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Determine the number of NA values in a column
(17 answers)
Closed 2 years ago.
Here is the data that I am using :
https://www.dropbox.com/s/dl/chmzqmus6bfoaim/climate_clean.csv
I want to know how many observations of the variable average_temperature_celsius are missing
But I don't know how to do it, please could you help me
loaded your data in a variable called climate
sum(is.na(climate$average_temperature_celsius))
Related
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Make list of objects in global environment matching certain string pattern
(1 answer)
R: Put Variables from .GlobalEnv, that meet certain criteria in list
(2 answers)
Closed 3 months ago.
in python to parse all the variables that have a name ending for example with "_df"
I would use something similar to what I found here. How to do a similar thing in R?
Namely, I have several variables ending with _df and I have to do some actions to these.
Thanks
This question already has answers here:
How do I refer to multiple columns in a dataframe expression?
(1 answer)
When to use 'with' function and why is it good?
(2 answers)
Closed 1 year ago.
I'm writing code which subsets from a dataframe a lot e.g. lots of dataframe_name$column_name and it's a pain to read and to write. Is there a way to tell R that I'm referencing dataframe_name so that I can just write column_name for each instance?
This question already has answers here:
long/bigint/decimal equivalent datatype in R
(7 answers)
Closed 3 years ago.
I am assigning a large odd number to a variable (1126605209290117121) and it is being shown as (1126605209290117120) [observe the last digit] in the environment. But assigning a large even number is represented correctly. Can someone explain why?
a = 1126605209290117121
print(as.character(a))
[1] "1126605209290117120"
After searching through the internet I learned that R still has only 32-bit integers.
This blog post in R Bloggers summarises the problem clearly
This question already has answers here:
How to find common elements from multiple vectors?
(3 answers)
Closed 5 years ago.
I have two RNAseq read-outs for two groups and would like to compare them. These data appear as a gene and a value. I would like to determine which genes are shared between the two datasets but they are very large and doing this manually will take a long time. Thanks!
Use
intersect(genes1, genes2)
and look up the help page for other related and useful functions.
This question already has answers here:
Sort (order) data frame rows by multiple columns
(19 answers)
Closed 9 years ago.
Playing around with airquality, and I want to sort the data by Ozone and Wind (within wind)
I have the following command:
sort.airquality<-airquality[order(Ozone, Wind),]
sort.airquality[1:153,]
For some reason I just don't think this is right, I've tried looking up some of the tutorials but they don't seem to cover exactly what I'm looking for. Any help would be most appreciated.
Thanks.
For improved readability, I suggest
sort.airquality <- airquality[with(airquality, order(Ozone, Wind)),]
You want
sort.airquality <- airquality[order(airquality$Ozone, airquality$Wind),]