tibbletime | Time-aware tibbles | Time Series Database library

by business-science R Version: v0.1.7 License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | tibbletime Summary

tibbletime is a R library typically used in Database, Time Series Database applications. tibbletime has no bugs, it has no vulnerabilities and it has low support. However tibbletime has a Non-SPDX License. You can download it from GitHub.

Time-aware tibbles

Support

Quality

Security

License

Reuse

Support

tibbletime has a low active ecosystem.

It has 177 star(s) with 32 fork(s). There are 17 watchers for this library.

It had no major release in the last 12 months.

There are 5 open issues and 71 have been closed. On average issues are closed in 339 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of tibbletime is v0.1.7

Quality

tibbletime has no bugs reported.

Security

tibbletime has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

tibbletime has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

tibbletime releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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tibbletime Key Features

No Key Features are available at this moment for tibbletime.

tibbletime Examples and Code Snippets

No Code Snippets are available at this moment for tibbletime.

Community Discussions

Trending Discussions on tibbletime

data.table approach for creating a running sequential number for each row in a group

Filtering dates in R

How to filter rows based on a date range from the result of a specific column in a group

tibbletime with tq_transmute producing strange error, column obviously exists but says it doesn't

R: Tibble Conversions

Rolling sum within group boundaries

How to use group_by() to display earliest date

dplyr and tibbletime. Object is not of class 'til_time'. And general approach to time aggregation

Wrong visual plot representation of a correlation

R knitr's Build Code Appendix not working

QUESTION

data.table approach for creating a running sequential number for each row in a group

Asked 2021-May-08 at 17:15

I need to create a running sequential number for every row in a group. The groups are both the artist IDs and also the course number. The course number is also a sequential running number created based off of a very specific criteria: If an artist goes more than 7 days in between recording, a new course number is created.

For example, let's say that we have an artist_id whose data looks like this:

artist_id session_number_total CustomerRecordId SiteRecordId recording_date control_panel year 1 1 3 3 1/1/2000 Left 2000 1 2 3 3 1/3/2000 Right 2000 1 3 3 3 1/8/2000 Right 2000 1 4 3 3 5/1/2000 Left 2000

This artist_id came in for a session on 1/1/2000, 1/3/2000, 1/8/2000, and 5/1/2000. Based off of the aforementioned criteria for creating the course number groups (no more than 7 days in between recording dates) while also adding in the running count of the number of sessions for that artist, the final dataset should look like this:

artist_id session_number_total CustomerRecordId SiteRecordId recording_date control_panel year days_between Status course_number session_in_course 1 1 3 3 1/1/2000 Left 2000 0 Existing Course 1 1 1 2 3 3 1/3/2000 Right 2000 2 Existing Course 1 2 1 3 3 3 1/8/2000 Right 2000 5 Existing Course 1 3 1 4 3 3 5/1/2000 Left 2000 114 New Course 2 1

I am able to achieve this using some very convoluted code with dplyr. It works every time but the problem is that with 2.5 million rows in my dataset, the code can take 20-30 minutes to run each time I open a new session in R.

Considering how great data.table is for large sets of data, I'm wondering if anyone knows a data.table solution for creating the sequential group numbers and the running session count inside each of the groups based off of the criteria mentioned above? Any help would be appreciated so thank you in advance.

Here is a reproducible dataset and the code I used in dplyr to accomplish creating the final dataset:

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ANSWER

Answered 2021-May-08 at 17:15

How about this data.table solution:

Source https://stackoverflow.com/questions/67437952

QUESTION

Filtering dates in R

Asked 2021-Mar-25 at 02:01

I'm having issues with filtering my dataset into a specific date. I'm not sure how to upload the dataset on here but here is the link for it https://sexualitics.github.io . I'm trying to explore porn trends over the years focusing on 2007 first then 2008, 2009 etc. However, nothing has worked from what I have tried.

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ANSWER

Answered 2021-Mar-24 at 22:50

There are several places you can find out how to solve this.

One example: https://www.gormanalysis.com/blog/dates-and-times-in-r-without-losing-your-sanity/

But i understand you are new to R, and get stuck at small errors. I think your error is in formating the date. You need to help R to interpret the text.

Try this:

Source https://stackoverflow.com/questions/66789844

QUESTION

How to filter rows based on a date range from the result of a specific column in a group

Asked 2021-Mar-06 at 17:36

Problem

I have data in four columns (ID), The date a test was done (TestDT) a column with the numerical result of a test of interest (Test1) and another column with a numerical result of a different test of interest (Test2).

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ANSWER

Answered 2021-Mar-06 at 17:36

data.table has foverlaps function that merges two datasets on the date ranges.

You will need to split your data into test1 and test2 and do something like this:

Source https://stackoverflow.com/questions/66505421

QUESTION

tibbletime with tq_transmute producing strange error, column obviously exists but says it doesn't

Asked 2021-Jan-14 at 05:46

I could have sworn this code worked a week ago, but I guess that I am mistaken. I keep getting the error: Error: Can't subset columns that don't exist. x Column asset doesn't exist. Run rlang::last_error() to see where the error occurred. In addition: Warning message: ... must not be empty for ungrouped data frames. Did you want data = everything()?

