Filter rows based on values of multiple columns in R

Question

Here is the data set, say name is DS.

       Abc    Def   Ghi
1      41     190   67
2      36     118   72
3      12     149   74
4      18     313   62
5      NA      NA   56
6      28      NA   66
7      23     299   65
8      19      99   59
9       8      19   61
10     NA     194   69

How to get a new dataset DSS where value of column Abc is greater than 25, and value of column Def is greater than 100.It should also ignore any row if value of atleast one column in NA.

I have tried few options but wasn't successful. Your help is appreciated.

na.omit(DS[with(DS, Abc > 20 & Def > 100), ])

David Arenburg
– David Arenburg

2015-01-15 11:58:26 +00:00
Commented Jan 15, 2015 at 11:58 — David Arenburg
– David Arenburg, Commented Jan 15, 2015 at 11:58

Manohar Swamynathan · Accepted Answer · 2015-01-15 18:40:01Z

3

There are multiple ways of doing it. I have given 5 methods, and the first 4 methods are faster than the subset function.

R Code:

# Method 1:
DS_Filtered <- na.omit(DS[(DS$Abc > 20 & DS$Def > 100), ]) 
# Method 2: which function also ignores NA
DS_Filtered <- DS[ which( DS$Abc > 20 & DS$Def > 100) , ]
# Method 3:
DS_Filtered <- na.omit(DS[(DS$Abc > 20) & (DS$Def >100), ])

# Method 4: using dplyr package
DS_Filtered <- filter(DS, DS$Abc > 20, DS$Def >100)
DS_Filtered <- DS %>% filter(DS$Abc > 20 & DS$Def >100)

# Method 5: Subset function by default ignores NA
DS_Filtered <- subset(DS, DS$Abc >20 & DS$Def > 100)

edited Jan 15, 2015 at 18:40

answered Jan 15, 2015 at 12:49

Manohar Swamynathan

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