我的list-column
:
library(tidyverse)
dataset<-as_tibble(matrix(rnorm(6*30,1000,100),ncol=6))
cluster<-kmeans(dataset,centers=3)
dataset$kmeans<-as.factor(cluster[['cluster']])
mylist<-split(dataset,dataset$kmeans)
names(mylist)<-str_c('dataset',seq_along(mylist))
obj<-dataset%>%
group_by(kmeans)%>%
nest()
我尝试:
obj%>%
summarise_if(.data,is.numeric,sum)
错误:无法将列表转换为函数
和
obj%>%
map(~summarise_if(.data,is.numeric,sum))
UseMethod(“ tbl_vars”)中的错误: 没有适用于“ tbl_vars”的适用方法应用于“ rlang_data_pronoun”类的对象
在其他尝试中...
那么,如何将dplyr
函数应用到list-column
中呢?
答案 0 :(得分:0)
一种解决方案是在列表列(lbl = load_img(im)
lbl = scipy.misc.imresize(lbl, (self.image_shape[1], self.image_shape[0]))
bg_color = np.array([255, 255, 255])
building_color = np.array([255, 0, 0])
road_color = np.array([0, 0, 255])
gt_bg = np.all(lbl == bg_color, axis=2)
building_bg = np.all(lbl == building_color, axis=2)
road_bg = np.all(lbl == road_color, axis=2)
building_bg = gt_bg.reshape(*building_bg.shape, 1)
road_bg = gt_bg.reshape(*road_bg.shape, 1)
gt_bg = gt_bg.reshape(*gt_bg.shape, 1)
lbl = np.concatenate((gt_bg, building_bg, road_bg), axis=2)
return np.array([lbl])
)中使用dplyr::pull
:
obj$data