I am trying to compare two Excel files (same number of columns, but sometimes different number of rows).
I imported the Excel files to data1 and data2 respectively.
library(dataCompareR)
comparedata <- rCompare(data1, data2)
summary(comparedata)
saveReport(comparedata, reportName = 'Comparison Result')
All goes well, but I have three challenges:
The Sample row data is set to 5. How can I increase that to the actual different row that the summery comes up with?
How can I ask the primary key in the result as it only shows the two matching columns?
Sometimes the numbers of the row don't match, and the data gets off. Can I set up a primary comparison key instead of row to row?
Related
I have a data table, where I would like to extract the rows that are equal in the different columns
what are the different functions to get there ?
I started programming in R yesterday (literally), and I am having the following issue:
-I have a data frame containing R rows, and each row contains N values.
Rows are identified by the first and second field, while the other N-2 are just numerical values or NA.
-Some rows have identical first field and identical second field, something like:
row 1: a,b, third_field, .. ,last_field
row 2: a,b, third_field, .. ,last_field
the rule is that usually the first line will have its fields containing some numbers and some NA, while the second row will contain NA and numbers as well, but differently distributed.
What I am trying to do is to merge the two rows (or records) according to these two rules:
1) if both rows have a NA on a given field, I keep NA
2) if one of the two has a number, I use that value; if both of the rows contain the same value, I keep it also.
How do you do this without looping on each field of each row? (1M rows, tenths of fields, it will finish maybe tomorrow).
I do not know how to better explain my problem. I am sorry for the lengthy explaination, thanks a lot.
EDIT: it is better if I add an example. The following two lines
a,b,NA,NA,NA,1,2 ,NA
a,b,NA,3 ,NA,1,NA,NA
should become
a,b,NA,3 ,NA,1,2 ,NA
I have a fairly large data set in csv format that I'd like to read into R. The data is annoyingly structured (my own fault) as follows:
,US912828LJ77,,US912810ED64,,US912828D804,...
17/08/2009,101.328125,15/08/1989,99.6171875,02/09/2014,99.7265625,...
And with the second line style repeated for a few thousand times. The structure is that each pair of columns represents a timeseries of differing lengths (so that the data is not rectangular).
If I use something like
>rawdata <- read.csv("filename.csv")
I get a dataframe with all the blank entries padded with NA, and the odd columns forced to a factor datatype.
What I'd like to ultimately get to is either a set of timeseries objects (for each pair of columns) named after every even entry in the first row (the "US912828LJ77" fields) or a single dataframe with row labels as dates running from the minimum of (min of each odd column) to max of (max of each odd column).
I can't imagine I'm the only mook to put together a dataset in such an unhelpful structure but I can't see any suggestions out there for how to deal with this. Any help would be greatly appreciated!
First you need to parse every odd column to date
odd.cols = names(rawdata)[seq(1,dim(rawdata)[2]-1,2)]
for(dateCol in odd.cols){
rawdata[[dateCol]] = as.Date(rawdata[[dateCol]], "%d/%m/%Y")
}
Now I guess the problem is straightforward, you just need to find min, max values per column, create a vector running from min date to max date, join it with rawdata and handle missing values for you US* columns.
I've done some thorough research and I am struggling with an attempt to find a function that will name the number of the row (in my data frame the rows don't contain numbers) that contains a certain value. In this case a number.
e.g. Call the data frame = df
I don't know how to show a little image of the data frame but say that in row 5, column 4 the value was '162', is there a function I could use that will end with the return being '5' or 'row 5'?
I have used rowsums(df=="162")
which gives a long line of the rows, if they contain the values there is a '1' under them, if not a '0' but I need a function that simply states the row.
I couldn't figure out how to correctly use the 'which' function either.
which(df$col4=='162')
I am assuming that col4 is the name of the column number 4
I need to extract the columns from a dataset without header names.
I have a ~10000 x 3 data set and I need to plot the first column against the second two.
I know how to do it when the columns have names ~ plot(data$V1, data$V2) but in this case they do not. How do I access each column individually when they do not have names?
Thanks
Why not give them sensible names?
names(data)=c("This","That","Other")
plot(data$This,data$That)
That's a better solution than using the column number, since names are meaningful and if your data changes to have a different number of columns your code may break in several places. Give your data the correct names and as long as you always refer to data$This then your code will work.
I usually select columns by their position in the matrix/data frame.
e.g.
dataset[,4] to select the 4th column.
The 1st number in brackets refers to rows, the second to columns. Here, I didn't use a "1st number" so all rows of column 4 are selected, i.e., the whole column.
This is easy to remember since it stems from matrix calculations. E.g., a 4x3 dimensional matrix has 4 rows and 3 columns. Thus when I want to select the 1st row of the third column, I could do something like matrix[1,3]