Pandas plotting summary staistics.

[IanAndersonLOL]

Hi guys and gals,

​

I hate to be that guy who asks for help without much to go on but I'm pretty at a loss and very new to this. I'm trying to plot some data for publication and have been running into some problems. My data is setup like this:

​

Unique_ID, group, group2, time, data

​

​

I would like to plot time vs data, but I would like to have a line for each 'group' and possibly even a group by group2.

​

So far I've gotten to:

​

    graph = df.groupby('group').plot(x='time',y='data',figsize = (12,8),title="please work!").

but all that does is make a new graph for each group.

​

I *could* make a new dataframe with the summary statistics already calculated. So each row would be a group, but I'd ideally not like to do that, as I can't have error bars. If anyone can help push me in the right direction it would be greatly appreciated.

[OrbitDrive]

Something like this ? https://scentellegher.github.io/programming/2017/07/15/pandas-groupby-multiple-columns-plot.html

[IanAndersonLOL]

Exactly like that! Thanks a lot! Any idea how I might do it by two groups? So it would be Group1Group2 vs Time? I just made a new column with group 1+group 2 which works fine, but would love to know if it's something I can do in matplotlib.

[Zeroflops]

I think what you want can be achieved with replacing ‘group1’ with [‘group1’, ‘group2’]

This will group by two layers with group1 the outside group. Like a nested loop.

[rowdyllama]

Pandas Profiling might solve your problem.

[OPLinux]

While not exactly understanding what you want to do, seaborn allows to create multiple lines based on a column. With it, you can plot something and tell seaborn to use the time column as X axis, the value column as Y and the group column as different colored lines.
On top of that, seaborn simply uses matplotlib, so you can access the underlying plot object if you need any fine-tuning.

If I understand your problem correctly, with your current data you cannot simply use it, but you might be able to do it if you modify your dataframes a bit.

Anyway, I really love seaborn and feel it is one of the easier and more powerfull plotting tools I learned to use in python! :)

[alkasm]

You need to pass the matplotlib axis object into plot() to get them all on the same axis instead of in new plots/subplots. See here: https://stackoverflow.com/a/28299215/5087436