Suppose you had a dataset (assigned to df) with 10,000 observations and with a single numerical column called y. 6,995 observations for y are positive; 5 observations for y are NA; and the others are negative (i.e., less than 0). The code should allow you to change the value of y to NA if y is currently negative. If the value of y is currently positive or NA, it should remain unchanged. Some part of the code are redacted. df$y[   A   (df$y    B     )]   C     Complete the code by filling the blanks below.    A    : [Fill in the blank]    B    : [Fill in the blank]    C    : [Fill in the blank] 多项填空题

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类似问题

Suppose I have 1,000 simulation results of the sample sum of a chance event, stored under a variable called simulation_result Which of the following codes can I use to produce a cumulative table? The cumulative table should show the number of simulations that had a sample sum of at least a certain number. 

na is a vector of numeric elements. You do not know how many elements na has.  When you run the following, you are returned 1.  sum(is.na(na)) If you execute the following, what would be the output? sum(is.na(na[which(is.na(na))] + na)) ==length(na)

Dharma has vector w in her active R session. There are no missing values in w. That is, there is no NA’s in w. She executed the following code: sum(w) == sum(w[which(w)]) R returned (outputted) TRUE on her R console. TRUE/FALSE: w is not a logical vector.

Suppose you have a subset of our usual North American stock market data loaded into comp data frame with 80,200 observations with all 50 columns. You executed: comp %>% select(emp) %>%    summarise (ave_emp = mean(emp, na.rm = TRUE), number = sum(is.na(emp))) R gave the following output as a result:   ave_emp <dbl> number <int> 8.291884 10,200 Then, you run the following code. comp %>% select(emp) %>%     mutate(num = n()) %>% summarise(min_num = min(num)) The following output  was displayed. min_num <dbl> _{______________ What is the redacted value above?  

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