In VisiData, a loader is a module which directs how VisiData structures and engages with a particular data source. These sources are currently supported.
On default, the file extension determines which loader is used. Unknown filetypes are loaded as Text sheets.
vd sample.tsv ps aux | vd
To force a particular loader, pass
-f with the filetype or format name.
vd -f sqlite bar.db ls -l | vd -f fixed
VisiData has an adapter for pandas. To load a file format which is supported by pandas, execute
vd -f pandas data.foo. This will call
vd -f pandas data.parquet
loads a parquet file. When using the pandas loader, the
.fileformat file extension is mandatory.
Note that if you are using Python v3.7, then you will need to manually install pandas >=0.23.2 (our requirements.txt file installs v0.19.2 as the last version compatible with 3.4).
@paulklemm has wonderfully developed a small
R package which bridges the gap between
R and VisiData.
rvisidata using devtools run:
from within the
Any data frame can then be opened by VisiData:
Please note, that this tool opens the data frame in readonly mode. Any changes made will be discarded.
For more more details, questions, and feedback, check out the rvisidata repository.
Multiple files can be passed as inputs through the commandline.
vd birdsdiet.tsv surveys.csv sunshinelist.html
Upon launching, the final dataset to load (in this case, sunshinelist.html) will be displayed on top.
To load files from within a VisiData session, press
o and enter a filepath.
Sto open the Sheets sheet.
Enterto jump to the sheet referenced in that current cursor row.
vd -b countries.fixed -o countries.tsv
Note: Not all filetypes which are supported as loaders are also supported as savers. See the manpage for the supported output formats.