Better Looking Universal Matplotlib Engine.
Blume provides a replacement for the matplotlib table module.
Displaying data as tables in matplotlib.
It fixes a number of issues with the existing table and has:
- more reliable code for automatically setting the font size to make best use of the space available.
- Padding between text and the cell edges which works better across a range of text sizes.
- First row of cell data is now row 0 regardless of whether the table has a row header. The row header is row -1.
- New options to allow cell edge colours to be specified.
To use the new table, just import blume.table and use that to create your tables instead of the matplotlib.table.table.
from blume import table tab = table(ax, ..)
The first parameter to table should be an matplotlib.axes.
If you are using the pyplot interface, note that calling pyplot.table will use matplotlib.table.table.
Instead import table from blume and use as follows:
from blume.table import table tab = table(plt.gca(), ...)
And lots more
The general theme is how to create generic tools to explore tables of data, visualising the data with matplotlib.
Tools that also help with managing open data.
For small datasets, there is an evolving example of working with simple csv files, stored in a git repository. See blume.examples.ocixx.
From source code
Get the latest code:
git clone http://github.com/swfiua/blume
python setup.py install
pip3 install blume
The blume/examples folder has a number of demonstrations of what can be done with this table.
You can run these with python3:
python3 -m blume.example.cpr
Or you can run a folder full of examples by using blume.eggshow.
The package will only require an appropriate version of matplotlib.
This is to make it easy for anyone who is only here for the table.
The U in blume.
This for now is the blume.cpr module.
Run tests using: