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I like to create some sampling effort curves for species data. Where are several study areas with a number of sampling plots, resampled over a certain time period. My data set looks similar to this one:

In my dataframe CORtrial I have two columns, rDate in POSixct format which goes from 2015-07-27 17:45:00 until 2017-08-31 16:55:00 and REFN630 in numeric format. A value of REFN630 is recorded in rDate in a time interval of 5 in 5 minutes.

That's the structure of my dataframe:

I have traffic density (number of cars) data of various segments of a road. I want to plot a contour map like in the attached figure in R.

This question follow-up of a previous question: how to find the maximum value of a column dataframe in a specific POSIXct time interval in r?

In my dataframe CORtrial I have two columns, rDate in POSixct format which goes from 2015-07-27 17:45:00 until 2017-08-31 16:55:00 and REFN630 in numeric format. A value of REFN630 is recorded in rDate in a time interval of 5 in 5 minutes.

That's the structure of my dataframe:

If I have a data frame with entries stamped with date/time on "POSIXct" "POSIXt" form (as shown in the example data) Is there a way to group by day/hour %>% summarize(sum) to obtain all the observations by day by hour or do I have to extract the day and time and create a new column for each and group by those?

The issue I am having is that when I use the second approach with multiple year data the plots group the month variables instead of showing a consecutive time series.

Thanks in advance

I am learning about text mining and rTweet and I am currently brainstorming on the easiest way to clean text obtained from tweets. I have been using the method recommended on this link to remove URLs, remove anything other than English letters or space, remove stopwords, remove extra whitespace, remove numbers, remove punctuations.

This method uses both gsub and tm_map() and I was wondering if it was possible to stream line the cleaning process using stringr to simply add them to a cleaning pipe line. I saw an answer in the site that recommended the following function but for some reason I am unable to run it.

So I have this dataset

This is the code I wrote :

This seems like it would be a simple thing to do, but I am stumped.

I was using tidyverse material as a guide: here

I have a list of recession time periods, and I want to create a data frame as an output that lists every date and whether or not that date is in a recession. I would like to keep the solution in dplyr format.

Here is a reproducible example