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* Add first iteration of custom context * Add sample data + improve plot * Change `head` to `show` with sorting and limit. Add "-x" to plot and dynamic update of completer * generate random time series for test csv * Make columns lower case. Check if date is in columns and convert to timestamp. Improve plotting for dates * Add qa to custom * Add pred to custom * Hugooooo * Testing * dang whitespace Co-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com> Co-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt>
1.2 KiB
Vendored
1.2 KiB
Vendored
usage: plot [-y {colnorm,col2,colnorm3,colb}] [-x {colnorm,col2,colnorm3,colb}] [-k {line,scatter,bar,barh,hist,box,kde,area,pie,hexbin}] [-h] [--export {png,jpg,pdf,svg}]
Plot 2 columns of loaded data.
optional arguments:
-y {colnorm,col2,colnorm3,colb}
Variable to plot along y (default: None)
-x {colnorm,col2,colnorm3,colb}, --vs {colnorm,col2,colnorm3,colb}
Variable along x axis (default: )
-k {line,scatter,bar,barh,hist,box,kde,area,pie,hexbin}, --kind {line,scatter,bar,barh,hist,box,kde,area,pie,hexbin}
Type of plot for data (default: scatter)
-h, --help show this help message (default: False)
--export {png,jpg,pdf,svg}
Export figure into png, jpg, pdf, svg (default: )
Note that when no "-x/--vs" is supplied, the x axis will be the dataframe index. The -x and -y defaults will be the
columns present in your data. In this scenario, the columns loaded are colnorm,col2,colnorm3,colb .
The different kinds of plots can be seen in the kind kwarg of the
pandas plot function