R 替换数据帧的非零值

我有一个数据框，看起来像下面的示例数据

> dput(df)
structure(list(BranchCode = structure(c(9L, 3L, 2L, 1L, 10L, 
6L, 8L, 11L, 4L, 5L, 7L), .Label = c("BU", "CA", "GT", "IN", 
"LM", "OX", "QC", "SR", "TD", "WG", "YV"), class = "factor"), 
    Requirement = c(0L, 5L, 12L, 1L, 0L, 0L, 6L, 0L, 3L, 10L, 
    0L), Availabile = c(3L, 3L, 0L, 7L, 0L, 8L, 0L, 0L, 7L, 3L, 
    6L), Alternative = c(9L, 0L, 0L, 0L, 10L, 2L, 3L, 8L, 0L, 
    0L, 5L), Complex = c(3L, 2L, 7L, 5L, 0L, 0L, 7L, 2L, 0L, 
    6L, 3L), Level1 = c(0L, 6L, 0L, 0L, 6L, 0L, 9L, 0L, 0L, 0L, 
    0L), Level2 = c(4L, 0L, 0L, 8L, 1L, 6L, 10L, 18L, 0L, 3L, 
    5L)), .Names = c("BranchCode", "Requirement", "Availabile", 
"Alternative", "Complex", "Level1", "Level2"), class = "data.frame", row.names = c(NA, 
-11L))

我需要用数字1替换所有非零值。我可以用两种方法来做到这一点

一次使用一列替换，如下所示。那我每次都得换列名

df$Requirement[df$Requirement！=0]您可以

df[-1] <- as.integer(df[-1] != 0)
df
#   BranchCode Requirement Availabile Alternative Complex Level1 Level2
#1          TD           0          1           1       1      0      1
#2          GT           1          1           0       1      1      0
#3          CA           1          0           0       1      0      0
#4          BU           0          1           0       1      0      1
#5          WG           0          0           1       0      1      0
#6          OX           0          1           1       0      0      1
#7          SR           1          0           1       1      1      1
#8          YV           0          0           1       1      0      1
#9          IN           1          1           0       0      0      0
#10         LM           1          1           0       1      0      1
#11         QC           0          1           1       1      0      1

numeric_cols <- vapply(df, is.numeric, logical(1))
df[numeric_cols] <- as.integer(df[numeric_cols] != 0)
df

df[-1]
df1[-1]=1
获取
TRUE
（1）

在

+

前面加上前缀将类型转换为整数

---

只是先前答案的补充

df[-1] <- as.numeric(df[-1] != 0)
df[-1] <- as.numeric(df[-1] != 0, as.logical)
df[-1] <- as.numeric(as.logical(df[-1] != 0))

---

df[-1]
df[df！=0]@sotos，感谢您花时间调查此事。你的建议很好，但它将所有其他非数字列变成了
NA
。除了从原始df复制相应的列之外，我还需要做其他任何处理吗？哇，真不敢相信只有一行代码就解决了我的问题。它为我创造了奇迹。非常感谢。很好的解决方案。感谢您的时间和解决方案。
numeric_cols <- vapply(df, is.numeric, logical(1))
df[numeric_cols] <- as.integer(df[numeric_cols] != 0)
df

df1[-1] <- + sapply(df1[-1], as.logical)

#   BranchCode Requirement Availabile Alternative Complex Level1 Level2
#1          TD           0          1           1       1      0      1
#2          GT           1          1           0       1      1      0
#3          CA           1          0           0       1      0      0
#4          BU           1          1           0       1      0      1
#5          WG           0          0           1       0      1      1
#6          OX           0          1           1       0      0      1
#7          SR           1          0           1       1      1      1
#8          YV           0          0           1       1      0      1
#9          IN           1          1           0       0      0      0
#10         LM           1          1           0       1      0      1
#11         QC           0          1           1       1      0      1

df[-1] <- as.numeric(df[-1] != 0)
df[-1] <- as.numeric(df[-1] != 0, as.logical)
df[-1] <- as.numeric(as.logical(df[-1] != 0))