bigrquery
An interface to Google's BigQuery from R. (by r-dbi)
DBI
A database interface (DBI) definition for communication between R and RDBMSs (by r-dbi)
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| bigrquery | DBI | |
|---|---|---|
| 2 | 1 | |
| 505 | 284 | |
| 0.4% | 1.4% | |
| 8.4 | 9.2 | |
| 9 days ago | 12 days ago | |
| R | R | |
| GNU General Public License v3.0 or later | GNU Lesser General Public License v3.0 only |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
bigrquery
Posts with mentions or reviews of bigrquery.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-09-16.
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Querying partitioned tables in BigQuery using bigrquery
Hadley claims
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How To Access And Query Your Google BigQuery Data Using Python And R
In this post, we see how to load Google BigQuery data using Python and R, followed by querying the data to get useful insights. We leverage the Google Cloud BigQuery library for connecting BigQuery Python, and the bigrquery library is used to do the same with R.
DBI
Posts with mentions or reviews of DBI.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-29.
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Personal project: I'm logging sensor data to Sqlite on a Raspberry Pi. I want to make some pretty visuals with R using the data, but unsure about my options for making the data accessible to R.
You can query the database directly from an R session. My preferred approach is to use the DBI package. I would also recommend using the dbplyr package to write dplyr-style data transformations instead of trying to do a bunch of SQL string formatting.
What are some alternatives?
When comparing bigrquery and DBI you can also consider the following projects:
BigQuery-Python - Simple Python client for interacting with Google BigQuery.
dbplyr - Database (DBI) backend for dplyr
rmarkdown - Dynamic Documents for R
tig_stack
ggplot2 - An implementation of the Grammar of Graphics in R
rudderstack-docs - Documentation repository for RudderStack - the Customer Data Platform for Developers.
ChineseNames - 🀄 Chinese Name Database (1930-2008).
koral - Postgres data mapping helpers for R