group-by

问题 Suppose we want to group_by() and summarise a massive data.frame with very many columns, but that there are some large groups of consecutive columns that will have the same summarise condition (e.g. max , mean etc) Is there a way to avoid having to specify the summarise condition for each and every column, and instead do it for ranges of columns ? Example Suppose we want to do this: iris %>% group_by(Species) %>% summarise(max(Sepal.Length), mean(Sepal.Width), mean(Petal.Length), mean(Petal

问题 Suppose we want to group_by() and summarise a massive data.frame with very many columns, but that there are some large groups of consecutive columns that will have the same summarise condition (e.g. max , mean etc) Is there a way to avoid having to specify the summarise condition for each and every column, and instead do it for ranges of columns ? Example Suppose we want to do this: iris %>% group_by(Species) %>% summarise(max(Sepal.Length), mean(Sepal.Width), mean(Petal.Length), mean(Petal

问题 I have a Linq query like this var results= StudentsList.GroupBy(x=> x.GroupID) .GroupBy(x=> x.Any(g=>g.IsQualified== true)) .Select(g=> g) .ToList(); I want to store the part x.Any(g=>g.IsQualified== true) into a variable so that I can change it on the fly (example: x.Any(g=>g.StudentName== "John") ) based on my requirement and without defining a new Linq query separately. Is that possible? Pseudo Code static void SomeFunction(Func<int, int> op) { var results= StudentsList.GroupBy(x=> x

问题 I am trying to run a gremlin query which groups vertices of a certain label into several groups by a certain field (assume it is 'displayName') and limit the number of groups to n and the number of items in each group also to n . Is there a way to achieve that? Since group().by() returns a list of the item, I tried using unfold() and then applying limit on the inner items. I managed to limit the number of groups that are returned, but couldn't limit the number of items in each group. Here's

问题 I am trying to run a gremlin query which groups vertices of a certain label into several groups by a certain field (assume it is 'displayName') and limit the number of groups to n and the number of items in each group also to n . Is there a way to achieve that? Since group().by() returns a list of the item, I tried using unfold() and then applying limit on the inner items. I managed to limit the number of groups that are returned, but couldn't limit the number of items in each group. Here's

问题 My question is simple, I have a dataframe and I groupby the results based on a column and get the size like this: df.groupby('column').size() Now the problem is that I only want the ones where size is greater than X . I am wondering if I can do it using a lambda function or anything similar? I have already tried this: df.groupby('column').size() > X and it prints out some True and False values. 回答1: The grouped result is a regular DataFrame, so just filter the results as usual: import pandas

问题 My question is simple, I have a dataframe and I groupby the results based on a column and get the size like this: df.groupby('column').size() Now the problem is that I only want the ones where size is greater than X . I am wondering if I can do it using a lambda function or anything similar? I have already tried this: df.groupby('column').size() > X and it prints out some True and False values. 回答1: The grouped result is a regular DataFrame, so just filter the results as usual: import pandas

问题 I have a pandas Dataframe df and I want to Group by text column with aggregation of: Stack the english_word and return the list Sum the count column Now I only can do either making the english_word list or sum the count column. I try to do that, but it return error. How to do both of that aggregation? In simple, what I want: text saya eat chicken english_word [eat,chicken] count 2 df.groupby('text', as_index=False).agg({'count' : lambda x: x.sum(), 'english_word' : lambda x: x.list()}) This

问题 I have a pandas Dataframe df and I want to Group by text column with aggregation of: Stack the english_word and return the list Sum the count column Now I only can do either making the english_word list or sum the count column. I try to do that, but it return error. How to do both of that aggregation? In simple, what I want: text saya eat chicken english_word [eat,chicken] count 2 df.groupby('text', as_index=False).agg({'count' : lambda x: x.sum(), 'english_word' : lambda x: x.list()}) This

问题 I have a pandas Dataframe df and I want to Group by text column with aggregation of: Stack the english_word and return the list Sum the count column Now I only can do either making the english_word list or sum the count column. I try to do that, but it return error. How to do both of that aggregation? In simple, what I want: text saya eat chicken english_word [eat,chicken] count 2 df.groupby('text', as_index=False).agg({'count' : lambda x: x.sum(), 'english_word' : lambda x: x.list()}) This