将单元格条目粘贴到一个单元格中并删除空单元格答案

【问题标题】：Pasting cell entries into one cell and deleting empty cells将单元格条目粘贴到一个单元格中并删除空单元格
【发布时间】：2020-01-10 15:20:23
【问题描述】：

我有以下问题：我有一张有许多空单元格的表格。但第一列不包含空单元格。像这样：

structure(list(variable = c("variable", "Mean (M)", "Standard", 
"deviation", "(SD)", "1. Challenge"), M = c("M", "", "", "", 
"", "3.06"), SD = c("SD", "", "", "", "", "1.08"), X1 = c("1", 
"3.03", "1.09", "", "", ""), X2 = c("2", "2.19", "1.07", "", 
"", "â\210’0.06"), X3 = c("3", "1.93", "1.10", "", "", "0.52***"
), X4 = c("4", "1.86", "1.04", "", "", "â\210’0.14*")), row.names = c(NA, 
6L), class = "data.frame"))

How it looks like now

现在我想将标准（=“偏差”和“（SD）”）下的两个单元格的条目粘贴到单元格中，并删除这些仅包含空单元格的行。所以输出应该是这样的：

structure(list(variable = structure(c(2L, 3L, 1L), .Label = c("1. Challenge", 
"Mean (M)", "Standard deviation SD", "variable"), class = "factor"), 
    M = structure(c(1L, 1L, 2L), .Label = c("", "3.06", "M"), class = "factor"), 
    SD = structure(c(1L, 1L, 2L), .Label = c("", "1.08", "SD"
    ), class = "factor"), `1` = structure(c(4L, 3L, 1L), .Label = c("", 
    "1", "1.09", "3.03"), class = "factor"), `2` = structure(c(3L, 
    1L, 4L), .Label = c("1.07", "2", "2.19", "â\210’0.06"), class = "factor"), 
    `3` = structure(3:1, .Label = c("0.52***", "1.10", "1.93", 
    "3"), class = "factor"), `4` = structure(c(2L, 1L, 4L), .Label = c("1.04", 
    "1.86", "4", "â\210’0.14*"), class = "factor")), row.names = 2:4, class = "data.frame")

How I would like it to look like

你能帮忙吗？谢谢！

【问题讨论】：

您可以删除缺少数据的列，然后手动重命名该列。 df <- tidyr::drop_na(df, -variable); df[2,1] <- "Standard deviation SD".
但这无济于事，因为问题不是NA，而是空白单元格！我试过这个：no_blank_Table <-Tab[!(Tab$SD==""), ] 但后来我也丢失了前几行。我想删除仅包含空白单元格的行（忽略第一列）。有什么想法吗？
您可以使用 dplyr 轻松地将所有空白值转换为 NA：df <- mutate_all(df, ~ na_if(., ''))

标签： r cell paste

【解决方案1】：

一个选项是根据除第一列之外的所有列中出现的空白 ("") 创建一个分组列，然后当行数大于 1 时，每个列的元素 paste并获取distinct 行

library(dplyr)
library(stringr)
df1 %>% 
    group_by(grp = cumsum(rowSums(.[-1] == "") != ncol(.)-1))  %>%  
    mutate_at(vars(-group_cols()), ~ if(n() > 1) str_c(., collapse=" ") else .) %>%
    ungroup %>%
    type.convert(as.is = TRUE) %>%
    select(-grp) %>% 
    distinct

【讨论】：

太棒了！非常感谢！不知道这是否需要，但我简化了一下：
Table2 %>% group_by(grp = cumsum(rowSums(.[-1] == "") != ncol(.)-1)) %>% mutate_at(vars(-group_cols()), ~ if(n() > 1) str_c(., collapse=" ") else .) %>% unique(.) %>% .[-1, -10]
@Anne-KathrinKleine 谢谢。 type.convert 用于更改每列的类型（如果需要），unique 是类似于 distinct 的基础 R 来自 dplyr