I like to create a table that has the frequency of several columns in my data frame. I am copying part of my data frame below. The table is supposed to have frequency (both n and %) of "red" in C...

Sep 7, 2014 · Pandas has a built-in function called value_counts(). Example: if your DataFrame has a column with values as 0's and 1's, and you want to count the total frequencies for each of them, then simply use this: df.colName.value_counts()

Aug 31, 2012 · I'm looking for a way to do simple aggregates / counts via data.table. Consider the iris data, which has 50 observations per species. To count the observations per species I have to summaries ove...

Sep 1, 2012 · Let say, I have a table named table with headers which looks like A B 1 2 2 1 What I want to do is adding a new column table$C such that if table$A < table$B then ...

A much more canonical answer can be found at the question linked about, now with the name Reshape three column data frame to matrix ("long" to "wide" format). In my opinion, it would have been better for this one to have been closed as a duplicate of that.

Feb 9, 2012 · Very simple option in case you have many individual columns to delete in a data table and you want to avoid typing in all column names #careadviced dt <- dt[, -c(1,4,6,17,83,104)]

Nov 11, 2015 · I currently have: Country.Name 1995 1996 1997 ... 2013 Country1 Country2 (numeric data) Country3 -This format makes it difficult to graph the data for each country, and compare them,

Sep 4, 2015 · Note: The sequence of piped results with janitor and tidyr has the benefit of being more transparent, but it essentially replicates the same result achieved with as.data.frame(table(df)).

I have a data frame with a number of infections identified from clinical isolates at different dates. So far I have organised the data into a shape that I want to start working with. I am trying to

Sep 3, 2013 · I have a simple table (age by marital status) for individuals in a range of geographical zones. I'd like to produce a table for each of these, would this be possible to do using a where statement,