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I am an R novice and am having some challenges. I am dealing with a large dataframe which I have read from a csv file. My numerical vectors contain NAs which are stopping me from running analyses. How do I get rid of these NAs so I can actually do something with my data?
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omit() method is used to remove the NA values directly by resulting in the non-NA values and omitted NA values indexes. Return type: Returns the non-NA values. Returns the indexes of NA values which are removed from the vector.
To remove all rows having NA, we can use na. omit function. For Example, if we have a data frame called df that contains some NA values then we can remove all rows that contains at least one NA by using the command na. omit(df).
To remove observations with missing values in at least one column, you can use the na. omit() function. The na. omit() function in the R language inspects all columns from a data frame and drops rows that have NA's in one or more columns.
To replace NA with 0 in an R data frame, use is.na() function and then select all those values with NA and assign them to 0. myDataframe is the data frame in which you would like replace all NAs with 0.
x[!is.na(x)], or na.omit (see apropos("^na\\.") for all available na. functions),na.rm = TRUE
as an argument e.g. sapply(dtf, sd,
na.rm = TRUE),options(na.action = "na.omit")
which is set by default, but many
functions don't rely on globally
defined NA action (mean for
instance), while some do (right now I
cannot come up with an example),Long story short, dealing with NA's is a very broad problem, try to concretize it a bit and give us a concise question. I'm sure that someone of SOers can help you!
Cheers, lad!
84
na.omit(dataFrame)
This is an awesome website that I use for quick R related information: http://www.statmethods.net/input/missingdata.html
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