Yes this is not the best place, rather it should be better asked in
bioinformatics forums like biostar and bioconductor.
On Sat, Sep 21, 2019 at 11:08 AM Mohammadian
wrote:
> Hi!
>
> I dont know whether this is the best place to ask this question, however:
>
> Suppose I want to perform
Please All:
While as I said in my first post I am still not convinced that the OP was in
good faith to improve R and not a troll (yours to decide), I also don't think
attacking a person's research to counter a point that has nothing to do with
their research is what is wanted on this
(excerpts only)
> slavery being easily justified by the Bible while abolition is not is an
> experience.
> P.S. Do any R developers actually read this?
I've read one or two verses...
I also found this (by you):
https://www.ncbi.nlm.nih.gov/pubmed/20362542
Which uses embryonic stem cells.
I
You really need to address the responses to your previous posts on this topic.
[1][2] What happened when you tested those methods? In particular, what about
them was so ineffective that you are still here asking the same question? And
why are you starting new threads of conversation on the same
On 9/21/19 12:57 PM, Phillip Heinrich wrote:
Still putzing around trying to increment a count vector when the date changes.
Date count
1 2018-03-29 1
2 2018-03-29 1
3 2018-03-29 1
81 2018-03-30 1
82 2018-03-30 1
83 2018-03-30 1
165 2018-03-31 1
Still putzing around trying to increment a count vector when the date changes.
Date count
1 2018-03-29 1
2 2018-03-29 1
3 2018-03-29 1
81 2018-03-30 1
82 2018-03-30 1
83 2018-03-30 1
165 2018-03-31 1
166 2018-03-31 1
167 2018-03-31 1
I can
On 21/09/2019 9:05 a.m., Jeff Newmiller wrote:
Your use of subset instead of select does not help,
Whoops, sorry. Thanks for doing the real check.
Duncan
but a corrected example does indeed confirm your point.
library(dplyr)
str(data.frame(a=c(1,1,2,2), b=1:4) %>% select(b,a))
##
Your use of subset instead of select does not help, but a corrected example
does indeed confirm your point.
library(dplyr)
str(data.frame(a=c(1,1,2,2), b=1:4) %>% select(b,a))
## 'data.frame':4 obs. of 2 variables:
## $ b: int 1 2 3 4
## $ a: num 1 1 2 2
However the `[` issue is still
On 21/09/2019 7:38 a.m., Jeff Newmiller wrote:
The dplyr::select function returns a special variety of data.frame called a tibble.
I don't think that's always true. The docs say it returns "An object of
the same class as .data.", and that's what I'm seeing:
> str(data.frame(a=c(1,1,2,2),
The dplyr::select function returns a special variety of data.frame called a
tibble. The tibble has certain features designed to make it behave consistently
when indexing is used. Specifically, the `[` operator always returns a tibble
regardless of how many columns are indicated by the column
Hi Phillip,
While I really like Ana's solution, this might also help:
phdf<-read.table(text="Date count
2018-03-29 1
2018-03-29 1
2018-03-29 1
2018-03-30 1
2018-03-30 1
2018-03-30 1
2018-03-31 1
2018-03-31 1
2018-03-31 1",
Thank for the prompt response.
On 9/21/19, ঋষি ( ऋषि / rIsHi ) wrote:
> Yes this is not the best place, rather it should be better asked in
> bioinformatics forums like biostar and bioconductor.
>
> On Sat, Sep 21, 2019 at 11:08 AM Mohammadian
> wrote:
>
>> Hi!
>>
>> I dont know whether this
Hi!
I dont know whether this is the best place to ask this question, however:
Suppose I want to perform meta-analysis on 10 different microarray studies.
Study Tissue-source
Study1 Neuron
Study2 Blood
Study3 Neuron and PBMC
..
Study10 ...
How should I treat Study3?
The R
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