使用for()循环将数据处理应用于数据集的所有行

发布于01月07日

我有一个空的数据框

new_df<-structure(list(id = c("R_88j7lG37gLfxk22", "R_88j7lG37gLfxk22", 
"R_88j7lG37gLfxk22", "R_88j7lG37gLfxk22", "R_88j7lG37gLfxk22", 
"R_88j7lG37gLfxk22", "R_88j7lG37gLfxk22", "R_88j7lG37gLfxk22", 
"R_88j7lG37gLfxk22", "R_88j7lG37gLfxk22", "R_88j7lG37gLfxk22", 
"R_88j7lG37gLfxk22", "R_6DK8lERVf8lSQf4", "R_6DK8lERVf8lSQf4", 
"R_6DK8lERVf8lSQf4", "R_6DK8lERVf8lSQf4", "R_6DK8lERVf8lSQf4", 
"R_6DK8lERVf8lSQf4", "R_6DK8lERVf8lSQf4", "R_6DK8lERVf8lSQf4", 
"R_6DK8lERVf8lSQf4", "R_6DK8lERVf8lSQf4", "R_6DK8lERVf8lSQf4", 
"R_6DK8lERVf8lSQf4"), choice = c(0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 
1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1), low_env = c(NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA), mid_env = c(NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA), high_env = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), low_eth = c(NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA), mid_eth = c(NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA), high_eth = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), 
    `low_pri($25)` = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), 
    `mid_pri($75)` = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), 
    `high_pri($125)` = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
    )), row.names = c(NA, 24L), class = "data.frame")

使用上面的数据和代码，我根据long数据集的第一行填充了其中的一半.我如何使用for()循环才能将此方法应用于long数据集中将填充另一半的其余行？

long<-structure(list(id = c("R_88j7lG37gLfxk22", "R_6DK8lERVf8lSQf4"
), t1_choice = c("2", "3"), t2_choice = c("1", "3"), t3_choice = c("1", 
"2"), t4_choice = c("2", "1"), t1_p1_env = c("high_env", "mid_env"
), t1_p1_eth = c("low_eth", "mid_eth"), t1_p1_pri = c("$125", 
"$25"), t1_p2_env = c("mid_env", "high_env"), t1_p2_eth = c("high_eth", 
"low_eth"), t1_p2_pri = c("$25", "$75"), t1_p3_env = c("low_env", 
"low_env"), t1_p3_eth = c("mid_eth", "low_eth"), t1_p3_pri = c("$75", 
"$75"), t2_p1_env = c("high_env", "mid_env"), t2_p1_eth = c("low_eth", 
"high_eth"), t2_p1_pri = c("$75", "$125"), t2_p2_env = c("mid_env", 
"low_env"), t2_p2_eth = c("mid_eth", "low_eth"), t2_p2_pri = c("$125", 
"$75"), t2_p3_env = c("mid_env", "high_env"), t2_p3_eth = c("mid_eth", 
"high_eth"), t2_p3_pri = c("$75", "$75"), t3_p1_env = c("high_env", 
"mid_env"), t3_p1_eth = c("high_eth", "mid_eth"), t3_p1_pri = c("$125", 
"$125"), t3_p2_env = c("mid_env", "high_env"), t3_p2_eth = c("low_eth", 
"low_eth"), t3_p2_pri = c("$25", "$25"), t3_p3_env = c("low_env", 
"low_env"), t3_p3_eth = c("high_eth", "high_eth"), t3_p3_pri = c("$25", 
"$75"), t4_p1_env = c("low_env", "high_env"), t4_p1_eth = c("low_eth", 
"low_eth"), t4_p1_pri = c("$75", "$125"), t4_p2_env = c("high_env", 
"mid_env"), t4_p2_eth = c("mid_eth", "mid_eth"), t4_p2_pri = c("$125", 
"$25"), t4_p3_env = c("low_env", "low_env"), t4_p3_eth = c("high_eth", 
"mid_eth"), t4_p3_pri = c("$25", "$125")), row.names = c(NA, 
-2L), class = c("tbl_df", "tbl", "data.frame"))

#working
# Loop through the first three rows of new_df
for (i in 1:3) {
  # Extracting the required values from long1 for each row
  env <- long[1,][paste0("t1_p", i, "_env")][1]
  eth <- long[1,][paste0("t1_p", i, "_eth")][1]
  pri <- long[1,][paste0("t1_p", i, "_pri")][1]
  
  # Matching values from long[1,] to new_df columns in the corresponding row
  new_df[i, "low_env"] <- as.numeric(env == "low_env")
  new_df[i, "mid_env"] <- as.numeric(env == "mid_env")
  new_df[i, "high_env"] <- as.numeric(env == "high_env")
  new_df[i, "low_eth"] <- as.numeric(eth == "low_eth")
  new_df[i, "mid_eth"] <- as.numeric(eth == "mid_eth")
  new_df[i, "high_eth"] <- as.numeric(eth == "high_eth")
  new_df[i, "low_pri($25)"] <- as.numeric(pri == "$25")
  new_df[i, "mid_pri($75)"] <- as.numeric(pri == "$75")
  new_df[i, "high_pri($125)"] <- as.numeric(pri == "$125")
}

# Loop through the second three rows of new_df
for (i in 1:3) {
  # Extracting the required values from long[1,] for each row
  env <- long[1,][paste0("t2_p", i, "_env")][1]
  eth <- long[1,][paste0("t2_p", i, "_eth")][1]
  pri <- long[1,][paste0("t2_p", i, "_pri")][1]
  
  # Matching values from long[1,] to new_df columns in the corresponding row
  new_df[i + 3, "low_env"] <- as.numeric(env == "low_env")
  new_df[i + 3, "mid_env"] <- as.numeric(env == "mid_env")
  new_df[i + 3, "high_env"] <- as.numeric(env == "high_env")
  new_df[i + 3, "low_eth"] <- as.numeric(eth == "low_eth")
  new_df[i + 3, "mid_eth"] <- as.numeric(eth == "mid_eth")
  new_df[i + 3, "high_eth"] <- as.numeric(eth == "high_eth")
  new_df[i + 3, "low_pri($25)"] <- as.numeric(pri == "$25")
  new_df[i + 3, "mid_pri($75)"] <- as.numeric(pri == "$75")
  new_df[i + 3, "high_pri($125)"] <- as.numeric(pri == "$125")
  # Adjusting the choice column
  new_df[i + 3, "choice"] <- as.numeric(long[1,][paste0("t2_choice")][1] == i)
}
  # Loop through the second three rows of new_df
  for (i in 1:3) {
    # Extracting the required values from long[1,] for each row
    env <- long[1,][paste0("t3_p", i, "_env")][1]
    eth <- long[1,][paste0("t3_p", i, "_eth")][1]
    pri <- long[1,][paste0("t3_p", i, "_pri")][1]
    
    # Matching values from long[1,] to new_df columns in the corresponding row
    new_df[i + 6, "low_env"] <- as.numeric(env == "low_env")
    new_df[i + 6, "mid_env"] <- as.numeric(env == "mid_env")
    new_df[i + 6, "high_env"] <- as.numeric(env == "high_env")
    new_df[i + 6, "low_eth"] <- as.numeric(eth == "low_eth")
    new_df[i + 6, "mid_eth"] <- as.numeric(eth == "mid_eth")
    new_df[i + 6, "high_eth"] <- as.numeric(eth == "high_eth")
    new_df[i + 6, "low_pri($25)"] <- as.numeric(pri == "$25")
    new_df[i + 6, "mid_pri($75)"] <- as.numeric(pri == "$75")
    new_df[i + 6, "high_pri($125)"] <- as.numeric(pri == "$125")
    # Adjusting the choice column
    new_df[i + 6, "choice"] <- as.numeric(long[1,][paste0("t3_choice")][1] == i)
  }
for (i in 1:3) {
  # Extracting the required values from long[1,] for each row
  env <- long[1,][paste0("t4_p", i, "_env")][1]
  eth <- long[1,][paste0("t4_p", i, "_eth")][1]
  pri <- long[1,][paste0("t4_p", i, "_pri")][1]
  
  # Matching values from long[1,] to new_df columns in the corresponding row
  new_df[i + 9, "low_env"] <- as.numeric(env == "low_env")
  new_df[i + 9, "mid_env"] <- as.numeric(env == "mid_env")
  new_df[i + 9, "high_env"] <- as.numeric(env == "high_env")
  new_df[i + 9, "low_eth"] <- as.numeric(eth == "low_eth")
  new_df[i + 9, "mid_eth"] <- as.numeric(eth == "mid_eth")
  new_df[i + 9, "high_eth"] <- as.numeric(eth == "high_eth")
  new_df[i + 9, "low_pri($25)"] <- as.numeric(pri == "$25")
  new_df[i + 9, "mid_pri($75)"] <- as.numeric(pri == "$75")
  new_df[i + 9, "high_pri($125)"] <- as.numeric(pri == "$125")
  

  # Adjusting the choice column
  new_df[i + 9, "choice"] <- as.numeric(long[1,][paste0("t4_choice")][1] == i)
}

预期结果

使用for()循环将数据处理应用于数据集的所有行

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