Filtering data in a dataframe based on criteria

Given a dataframe "dfrm" with the names of the cities in the 'city' column, the population in the "population" column and the average summer temperature in the "meanSummerT" column your request for the subset meeting those joint requirements would be met with any of these:

subset( dfrm, population < 1e6 & meanSummerT > 70)
dfrm[ which(dfrm$population < 1e6 & dfrm$meanSummerT > 70) , ]
dfrm[ which( dfrm[[ 'population' ]] < 1e6 & dfrm[[ 'meanSummerT' ]] > 70) , ]

If you wanted just the names of the cities meeting those joint criteria then these would work:

subset( dfrm, population < 1e6 & meanSummerT > 70 , city)
dfrm[ which(dfrm$population < 1e6 & dfrm$meanSummerT > 70) , "city" ]
dfrm[ which(dfrm[['population']] < 1e6 & dfrm[['meanSummerT']] > 70) , "city" ]

Note that the column names are not quoted in the subset or following the "$" operator but they are quoted inside "[[". And note that using which can be dangerous if no lines of data match because instead of getting no lines you will get the entire dataframe.

You are looking for subset

if your data is called mydata

newdata <- subset(mydata, city < 1e6)

Or you could use [, which is programatically safer

newdata <- mydata[mydata$city < 1e6]

For more than one condition use & or | where approriate

You could also use the sqldf package to use sql

library(sqldf)

newdata <-  sqldf('select * from mydata where city > 1e6')

Or you could use data.table which makes the syntax easier for [ (as well as being memory efficient)

library(data.table)

mydatatable <- data.table(mydata)
newdata <- mydatatable[city > 1e6]