如何提取不具有在R / sparklyr一个DataSet中的任何空值的列名？

Question

我想只提取不具有作为R的大型数据集的空值的列名。

如果我的表有4列（ID，价格，产品，状态）的列价格和状态有几个空值和列ID和产品没有空值。然后，我想我作为输出：ID，产品

Answer 1

如果你需要一个确切的答案，你得先扫描完整数据集，计算遗漏值：

library(dplyr)

df <- copy_to(sc, tibble(
  id = 1:4,  Price = c(NA, 3.20, NA, 42),
  Product = c("p1", "p2", "p3", "p4"),
  Status = c(NA, "foo", "bar", NA)))

null_counts <- df %>% 
    summarise_all(funs(sum(as.numeric(is.na(.)), na.rm=TRUE))) %>% 
    collect() 

null_counts

# A tibble: 1 x 4
     id Price Product Status
  <dbl> <dbl>   <dbl>  <dbl>
1     0     2       0      2

确定哪些列已失踪数等于零：

cols_without_nulls <- null_counts %>% 
  select_if(funs(. == 0)) %>% 
  colnames()

cols_without_nulls

[1] "id"      "Product"

并使用这些选择

df %>% select(one_of(cols_without_nulls))

# Source: spark<?> [?? x 2]
     id Product
  <int> <chr>  
1     1 p1     
2     2 p2     
3     3 p3     
4     4 p4 

较短的变体的话：

df %>% select_if(funs(sum(as.numeric(is.na(.)), na.rm=TRUE) == 0))

Applying predicate on the first 100 rows
# Source: spark<?> [?? x 2]
     id Product
  <int> <chr>  
1     1 p1     
2     2 p2     
3     3 p3     
4     4 p4    

但是当你看到它只会采样数据。

Answer 2

data <- data.frame(ID = c(1,2,3,4),
                   Price = c(50, NA, 10, 20),
                   Product = c("A", "B", "C", "D"),
                   Status = c("Complete", NA, "Complete", "Incomplete"))

names(apply(data, 2, anyNA)[apply(data, 2, anyNA) == FALSE])