I work with a quite large table (50MB) which has a similar format to the following table:
I would like to manipulate the dataframe using pandas' stack
, unstack
, set_index
, pivot
, pivot_table
function or in any other idiomatic fashion, so I'll be able to plot all size
signals as function of time. For example, plotting the size
column at the different time points using parallel_coordinates
.
iteration weight count edge blobs days frame start time size
1 7 600 100 1000 0 0 0 0
1 7 600 100 1000 1 2 2 13.5
2 3 600 100 333 0 0 0 19.5
2 3 600 100 333 1 2 2 25.5
3 4 600 100 1000 0 0 0 22.5
3 4 600 100 1000 1 2 2 24
Then once I plot the individual signal as function of time, I want to average over the different iterations of the same physical condition (where weight, count, edge, blobs, days time
are the same).
EDIT:
I think that if I find an easy way to convert the original dataframe to this one, we will be able to plot all the size
vs. time
signals:
Or maybe something like that: