On 9/18/2022 9:44 PM, Rui Barradas wrote:
Hello,
I cannot reproduce the error.
Anyway, if the data is discrete a bar plot might be more appropriate.
barplot(table(x),
col = "green",
main = "Bar plot of Binomial Distribution B(20,0.4)")
Or, to have proportions,
barplot(table
Hello,
I cannot reproduce the error.
Anyway, if the data is discrete a bar plot might be more appropriate.
barplot(table(x),
col = "green",
main = "Bar plot of Binomial Distribution B(20,0.4)")
Or, to have proportions,
barplot(table(x)/length(x), etc)
Hope this helps,
Rui
Dear friends,
Hope you are doing great.
I first generated random deviates from a binomial distribution with the
following code (I had to generate from a B(20,0.4) dist):
#Setting seed
set.seed(1234567)
#Generating 1000 random deviates from a B(20,0.4) Distribution
x <- rbinom(1000,20,0.4)
#Gener
Adding to what Nick said, extra lines like those described often are in some
comment format like beginning with "#" or some consistent characters that can
be filtered out using comment.char='#' for example in read.csv() or
comment="string" in the tidyverse function read_csv().
And, of course yo
Helo,
Unfortunatelly there are many files with a non tabular data section
followed by the data. R's read.table has a skip argument:
skip
integer: the number of lines of the data file to skip before beginning
to read data.
If you do not know how many lines to skip because it's not always
Use the skip parameter if the number of header lines is always the same.
On September 18, 2022 12:39:50 PM PDT, Nick Wray wrote:
>Hello - I am having to download lots of rainfall and temperature data in
>csv form from the UK Met Office. The data isn't a problem - it's in nice
>columns and can be
Can you provide a sample of say the first 3 rows then the last 2 rows
before the CSV starts.
Are there always the same number of lines at the top? Or can it vary
depending what non-sense the Met Office decided to contaminate it with?
This should be solvable with some sample data.
Base R or Tidyv
Hello - I am having to download lots of rainfall and temperature data in
csv form from the UK Met Office. The data isn't a problem - it's in nice
columns and can be read into R easily - the problem is that in each csv
there are 60 or so lines of information first which are not part of the
columnar
If you want to delete row 18 you can do
mydf <- mydf[-18,]
This selects all rows other than row 18, and all columns and 'saves' it
back to the original data frame. Many people prefer to allocate to a new
dataframe so that if the -18 is wrong they can simply fix things.
I wasn't sure if you knew
>From the file? Or the data frame once its loaded?
What format is the file? CSV?
Do you know the line that needs deleted?
mydf <- read.csv("myfile.csv")
mydf2 <- mydf[-columnName == "valuetodelete", ]
# Note the - infront of column name
# or perhaps columnName != "value to delete", ]
write.csv
I’ve been retired since ‘06 and have forgotten most of R. Now I have a use for
it. I’ve created a data file and need to delete one row from it. How do I do
that?
DFP (iPad)
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You shouldn't use use r-squared in the context of glm, in fact it's not
possible. But if you need try calculating pseudo r-squared values
From: R-help on behalf of Rolf Turner
Sent: Saturday, September 17, 2022 12:29:56 AM
To: Kayla Bazzana
Cc: R-help@r-project
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