New databraryr v0.6.3

A new version of databraryr is now available on CRAN.

This version supports “piping” of commands:

databraryr::list_volume_assets() |> 
  dplyr::filter(format_extension == "csv") |>
  databraryr::download_session_assets_fr_df()

[1] "9807/databrary-institutions-investigators.csv"
[2] "9807/volumes-citations-monthly.csv"           

These CSV files are from the default volume 1, session/slot 9807. By default, the files are saved in the local directory named with the session ID.

So, we can do the following:

inst_invest_df <- readr::read_csv("9807/databrary-institutions-investigators.csv",
                                  show_col_types = FALSE)

library(ggplot2)
inst_invest_df |>
  ggplot() +
  aes(x = Date, y = Institutions) +
  geom_point()

This is obviously an older version of the plot showing growth in the number of authorizing institutions. The current, more colorfully styled version is here:

https://databrary.github.io/analytics/include/img/fig-databrary-inst-invest-timeseries-1.png

Supporting piping had been on my to-do list, but I pushed it up the priority list on the request of some colleagues.

Note

In generating this post, I discovered that I had not generated an arm64 MacOS binary.

So, the standard workflow for installing the package on some Macs will not work.

In the meantime, devtoools::install_github("databrary/databrary") should work.

This will be fixed soon.

Coding is hard.