When we look at the mtcars dataset in R:
head(mtcars)
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
I want to select the Mazda models with 6 cylinders (cyl is 6) and see which of those cars has the most horse power hp. Or, alternatively, I want to see which Merc model with 4 cylinders has the highest hp.
How can I do that? Do I subset? Or maybe grep?
You want to check two conditions: The model name of the car and the cylinder numbers, right?
You can subset the data to the rows that satisfy your (double) condition and then see which of the remaining rows has the highest values for the column hp
bestcar <- function(carname, cyl_nr){
inds <- (grepl(carname, rownames(mtcars)) & mtcars$cyl == cyl_nr)
subdf <- mtcars[inds, ]
rownames(subdf)[which.max(subdf$hp)]
}
bestcar("Mazda", 6)
# "Mazda RX4"
bestcar("Merc", 4)
# "Merc 230"
Related
I have a column including lots of "0" and other values (f.i. 2 or 2,3 etc). Is there any possibility to rename the columns with 0 to "None" and all other values to "others"? I wanted to use fct_recode or fct_collapse but cant figure out how to include all other values. Do you have any idea? I must not be necessarily include the fct_recode function.
Thanks a lot
Philipp
I tried to use fct_recode, fct_collapse
Here is a way to do it using mtcars and the vs column as an example:
cars <- mtcars
head(cars)
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
cars$vs <- ifelse(cars$vs == 0, "none", "other")
head(cars)
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 none 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 none 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 other 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 other 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 none 0 3 2
Valiant 18.1 6 225 105 2.76 3.460 20.22 other 0 3 1
Note that R coerces the vs column from numeric to character. But you could do that explicitly first for clarity:
cars$vs <- as.character(cars$vs)
Using dplyr, we can do this on multiple colums as
library(dplyr)
df1 <- df1 %>%
mutate(across(everything(), ~ case_when(.x == 0 ~ "none", TRUE ~ "other")))
Or in base R
df1[] <- c("other", "none")[1 + (df1 == 0)]
When I run colnames(), it never shows the name of this first column.
For example, after wasting a lot of time researching online, I discovered the name of the first column in mtcars is das_Auto.
Why doesn't this name show when I run this code?
[colnames(mtcars)][1]
What's the easiest way to determine the name of the first column in a data set?
This is because the first 'column' of mtcars is not actually a column but an index. If you want to convert it to a column you can run the below:
df <- cbind(das_Auto = rownames(mtcars), mtcars)
rownames(df) <- 1:nrow(mtcars)
head(df)
das_Auto mpg cyl disp hp drat wt qsec vs am gear carb
1 Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
2 Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
3 Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
4 Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
5 Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
6 Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
I'm trying to add a column to a dataframe using add_column and if_else but I can get it I don't know how to do a correct logical test using logical conditional (or "|").
I have this kind data:
dataframe1
variable 1 variable2 variable3
(char) (char) (char)
value value value
value value value
value value value
I try this:
dataframe2 <- dataframe1%>%
add_column(newcolumn_name = if_else(variable3== "value1"|"value2”, TRUE, FALSE)
And I get this error:
Unknown or uninitialised column: value1.Error in variable3 ==
“value1“| "value2" : operations are possible only for numeric,
logical or complex types
Consider to extract the column with .$. The == can be replaced with %in% and | is used mostly with regex pattern (OR) while == does a fixed match. In addition, the output of == or %in% returns a logical vector. So, we don't need the if_else/ifelse
library(dplyr)
library(tibble)
dataframe1 %>%
add_column(newcolumn_name = .$variable3 %in% c("value1", "value2"))
Using a reproducible example
head(mtcars) %>%
add_column(new_column_name = .$carb %in% c(1, 4))
mpg cyl disp hp drat wt qsec vs am gear carb new_column_name
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 TRUE
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 TRUE
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 TRUE
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 TRUE
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 FALSE
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1 TRUE
Also, this can be done within dplyr itself i.e. using mutate and thus we don't need to extract the column
head(mtcars) %>%
mutate(new_column_name = carb %in% c(1, 4))
mpg cyl disp hp drat wt qsec vs am gear carb new_column_name
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 TRUE
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 TRUE
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 TRUE
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 TRUE
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 FALSE
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1 TRUE
I was able to do that with this code:
dataf2 <- dataf %>%
add_column(newcol = ifelse(dataf$var3=="value1" | dataf$var3=="value2", TRUE, FALSE) )
When I create a new variable, is there a way to specify in the function where to place it?
