![]() ![]() Convert the variable to a factor and add the labels Utrecht, New York, London, Singapore, Rome and Cape Town.ĭat3$V1 <- factor(dat3$V1, labels = c("Utrecht", "New York", "London", "Singapore", "Rome", "Capetown")) Imagine that the first variable V1 in our dataframe dat3 is not coded correctly, but actually represents grouping information about cities.One problem that often occurs is that categorical variables (factors in R) are not coded as such. If we, at a later stage, start analyzing our data without the correct measurement level, we may run into problems. Inspecting the structure of your data is vital, as you probably have imported your data from some other source. A useful function to inspect the structure of a dataframe is str(). This means that the column is indeed a factor (a categorical variable - as it is supposed to be). Note that R automatically reports the values the character column can take. With dataframes assigning names happens automatically. Try it.Ĭolumns can also be called by the $ sign, but only if a name has been assigned. For a vector there are no two dimensions and only one dimension can be called. The first number (before the comma) represents the row and the second number (after the comma) represents the column. Select 1) the third row, 2) the second column and 3) the intersection of these two in the dataframe dat3 that you have created in Question 4.I forced this to prove a point: You now know that there is a distinction between characters and factors and you know hot to force this conversion to factors in a data frame. Character vectors are not converted to factors in data frames by default, but the argument stringsAsFactors = TRUE has resulted in this conversion. Factors are categorical variables that are depicted by numbers. This is due to us not specifying the variable correctly in the matrix we used to create the dataframe. Rather tricky the function as.ame() has converted the first variable to a factor. As a matter of fact, it is also not a character variable. The first column in matrix dat3b obtained from Question 5 is indeed not numeric. Is.numeric(dat3) # TRUE is.numeric(dat3b) # FALSE Check if the first column in the data frames from Question 4 and Question 5 are indeed numeric.It may appear to be working, but if we check if column 1 is numerical, it turns out not to be the case. #VEC2 PACK CODE#But, be aware that the code dat3b <- as.ame(mat3, stringsAsFactors = TRUE)ĭoes not work properly (at least not as intended) as the matrix nature of mat3 turned everything into a character value and you have lost the numerical nature of vec1. At face value, everything may seem to be in order. Use function as.ame() on the matrix obtained from Question 4. Name the columns V1 and V2, respectively.
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