Subset of rows containing NA missing values in a chosen column of a data frame

Question

We have a data frame from a CSV file  The data frame DF has columns that contain observed values and a column  VaR2  that contains the date at which a measurement has been taken  If the date was not recorded  the CSV file contains the value NA  for missing data   Var1  Var2  10   2010 01 01 20   NA 30   2010 03 01   We would like to use the subset command to define a new data frame new DF such that it only contains rows that have an NA  value from the column  VaR2   In the example given  only Row 2 will be contained in the new DF   The command  new DF lt -subset DF DF Var2   NA      does not work  the resulting data frame has no row entries   If in the original CSV file the Value NA are exchanged with  NULL  the same command produces the desired result  new DF lt -subset DF DF Var2   NULL      How can I get this method working  if for the character string the value NA is provided in the original CSV file

User · Answer

Try changing this   new DF lt -dplyr  filter DF is na Var2

User · Answer

complete cases gives TRUE when all values in a row are not NA  DF  complete cases DF

User · Answer

Prints all the rows with NA data   tmp  lt - data frame c 1 2 3  c 4 NA 5    tmp round which is na tmp   ncol tmp

User · Answer

NA is a special value in R  do not mix up the NA value with the  NA  string  Depending on the way the data was imported  your  NA  and  NULL  cells may be of various type  the default behavior is to convert  NA  strings to NA values  and let  NULL  strings as is    If using read table   or read csv    you should consider the  na strings  argument to do clean data import  and always work with real R NA values   An example  working in both cases  NULL  and  NA  cells    DF  lt - read csv  file csv   na strings c  NA    NULL    new DF  lt - subset DF  is na DF Var2

User · Answer

new data  lt - data   gt   filter all any vars is na         This should create a new data frame  new data  with only the missing values in it    Works best to keep a track of values that you might later drop because they had some columns with missing observations  NA

User · Answer

Never use    NA  to test for missing values  Use is na   instead  This should do it   new DF  lt - DF rowSums is na DF    gt  0     or in case you want to check a particular column  you can also use  new DF  lt - DF is na DF Var      In case you have NA character values  first run  Df Df   NA    lt - NA   to replace them with missing values

[r] Subset of rows containing NA (missing) values in a chosen column of a data frame

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