Finding the 2nd Max value in R data table [closed] - r

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I have a data table that has a int column that is counting the iteration of a test that I've preformed. So the first time I preformed the test, Table$Column == 1 and the second time Table$Column == 2 and so on and so forth.
However, there are times when a test breaks or I don't want to use the results from a particular test run. I have code that compares the current run vs. the previous run that looks like this.
vLatest<-max(Table$Column)
vPrevious<-max(Table$Column)-1
But since I sometimes omit results, it breaks vPrevious. How could I replace the "-1" with a function that finds the "2nd" max value?

This should work:
vPrevious <- sort(Table$Column, decreasing=T)[2]
We first sort in descending order and then pick the second element.

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r function for counting specific row of 2 columns [closed]

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I need help how to compare 2 columns in r studio but only in the first 5 observations
code used first was
damgeByage<-table(test$Vehicle_Age,test$Vehicle_Damage)
damgeByage
which give me all 186 observation but only want the first 10 oobservation of both columns
I
We can subset the data with row index
table(test[1:10, c("Vehicle_Age", "Vehicle_Damage")])
akrun's answer works or you can also use:
table(test$Vehicle_Age[1:10],test$Vehicle_Damage[1:10])
the table is also subsettable if you just wanted the first 10 rows of the results:
damgeByage<-table(test$Vehicle_Age,test$Vehicle_Damage)
damgeByage[1:10,]

Specific variables calculation [closed]

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Hello,I have an issue.I have an excell and I want to calculate and to find Min. =0.000 etc..but I find Min. =1.700 etc. What am I doing wrong here?
I believe the problem is your inclusion of & grade as a term in your filter step.
What's going on is that R wants to interpret each of these terms (exam=="S1", year==2018, grade) as a logical value. When it converts grade to logical, 0 becomes FALSE and all other values become TRUE (try as.logical(-1:1) to see an example), so the zero values in your data get removed.
Just delete & grade from your code.

Adding my logs (values) to a dataframe in R [closed]

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Okay so I'm making logs of some distance variables
- example;
loghospital=log(hospital_2015_distance, base=exp(1))
Works, i get values that i can run in a regression.
However for my LASSO regression it's better i specify a dataset.
So i want a dataframe of these logs (values).
Or better I want these logs (values) added to my existing dataframe called (data).
Any idea how this can be achieved? And if not, what else i should do to achieve the same?
To add it to your data.frame you can use $:
data$loghospital = log(hospital_2015_distance, base=exp(1))
Also you could use [[ or [ and probably should <- instead of = for assignment:
# Examples:
data[["loghospital"]] <- log(hospital_2015_distance, base=exp(1))
data["loghospital"] <- log(hospital_2015_distance, base=exp(1))
data[, "loghospital"] <- log(hospital_2015_distance, base=exp(1))

Splitting a character into separate words in R [closed]

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I am working on a project in R (on TED_Talks data set). I have a data frame with one column called "tags" which contains a character like
"gaming,gender,sex,feminism,education,culture".
The problem is, the whole row is being read as a single character.
I want the output to be a vector containing separate words. eg:
"gaming","gender","sex","feminism","education","culture"
so I can do further analysis on tags.
You can simply do the following:
say your entry is in object a, and you want to allocate the final result to object b:
a <- "gaming,gender,sex,feminism,education,culture"
b <- unlist(strsplit(a, "[,]"))

Find duplicate registers in R [closed]

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I have an excel file with a list of emails and channels that collected it. How can I know how many emails per channel are duplicated using R and automate it (every time I import a different file just have to run it and get the results ) ?
Thank you!!
Assuming the "df" dataframe has the relevant variables under the names "channel" and "email", then:
To get the number of unique channel-email pairs:
dim(unique(df[c("channel", "email")]))[1]
To get the sum of all channel-email observations:
sum(table(df$channel, df$email))
To get the number of duplicates, simply subtract the former from the later:
sum(table(df$channel, df$email)) - dim(unique(df[c("channel", "email")]))[1]

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