For each student (ie. ssid), find the average marks of the all courses taken. You are asked to have one average value for each student in the result. df2 % XXXX(sid) %>% XXXX(ave_grade = mean(grade, na.rm = TRUE)) Please fill in the blanks below. df2 % [Fill in the blank] (sid) %>% [Fill in the blank] (ave_grade = mean(grade, na.rm = TRUE))

Examining the task, we want to compute the average grade per student (sid) using a dplyr pipeline. The two blanks must chain operations so that we first group by sid, then compute the per-group average of grade. Option analysis for the first blank: - group_by: This is the correct function to establish the per-group computation by sid. By grouping by sid, subsequent operations (like mean) are performed within each student group. - summarise: If used as the first blank, summarise would attempt to collapse the data frame into one row per group, but it would not specify the grouping variable here. In the pipeline, you typically use group_by first and then summarise next; using summarise as the first step would be syntactically improper because there would be no grouping context yet. - summarize: This is an alternative spelling of summarise (American vs British variant). Using summarize here would be acceptable if used in the second blank after group_by, but as the first blank, the same issue as summarise applies: you need an input that has a grouping context, which is provided by group_by. Option analysis for the second blank: - group_by: Not valid in the second blank because after you group by sid, you want to reduce to a single summary per group, not re-group. Replacing the second blank with group_by would not make sense in the pipeline because you’d attempt to group again without performing a summarise, leading to an incomplete operation. - summarise: This is a correct choice for the second blank. It creates a data frame with one row per sid and a new column ave_grade containing the mean of grade within each group, which matches the objective of having one average per student. The exact spelling used in the second blank can be either summarise (British) or summarize (American); both are supported by dplyr as of common versions. - summarize: This is equally valid as the second blank, mirroring the rationale above. It accomplishes the same per-group calculation when used after an initial group_by. Putting it together, the canonical and idiomatic sequence is: df2 % group_by(sid) %>% summarise(ave_grade = mean(grade, na.rm = TRUE)) Alternatively, you could swap the second blank to summarize or summarize depending on your preferred spelling, as both are accepted by dplyr. The key points are: group_by(sid) first to define the groups, then a summarise/summarize with ave_grade = mean(grade, na.rm = TRUE) to produce one row per student with the average grade.

For each student (ie. ssid), find the average marks of the all courses taken. You are asked to have one average value for each student in the result. df2 <- student %>% XXXX(sid) %>% XXXX(ave_grade = mean(grade, na.rm = TRUE)) Please fill in the blanks below. df2 <- student %>% [Fill in the blank] (sid) %>% [Fill in the blank] (ave_grade = mean(grade, na.rm = TRUE)) 多项填空题

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df_c<- student %>% group_by(sid, year) %>% summarise(min_grade = min(grade), ave_min_grade = mean(min_grade)) df_d<- student %>% group_by(sid, year) %>% summarise(min_grade = min(grade)) %>% summarise(ave_min_grade = mean(min_grade)) Number of rows in df_c is different from that in df_d. There are 4 columns in df_c while there are 2 columns in df_d.

For each student (ie. `sid`), find the average marks of the all courses taken. You are asked to have one average value for each student in the result. df2 <- student %>% XXXX(sid) %>% XXXX(ave_grade = mean(grade, na.rm = TRUE)) Please fill in the blanks below. df2 <- student %>% [Fill in the blank] (sid) %>% [Fill in the blank] (ave_grade = mean(grade, na.rm = TRUE))

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