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I have a dataframe m and I want to remove all the rows where the f_name column has an entry greater than 3. I assume I can use something similar to

m <- m[-grep("nchar(m$f_name)>3", m$f_name]

To reword your question slightly, you want to retain rows where entries in f_name have length of 3 or less. So how about:

subset(m, nchar(as.character(f_name)) <= 3)

How to remove lines shorter than XY?, The following would remove lines that are 3 characters long or smaller: sed -n ' s/./&/4p' file. or awk 'gsub(/./,"&")>3' file. or awk 'length>3' file. or GNU awk: Use of "\v" means that in the pattern after it all ASCII characters except '0'-'9', 'a'-'z', 'A'-' Z' and '_' have a If a line does not contain 4 or more characters it is deleted. Adding all the table fields enables the delete query to remove entire records (rows) from the table. Optionally, you can enter criteria for one or more fields in the Criteria row of the designer, and then clear the Show check box for each criteria field. For more information about using criteria, see the Sample criteria for select queries table.

Try this:

m[!nchar(as.character(m$f_name)) > 3, ]

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The obligatory data.table solution:

setDT(m)
m[ nchar(f_name) <= 3 ]

Impala String Functions, All the functions that accept STRING arguments also accept the VARCHAR and Remove multiple spaces before and one space after. select concat('[',btrim(' hello ') When applied to a CHAR value, it might return a larger value than length() of multiple columns within the same row, while group_concat() joins together� It will delete the all rows for which column ‘Age’ has value 30. Delete rows based on multiple conditions on a column. Suppose Contents of dataframe object dfObj is, Original DataFrame pointed by dfObj. Let’s delete all rows for which column ‘Age’ has value between 30 to 40 i.e.

For those looking for a tidyverse approach, you can use dplyr::filter:

m %>% dplyr::filter(nchar(f_name) > 3)

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lapply: Apply a Function over a List or Vector, Simplification in sapply is only attempted if X has length greater than zero and if Otherwise an atomic vector or matrix or list of the same length as X (of length n for replicate ). VALUE) rows and length(X) columns, otherwise an array a with dim(a) apply , tapply , mapply for applying a function to multiple arguments, and� The following would remove lines that are 3 characters long or smaller: sed -r '/^.{,3}$/d' filename In order to save the changes to the file in-place, supply the -i option. If your version of sed doesn't support extended RE syntax, then you could write the same in BRE: sed '/^.\{,3\}$/d' filename which would work with all sed variants.

How To Use LEFT, RIGHT, MID, LEN, FIND And SEARCH Excel , Step #9: How To Use The CONCATENATE Function In Excel To Join All The As a consequence of this, if you delete all the rows that have blanks, you also delete specify a number of characters that is larger than the length of the text string,� There are instances where we have to select the rows from a Pandas dataframe by multiple conditions. Especially, when we are dealing with the text data then we may have requirements to select the rows matching a substring in all columns or select the rows based on the condition derived by concatenating two column values and many other scenarios where you have to slice,split,search substring

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Comments
  • @Umesh Awasthi I'm not sure that edits that trivial are really necessary.
  • You need to reword the question. Judging by your code, you don't want to remove "all the rows where the f_name column has an entry greater than 3." You want to remove rows where the length of the string in f_name is greater than 3.
  • @joran: agree!! but if that will enhance the readability there is no harm in that :)
  • A reproducible data set would be helpful for sure here.
  • @UmeshAwasthi My point, actually, was that slightly indenting the only line of code in the entire question does not, in fact, enhance its readability, and that edits that trivial are generally considered a nuisance, rather than helpful.
  • @hadely That got me in a code I was debugging today. +1 for a warning to a sneaky problem.
  • or wrap the conditional in isTRUE to eliminate NAs