Calibrating dplyr filter depends on Sys.Date()

[oktayozden]

Hi all,
This is my code which filters tweets depends upon Sys.Date().
Problem in this code, after time passes 23:59 that is, new day stars. There will be no tweet or very limited tweets sended by people. So, filter does not give substantial result. My R shiny dashboard does not work.

Is it possible to run this code for example after 12:00? any suggestion?

Thank you all

tweetsday1<- tweetsday %>% dplyr::filter(tweetsday$date==(Sys.Date()))

[oktayozden]

I try to write if else command like below. However, it does not work. Could you possibly help me?

tweetsday<-todaysdata
tweetsday1<- tweetsday %>% dplyr::filter(tweetsday$date==(Sys.Date()))
row<-nrow(tweetsday1)
row<-as.numeric(row)

checknrow<-function(x) {
if (row <20) {tweetsday1<-tweetsday %>% dplyr::filter(tweetsday$date==(Sys.Date()-1))}
else {tweetsday1<-tweetsday %>% dplyr::filter(tweetsday$date==(Sys.Date()))}
}

checknrow(row)

[williaml]

Hi, can you provide a reproducible example of the dataset?

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[calleros]

When using dplyr::filter you don't need tweetsday$, you shoud write it like this:

tweetsday %>% dplyr::filter(date==(Sys.Date()))

[xvalda]

Hi @oktayozden
Best option would be to select the last 24 hours instead of working with days.
In my suggestion below, just replace tweets_df with the actual name of your dataframe, and harvested_date with the appropriate variable you have.
Things you may need to check:

1. make sure your date format is parsed correctly (you may need to adapt ymd_hms)
2. Check if any issue with time zones
3. make clear in your UI that you're displaying the last 24 hours

library(tidyverse); library(lubridate)

tweets_df %>% 
  filter(as.double(difftime(now(), ymd_hms(harvested_date), units = "hours")) < 24)

If you need further help, follow the advice of @williaml and share a reprex with code and some actual data.

[oktayozden]

Thats great! thanks xvalda