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Tidytable Alternatives
Similar projects and alternatives to tidytable
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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Apache Arrow
Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better tidytable alternative or higher similarity.
tidytable reviews and mentions
Posts with mentions or reviews of tidytable.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-09.
- Tidyverse 2.0.0
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fuzzyjoin - "Error in which(m) : argument to 'which' is not logical"
If you need speed, you should consider using dtplyr (or tidytable), or even dbplyr with duckdb.
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tidytable v0.10.0 is now on CRAN - use tidyverse-like syntax with data.table speed
What do you think of this instead?
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Offering several functions to create the same object in my package
Here's an example - I use this in a package I've built called tidytable. Here is the as_tidytable() function I use that uses method dispatch.
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Dplyr performance issues (Late 2022)
If you're having performance issues with dplyr you can also try out tidytable
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R Dialects Broke Me
Iโd say tidytable is a better option these days as it supports more functions. Although I think dtplyr has improved on this front recently, but still lags. The author of tidytable contributes to dtplyr as well.
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Why is mlr3 so under-marketed?
I know you said it 'feels much faster' which isn't exactly a data oriented comparison, but tidymodels performs very well. You can see one of the dplyr functions as step_* in tidymodels, for example mutate vs. step_mutate under recipes library. The author of tidytable, which uses data.table, had some revisions due to this conversation, just as an example.
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Why is {dplyr} so huge, and are there any alternatives or a {dplyr} 'lite' that I can use for the basic mutate, group_by, summarize, etc?
Tidytable is what you might be looking for: https://markfairbanks.github.io/tidytable/, this will require a bit of refactoring (e.g group-bys happen as arguments in summarise/mutate). You'll get data.table like speed in a very compact & complete package.
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Programming with R {dplyr}
People can also use tidytable and keep the same workflow they're already used to ๐
- tidytable v0.8.1 is on CRAN - it also comes with a new logo! Need data.table speed with tidyverse syntax? Check out tidytable.
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Stats
Basic tidytable repo stats
26
436
8.2
about 1 month ago
markfairbanks/tidytable is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of tidytable is R.
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