将某列中的非NA值替换为R中另一列中的值
我试图用City.y列中的值替换合并数据框City.x列中的值,只要City.y列中没有NA 换句话说,我想替换City.x列中除NA之外的所有值 以下是我目前掌握的代码:将某列中的非NA值替换为R中另一列中的值,r,dataframe,if-statement,na,mutate,R,Dataframe,If Statement,Na,Mutate,我试图用City.y列中的值替换合并数据框City.x列中的值,只要City.y列中没有NA 换句话说,我想替换City.x列中除NA之外的所有值 以下是我目前掌握的代码: library(tidyverse) library(dplyr) # Import food data food <- read_csv(file = 'https://s3.amazonaws.com/notredame.analytics.data/inspections.csv',
library(tidyverse)
library(dplyr)
# Import food data
food <-
read_csv(file = 'https://s3.amazonaws.com/notredame.analytics.data/inspections.csv',
col_names=c("ID",
"DBAName",
"AKAName",
"License",
"FacilityType",
"Risk",
"Address",
"City",
"State",
"ZIP",
"InspectionDate",
"InspectionType",
"Results",
"Violations",
"Latitude",
"Longitude",
"Location"),
col_types = "icccffcfffcffcddc",
skip = 1)
# Change InspectionDate from character type to datetime type
food$InspectionDate <- strptime(food$InspectionDate, "%m/%d/%Y")
#Import zipcode data
zipcode <-
read_csv('https://s3.amazonaws.com/notredame.analytics.data/zipcode.csv',
col_names = c("ZIP",
"City",
"State",
"Latitude",
"Longitude"),
skip = 1)
# Convert ZIP, City, and State from character type to factor type
zipcode$ZIP <- as.factor(zipcode$ZIP)
zipcode$City <- as.factor(zipcode$City)
zipcode$State <- as.factor(zipcode$State)
#Correct zip codes (told these were incorrect)
food <- food %>%
mutate(food$ZIP = ifelse("60627", "60827", ZIP))
#Create merged table from food and zipcode tables
mergedtable <- merge(x=food,y=zipcode,by="ZIP",all.x=TRUE)
#new_DF <- mergedtable[is.na(mergedtable$ZIP),]
mergedtable <- mergedtable %>%
mutate(mergedtable$City.x = ifelse(!is.na(mergedtable$City.y), mergedtable$City.y, mergedtable$City.x))
mergedtable$City.x <- ifelse(!is.na(mergedtable$City.y), mergedtable$City.y, mergedtable$City.x)
库(tidyverse)
图书馆(dplyr)
#进口食品数据
食物与结合会更容易
library(dplyr)
mergedtable2 <- mergedtable %>%
mutate(ZIP = coalesce(City.y, City.x))
同样地
food <- food %>%
mutate(ZIP = ifelse("60627", "60827", ZIP))
^^^
食品%
变异(ZIP=ifelse(“60627”,“60827”,ZIP))
^^^
mergedtable %>%
mutate(ZIP = ifelse(!is.na(City.y), City.y, City.x))
^^^
food <- food %>%
mutate(ZIP = ifelse("60627", "60827", ZIP))
^^^