CODEWITHSUNDEEP
pythonmatplotlibpandas
Dimitris
Dimitris

Reputation: 435

pandas dataframe plot columns

After reading a series of files I create a dataframe with 7 columns:

<class 'pandas.core.frame.DataFrame'>
Int64Index: 756 entries, 0 to 755

Data columns:

Fr(Hz)        756  non-null values

res_ohm*m     756  non-null values

phase_mrad    756  non-null values

ImC_S/m       756  non-null values

Rm_S/m        756  non-null values

C_el          756  non-null values

date          756  non-null values

dtypes: float64(6), object(1)

then I want to group the date by column 6 (C_el) which has 12 variables:

Pairs = = data_set.groupby('C_el')

each group now contains data that are multiple of 21 (that means each 21 lines I have a new unique dataset) - 21 refers to the column 1 (Fr(Hz) where I am using 21 frequencies for each dataset

what I want to do is to create an x, y scattered plot - on X axis is column 1 (Fr(Hz), and on Y axis is column 3 (phase_mrad) - each dataset will have the 21 unique poits of frequency, and then I want to add all available datasets on the same plot, using different color

the final step, is to repeat this for the 11 remaining groups (as defined in an aearlier step)

sample datasets are here (A12) currently I do this very ugly in numpy multiple_datasets

Upvotes: 0

Views: 1167

Answers (1)

herrfz
herrfz

Reputation: 4894

I don't know if this will really satisfy your requirement, but I think groupby could do you a lot of favour. For instance, instead of the code example that you provided, you could instead do this:

for key, group in data_set.groupby('C_el'):
   # -- define the filename, path, etc..
   # e.g. filename = key
   group.to_csv(filename, sep=' ')

See also the documentation here. Sorry I can't help you out with more details, but I hope it helps to proceed somewhat.

Upvotes: 1

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