问题描述
我正在使用 R。我得到了数据集中特定列的缺失值，我需要将它们添加到我的主数据中。
我的数据看起来像这样...
A B C D G
Joseph 5 2.1 6.0 7.8
Juan NA 3.0 3.5 3.8
Miguel 2 4.0 2.0 2.5
Steven NA 6.0 5.0 0.2
Jennifer NA 0.1 5.0 7.0
emma 8.0 8.1 8.3 8.5
所以，不，我有 B 列中缺失值的数据
A B
Juan 3.0
Steven 2.5
Jennifer 4.4
我需要将它们添加到我的主要数据中。我尝试使用 tidyverse 中的 coalesce 函数，但我无法得到正确的结果。
解决方法
一种选择可能是：
df %>%
mutate(B = if_else(is.na(B),df2$B[match(A,df2$A)],B))
A B C D G
1 Joseph 5.0 2.1 6.0 7.8
2 Juan 3.0 3.0 3.5 3.8
3 Miguel 2.0 4.0 2.0 2.5
4 Steven 2.5 6.0 5.0 0.2
5 Jennifer 4.4 0.1 5.0 7.0
6 Emma 8.0 8.1 8.3 8.5
这行得通吗：
df
# A tibble: 6 x 5
A B C D G
<chr> <dbl> <dbl> <dbl> <dbl>
1 Joseph 5 2.1 6 7.8
2 Juan NA 3 3.5 3.8
3 Miguel 2 4 2 2.5
4 Steven NA 6 5 0.2
5 Jennifer NA 0.1 5 7
6 Emma 8 8.1 8.3 8.5
dd
# A tibble: 3 x 2
A B
<chr> <dbl>
1 Juan 3
2 Steven 2.5
3 Jennifer 4.4
df$B[match(dd$A,df$A)] <- dd$B
df
# A tibble: 6 x 5
A B C D G
<chr> <dbl> <dbl> <dbl> <dbl>
1 Joseph 5 2.1 6 7.8
2 Juan 3 3 3.5 3.8
3 Miguel 2 4 2 2.5
4 Steven 2.5 6 5 0.2
5 Jennifer 4.4 0.1 5 7
6 Emma 8 8.1 8.3 8.5
您可以连接两个数据框并使用 # so useless registration system
# Registration Phase
name = input("Type a username: ")
password = input("Type a password: ")
confrim_password = input("Type your password again: ")
eMail = input("Type youe e-mail Adress: ")
# Password checking
# Reading the txt file
user_informations = []
with open("userInfo.txt","r") as file_info:
for line in file_info.readlines():
line = line.replace("\n","")
user_informations.append(line)
# storing informations to a list
result = f"{name} | {password} | {confrim_password} | {eMail}"
user_informations.append(result)
# storing informations to a txt file
with open("userInfo.txt","w+") as file_info:
for line in user_informations:
file_info.write(f"{line}\n")
# this is just for testing
print(user_informations)
作为 coalesce 值。
B或在基数 R 中：
library(dplyr)
df1 %>%
left_join(df2,by = 'A') %>%
mutate(B = coalesce(B.x,B.y)) %>%
select(names(df1))
# A B C D G
#1 Joseph 5.0 2.1 6.0 7.8
#2 Juan 3.0 3.0 3.5 3.8
#3 Miguel 2.0 4.0 2.0 2.5
#4 Steven 2.5 6.0 5.0 0.2
#5 Jennifer 4.4 0.1 5.0 7.0
#6 Emma 8.0 8.1 8.3 8.5
您可以连接数据，然后在 B 列上应用 NA 值的值。
# your original data with missing value in column B
data
# data that contain data to fill into column B
additional_data
library(dplyr)
merged_data <- left_join(data,additional_data,by = "A",suffix = c("","_additional"))
merged_data %>% mutate(B = if_else(is_na(B),B_additional,B)) %>%
select(-B_additional)