this works perfectly...
new_data5 <- new_data4[nchar(new_data4$date_abandoned) != 8, ]
...and i can now think of a few different ways to manipulate my data with
what ive learned from these tricks, thanks alot David!
David Winsemius wrote:
>
>
> On Nov 15, 2009, at 11:00 AM, frenchcr wrote
On Nov 15, 2009, at 11:00 AM, frenchcr wrote:
Yes they are not in date format, theyre just characters.
the earliest date is 1601 i originally had one of 0101 00 00
(101 years
BC)...this was a software problem.
table(nchar(new_data4$date_abandoned))
2 8
315732263
The
Yes they are not in date format, theyre just characters.
the earliest date is 1601 i originally had one of 0101 00 00 (101 years
BC)...this was a software problem.
> table(nchar(new_data4$date_abandoned))
2 8
315732263
The 315732 are empty fields i thought.
The 263 are da
On Nov 14, 2009, at 8:43 PM, frenchcr wrote:
sorry David,
im really new to R (my first week) and appreciate your help. Also I
dont
always know what info to give people on the forum (although im
starting to
catch the drift).
heres what i get...
summary(new_data4$date_abandoned)
Min.
sorry David,
im really new to R (my first week) and appreciate your help. Also I dont
always know what info to give people on the forum (although im starting to
catch the drift).
heres what i get...
summary(new_data4$date_abandoned)
Min.1st Qu.Median Mean 3rd Qu. Max.
On Nov 14, 2009, at 5:24 PM, frenchcr wrote:
I tried the following but it does the opposite of what i want:
new_data5 <- subset(new_data4, date_abandoned > "0101")
I want to remove the rows with dates and leave just the rows without
a date.
This removes all the rows that dont have a
I tried the following but it does the opposite of what i want:
new_data5 <- subset(new_data4, date_abandoned > "0101")
I want to remove the rows with dates and leave just the rows without a date.
This removes all the rows that dont have a date in the date_abandoned column
...on a positiv
On Nov 14, 2009, at 1:21 PM, frenchcr wrote:
I want to go through a column in data called
Bad name for a data.frame. Fortunes, "dog" and all that.
date_abandoneddata["date_abandoned"]and remove all the rows
that
have numbers greater than 1,010,000.
Are you doing archeology? Gi
I want to go through a column in data called
date_abandoneddata["date_abandoned"]and remove all the rows that
have numbers greater than 1,010,000.
The dates are in the format 20091114 so i'm just going to treat them as
numbers for clean up purposes.
I know that i use subset but not sur
9 matches
Mail list logo
