road and hit
ggplot() to make graphs, factors may be useful in various kinds of fine
tuning.
-Original Message-
From: R-help On Behalf Of Rich Shepard
Sent: Tuesday, September 14, 2021 1:59 PM
To: r-help@r-project.org
Subject: Re: [R] Need fresh eyes to see what I'm missing
On Tue,
On Tue, 14 Sep 2021, Bert Gunter wrote:
**Don't do this.*** You will make errors. Use fit-for-purpose tools.
That's what R is for. Also, be careful **how** you "download", as that
already may bake in problems.
Bert,
Haven't had downloading errors saving displayed files.
The problem with the
Inline.
On Tue, Sep 14, 2021 at 10:42 AM Rich Shepard wrote:
>
> On Tue, 14 Sep 2021, Eric Berger wrote:
>
> > My suggestion was not 'to make a difference'. It was to determine whether
> > the NAs or NaNs appear before the dplyr commands. You confirmed that they
> > do. There are 2321 NAs in vel
On Tue, 14 Sep 2021, Bert Gunter wrote:
Input problems of this sort are often caused by stray or extra characters
(commas, dashes, etc.) in the input files, which then can trigger
automatic conversion to character. Excel files are somewhat notorious for
this.
Bert,
Large volume of missing dat
On Tue, 14 Sep 2021, Eric Berger wrote:
My suggestion was not 'to make a difference'. It was to determine whether
the NAs or NaNs appear before the dplyr commands. You confirmed that they
do. There are 2321 NAs in vel. Bert suggested some ways that an NA might
appear.
Eric,
Yes, you're all co
Hi Rich,
My suggestion was not 'to make a difference'. It was to determine
whether the NAs or NaNs appear before the dplyr commands. You
confirmed that they do. There are 2321 NAs in vel. Bert suggested some
ways that an NA might appear.
Best,
Eric
On Tue, Sep 14, 2021 at 6:42 PM Rich Shepard wr
On Tue, 14 Sep 2021, Bert Gunter wrote:
Input problems of this sort are often caused by stray or extra characters
(commas, dashes, etc.) in the input files, which then can trigger
automatic conversion to character. Excel files are somewhat notorious for
this.
Bert,
Yes, I'm going to closely r
Input problems of this sort are often caused by stray or extra
characters (commas, dashes, etc.) in the input files, which then can
trigger automatic conversion to character. Excel files are somewhat
notorious for this.
A couple of comments, and then I'll quit, as others should have
greater insigh
ve it again. That is
beyond the scope of this mailing list so if needed, ask me in private. You
have been working on this kind of stuff, but I assume often using other
tools outside R and dplyr.
-Original Message-
From: R-help On Behalf Of Rich Shepard
Sent: Tuesday, September 14, 2021 1
Rich Shepard
Sent: Tuesday, September 14, 2021 11:21 AM
To: r-help@r-project.org
Subject: [R] Need fresh eyes to see what I'm missing
The data file begins this way:
year,month,day,hour,min,fps
2016,03,03,12,00,1.74
2016,03,03,12,10,1.75
2016,03,03,12,20,1.76
2016,03,03,12,30,1.81
2016,03,03,
On Tue, 14 Sep 2021, Bert Gunter wrote:
Remove all your as.integer() and as.double() coercions. They are
unnecessary (unless you are preparing input for C code; also, all R
non-integers are double precision) and may be the source of your
problems.
Bert,
Are all columns but the fps factors?
R
On Tue, 14 Sep 2021, Bert Gunter wrote:
Remove all your as.integer() and as.double() coercions. They are
unnecessary (unless you are preparing input for C code; also, all R
non-integers are double precision) and may be the source of your problems.
Bert,
When I remove coercions the script prod
On Tue, 14 Sep 2021, Eric Berger wrote:
Before you create vel_by_month you can check vel for NAs and NaNs by
sum(is.na(vel))
sum(unlist(lapply(vel,is.nan)))
Eric,
There should not be any missing values in the data file. Regardless, I added
those lines to the script and it made no difference.
Remove all your as.integer() and as.double() coercions. They are
unnecessary (unless you are preparing input for C code; also, all R
non-integers are double precision) and may be the source of your
problems.
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and st
Before you create vel_by_month you can check vel for NAs and NaNs by
sum(is.na(vel))
sum(unlist(lapply(vel,is.nan)))
HTH,
Eric
On Tue, Sep 14, 2021 at 6:21 PM Rich Shepard
wrote:
> The data file begins this way:
> year,month,day,hour,min,fps
> 2016,03,03,12,00,1.74
> 2016,03,03,12,10,1.75
> 2
The data file begins this way:
year,month,day,hour,min,fps
2016,03,03,12,00,1.74
2016,03,03,12,10,1.75
2016,03,03,12,20,1.76
2016,03,03,12,30,1.81
2016,03,03,12,40,1.79
2016,03,03,12,50,1.75
2016,03,03,13,00,1.78
2016,03,03,13,10,1.81
The script to process it:
library('tidyverse')
vel <- read.csv
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