjustment is not precise enough.
Creating a single axis with labels = c("","June","") almost works but tick marks only accept one length so something like axis.ticks.length = unit(c(.25,0,.25),"cm") doesn't work.
I think something like this might be possible with the ggh4x package but I haven't been able to figure it out. I will be happy for any solution compatible with ggplot2, regardless of which package.
Have you looked into the scales package? Instead of manually creating x-axis ticks and labels, you can specify exactly how many x-axis tick marks and labels you want with breaks_pretty and specify date formatting with label_date. More info on date formatting here.
library(tidyverse)
library(scales)
time <- seq(as.Date("2020-1-1"), as.Date("2022-1-1"), by = "months")
var <- c(1:15, 15:6)
df <- data.frame(var, time) %>%
mutate(time = as.Date(time))
# original
df %>%
ggplot(aes(x = time, y = var)) +
geom_bar(stat = "identity")
# just month names
df %>%
ggplot(aes(x = time, y = var)) +
geom_bar(stat = "identity") +
scale_x_date(labels = label_date("%B"))
# increase tick marks with month names and full year
df %>%
ggplot(aes(x = time, y = var)) +
geom_bar(stat = "identity") +
scale_x_date(labels = label_date("%B %Y"),
breaks = breaks_pretty(n = 12)) # <- change 12 to another number
Related
I have a work project where I've been given a spreadsheet with tons of data and I want to plot it using R to look for trends.
The issue I am having is that I cannot plot it correctly using ggplot because I want to place to variables in the Y-Axis.
My goal is to plot "interest" and "awareness" on the Y-axis in different colors, say green and blue, and "admissions" on the X-axis.
Unfortunately, I am new StackOverflow and cannot include my Excel spreadsheet, so I included a screenshot for reference.
Excel note - the actual spreadsheet has 381 titles
ggplot(data =data, aes(x = 'admissions', y =
'interest')) + geom_line()
Here is one way we could do it:
library(tidyverse)
df %>%
pivot_longer(
c(interest, awarenes)
) %>%
mutate(value_number = parse_number(value)) %>%
ggplot(aes(x = admission, y = value_number, color= name, group=name)) +
geom_point()+
geom_line()+
scale_y_continuous(labels = function(x) paste0(x, "%"))+
scale_color_manual(values=c("green", "blue"))+
theme_bw()
I realize this is a simple question, but I’m having trouble getting this graph to display right.
I have a dataset like:
pet
pet_counts
dog
22
cat
100
birs
2
I want to make a bar graph that has the X-Axis labeled with each animal and the counts along the Y. When I specify, labs it just changed the words in the label but not the value below the tick marks.
I want the x axis to say dog and then in the Y have a count for f 22, for example.
I have tried:
Graph <- ggplot(data = animals, aes(pet_counts)) + geom_bar(stat=“count”) + labs(x = “pet”)
I think you're looking for geom_col() instead of geom_bar():
library(dplyr)
library(ggplot2)
animals <- tibble(
pet = c("dog", "cat", "birds"),
pet_counts = c(22, 100, 2)
)
animals %>%
ggplot(aes(x = pet, y = pet_counts)) +
geom_col() +
labs(
x = "Pet",
y = "Count"
)
The labs() function is optional, and will just change the names on the axis to something more readable.
The result:
The difference between geom_col() and geom_bar(), according to the documentation:
geom_bar() makes the height of the bar proportional to the number of cases in each group. If you want the heights of the bars to represent values in the data, use geom_col() instead.
Since you already have pet_counts, you should use geom_col().
I have three vectors and a list of crimes. Each crime represents a row. On each row, each vector identifies the percentage change in the number of incidents of each type from the prior year.
Below is the reproducible example. Unfortunately, the df takes the first value in and repeats in down the columns (this is my first sorta reproducible example).
crime_vec = c('\tSTRONGARM - NO WEAPON', '$500 AND UNDER', 'ABUSE/NEGLECT: CARE FACILITY', 'AGG CRIM')
change15to16vec = as.double(825, -1.56, -66.67, -19.13)
change16to17vec = as.double(8.11, .96, 50, 4.84)
change17to18vec = as.double(-57.50, 1.29, 83.33, 28.72)
df = data.frame(crime_vec, change15to16vec, change16to17vec, change17to18vec)
df
I need a graph that will take the correct data frame, show the crimes down the y axis and ALL 3 percentage change vectors on the x-axis in a dodged bar. The examples I've seen plot only two vectors. I've tried plot(), geom_bar, geom_col, but can only get one column to graph (occasionally).
Any suggestions for a remedy would help.
Not sure if this is what you are looking for:
library(tidyr)
library(ggplot2)
df %>%
pivot_longer(-crime_vec) %>%
ggplot(aes(x = value, y = crime_vec, fill = as.factor(name))) +
geom_bar(stat = "identity", position = "dodge") +
theme_minimal() +
xlab("Percentage Change") +
ylab("Crime") +
labs(fill = "Change from")
For using ggplot2 it's necessary, to bring your data into a long format. geom_bar should create your desired plot.
Currently, I have this plot that looks like this:
I don't like how on the x-axis there are weird lines / bars. I suspect this may be because ggplot can't fit all 540000 observations in the x axis. Here is the code I used to graph this:
data %>%
ggplot() +
geom_point(aes(x = dates_df$date, y = Quantity)) +
theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
labs(x = "Invoice Date", y = "Quantity", title = "Quantity vs Invoice Date")
What can I do to get rid of / solve this mess on the x-axis?
As was told on comments it seems there is a mess in Date column and you use of two separate data frames. As first join the data. I assume both of them has some Id or other key like name in column:
library("dplyr")
left_join(data,dates_df,by="id")
Date is also a character as was mentioned. To change it to Date, if you haven't already do this use as.Date function. After joining
data$date<- as.Date(data$date, "%m/%d/%Y")
you can find other date formats here: http://www.statmethods.net/input/dates.html
You said there are 540 000 observation on x axis. My suggestfion is to separate the chart for unique year. To do this use facet_grid function inside ggplot.
library(lubridate)
ggplot(df, aes(x= df$date,y= df$Quantity))+
geom_point() +
facet_grid(~year(df$date))
Hope it helped :)
This might be fairly simple but yet i cant seem to find out how to do it.
I got a nice plot with a group of lines of values in it.
The y represents an amount, the x represents dates.
The problem is simple, there so many dates that they are printed on top of each other.
The code :
sp = rbind(sp1,sp2,sp3,sp4)
pm = ggplot(data = sp, aes(x = date,
y = amount,
colour=sm,
group=sm)) +
geom_line()
How can I make the x axis only print for example every 5 dates instead of all of them?
Thanks in advance!
library(scales)
sp = rbind(sp1,sp2,sp3,sp4)
pm = ggplot(data = sp, aes(x = date, y = amount, colour=sm, group=sm)) +
geom_line() +
scale_x_date("x axis title", breaks = "5 years")
scale_x_date will sort out the x axis labels for you. To specify the label intervals use the scales packages as above. (p.s your dates need to be of class Date, POSIXct or POSIXlt)