Right now, it adds it to the end of the dataframe, but for ease of viewing in Excel for example, I'd like to place a new calculated column beside the columns I used for the calculation.
Here's an example of code:
rawdata2 <- (rawdata1 %>% unite(location, locations1,locations2, locations3,
na.rm = TRUE, remove=TRUE)
%>% select(-location7, -location16)
%>% unite(Sector, Sectors, na.rm=TRUE, remove=TRUE)
%>% unite(TypeofSpace, TypesofSpace, type.of.spaceOther, na.rm=TRUE,
remove=TRUE)
)
You can rearrange the columns in your data frame. It looks like you are using dplyr::select in your example.
library(dplyr)
head(mtcars)
# mpg cyl disp hp drat wt qsec vs am gear carb
# Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
# Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
# Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
# Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
# Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
# Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
mtcars2 <- mtcars %>%
select(mpg, carb, everything()) ## moves carb up behind mpg
head(mtcars2)
# mpg carb cyl disp hp drat wt qsec vs am gear
# Mazda RX4 21.0 4 6 160 110 3.90 2.620 16.46 0 1 4
# Mazda RX4 Wag 21.0 4 6 160 110 3.90 2.875 17.02 0 1 4
# Datsun 710 22.8 1 4 108 93 3.85 2.320 18.61 1 1 4
# Hornet 4 Drive 21.4 1 6 258 110 3.08 3.215 19.44 1 0 3
# Hornet Sportabout 18.7 2 8 360 175 3.15 3.440 17.02 0 0 3
# Valiant 18.1 1 6 225 105 2.76 3.460 20.22 1 0 3
You can do the same thing with base subsetting, for example with a data frame with 11 columns you can move the 11th behind the second by
mtcars3 <- mtcars[,c(1,11,2:10)]
identical(mtcars2, mtcars3)
# [1] TRUE
I ended up using relocate, documentation here: dplyr.tidyverse.org/reference/relocate.html
I am learning the for loop in R. I am trying to figure it out how to make a for loop in an specific variable in data.frame. I looked into several example in stackoverflow such as Q1, Q2, Q3 but none is useful of what I am looking for!
As an example using the mtcars dataset , let say I want to perform a for loop to:
look into the cyl and define for cyl 4,6,8, write and substitute with strings (low, medium, high), respectively.
for (i in mtcars$cyl) {
if (mtcars$cyl == 4){
print("low")}
if (mtcars$cyl == 6) {
print ("medium")}
if (mtcars$cyl == 8) {
print ("high")}
}
Certainly this is not the case!
what expected is something like this:
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
convert to:
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 medium 160 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 medium 160 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 low 108 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 medium 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 high 360 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 medium 225 105 2.76 3.460 20.22 1 0 3 1
Any help with explanation is highly appreciated!
This particular operation would be possible without loop.
df = mtcars
df$cyl[df$cyl == 4] = "low" #Subset the cyl values equal to 4 and assign 'low'
#Repeat for other values
But for running loop, I would go about like this
df = mtcars
for (i in 1:length(df$cyl)) { #Iterate over the length of df$cyl
#You could also do "for (i in seq_along(df$cyl)"
#Run "seq_along(df$cyl)" and "1:length(df$cyl)" to understand what values are being generated
if (df$cyl[i] == 4){ #Index df$cyl by [i]. If the ith value is 4, assign 'low'
df$cyl[i] = "low"
}
if (df$cyl[i] == 6) {
df$cyl[i] = "medium"
}
if (df$cyl[i] == 8) {
df$cyl[i] = "high"
}
}