I've taken it step by step to try and see where it is in my code and I can tell that it is after I group the assets, and occurs when I start to add on the tq_transmute. If someone could please help that would be greatly appreciated. I will have code that you should be able to just run automatically and see what I am talking about. It doesn't make any sense because "asset" does exist after gathering the data and grouping it.

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ANSWER

Answered 2021-Jan-14 at 05:46

gather has been replaced with pivot_longer and spread with pivot_wider. If you change gather code to pivot_longer it works. I am not exactly sure why it fails with gather though.

Source https://stackoverflow.com/questions/65713816

QUESTION

R: Tibble Conversions

Asked 2020-Dec-28 at 07:34

I am using the R programming language. I am following this tutorial over here: https://blogs.rstudio.com/ai/posts/2018-06-25-sunspots-lstm/

I am trying to prepare my data in the same way as this example over here:

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ANSWER

Answered 2020-Dec-28 at 07:34

Make your index column such that it can be converted to date object.

Source https://stackoverflow.com/questions/65473333

QUESTION

Rolling sum within group boundaries

Asked 2020-Nov-10 at 03:26

I'm trying to calculate a rolling sum based on the following toydata:

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ANSWER

Answered 2020-Nov-10 at 03:26

Here is an option using data.table::frollmean:

Source https://stackoverflow.com/questions/64758153

QUESTION

How to use group_by() to display earliest date

Asked 2020-Jul-15 at 20:57

I have a tibble called master_table that is 488 rows by 9 variables. The two relevant variables to the problem are wrestler_name and reign_begin. There are multiple repeats of certain wrestler_name values. I want to reduce the rows to only be one instance of each unique wrestler_name value, decided by the earliest reign_begin date value. Sample tibble is linked below:

So, in this slice of the tibble, the end goal would be to have just five rows instead of eleven, and the single Ric Flair row, for example, would have a reign_begin date of 9/17/1981, the earliest of the four Ric Flair reign_begin values.

I thought that group_by would make the most sense, but the more I think about it and try to use it, the more I think it might not be the right path. Here are some things I tried:

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ANSWER

Answered 2020-Jul-15 at 20:57

The common way to do this for databases involves a join:

Source https://stackoverflow.com/questions/62923035

QUESTION

dplyr and tibbletime. Object is not of class 'til_time'. And general approach to time aggregation

Asked 2020-Jun-14 at 15:22

I am new to packages dplyr and tibbletime and have the following objective. I need to sum the quantities of trades (qty in a dataset) that occur in the same interval of 24 hours. For instance, I have 3 trades within 1 hour with 300, 200 and 100 quantities respectively and I want them to be summed up to 600 and in the same fashion for all trades within one hour for the whole trading day. I tried the following:

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ANSWER

Answered 2020-Jun-14 at 15:22

I prefer to work directly with the dates itself using the lubridate package and then combine it with the rest of the tidyverse

Source https://stackoverflow.com/questions/62373635

QUESTION

Wrong visual plot representation of a correlation

Asked 2020-Mar-28 at 05:50

I built this code to check the correlation between Bitcoin and other altCoins, the table data is working fine, my only issue is when I try to plot the result to get a visual representation, I get the below result:

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ANSWER

Answered 2020-Mar-28 at 05:50

You need backticks around the variable name.

Source https://stackoverflow.com/questions/60897574

QUESTION

R knitr's Build Code Appendix not working

Asked 2020-Mar-21 at 20:17

I am trying to build a code appendix using the instructions from Yihui's site below:

https://bookdown.org/yihui/rmarkdown-cookbook/code-appendix.html

The issues is that I get no results, nothing happens when I preview the code in RStudio. One thing that I noticed is that code knitr::all_labels() returns NULL even though I have named all 30+ chunks in my Rnotebook. Also, I was able to build a external file with purl which is the last line. I tried to build a reprex with a basic starter Rnotebook, but the reprex didn't build in RStudio so I am going to paste what tried.

Thank you!

The Code...sorry, I had to remove the back ticks so that I could paste all the code chunks together.

...

ANSWER

Answered 2020-Mar-21 at 20:17

knitr::all_labels() returns NULL if it is not called in the full knitting process. When you run a single code chunk in the R Markdown Notebook, the document is not fully knitted.

To make knitr::all_labels() return all chunk labels, you should not use the notebook mode or preview the notebook, but knit the document instead (e.g., to the html_document output format).

Source https://stackoverflow.com/questions/60716003

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install tibbletime

The first thing to do is to turn your tibble into a tbl_time object. Notice the specification of the index as the date column of FB.
filter_time() - Succinctly filter a tbl_time object by date.
as_period() - Convert a tbl_time object from daily to monthly, from minute data to hourly, and more. This allows the user to easily aggregate data to a less granular level.
collapse_by() - Take an tbl_time object, and collapse the index so that all observations in an interval share the same date. The most common use of this is to then group on this column with dplyr::group_by() and perform time-based calculations with summarise(), mutate() or any other dplyr function.
collapse_index() - A lower level version of collapse_by() that directly modifies the index column and not the entire tbl_time object. It allows the user more flexibility when collapsing, like the ability to assign the resulting collapsed index to a new column.
rollify() - Modify a function so that it calculates a value (or a set of values) at specific time intervals. This can be used for rolling averages and other rolling calculations inside the tidyverse framework.
create_series() - Use shorthand notation to quickly initialize a tbl_time object containing a regularly spaced index column of class Date, POSIXct, yearmon, yearqtr or hms.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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