I have a correlation matrix (in the form of a DataFrame) from which I return a Series which is the top n correlated pairs of columns and the value of the correlation: See this for an example of what I mean. I take the resulting Series object and then cast as a dictionary like so: The resulting keys of this

Python Pandas Loop through Dictionary Keys (which are tuples) and plot variables against each other

I have a correlation matrix (in the form of a DataFrame) from which I return a Series which is the top n correlated pairs of columns and the value of the correlation:

HCT    HGB            0.928873
ALT    AST            0.920744
MCH    MCV            0.861742
bpsys  bpdia          0.846069
HCT    RBC            0.769507
HGB    RBC            0.697879
       gender_Male    0.690716
CL     SODIUM         0.688227
LYM    WBC            0.672971
RBC    gender_Male    0.663275
HCT    gender_Male    0.660515
MCH    MCHC           0.571524
age    HGB            0.512578
HGB    MCHC           0.506935
age    gender_Male    0.493219
dtype: float64

See this for an example of what I mean. I take the resulting Series object and then cast as a dictionary like so:

top_corrs = top_corrs.to_dict()

The resulting keys of this dictionary are tuples of the top n correlated variables, which I found by:

top_corrs.keys()

Resulting in 15 keys:

dict_keys([('HCT', 'HGB'), ('ALT', 'AST'), ('MCH', 'MCV'), ('bpsys', 'bpdia'), ('HCT', 'RBC'), ('HGB', 'RBC'), ('HGB', 'gender_Male'), ('CL', 'SODIUM'), ('LYM', 'WBC'), ('RBC', 'gender_Male'), ('HCT', 'gender_Male'), ('MCH', 'MCHC'), ('age', 'HGB'), ('HGB', 'MCHC'), ('age', 'gender_Male')])

Now, what I would like to do is go back to my original DataFrame from where I calculated the correlations and plot these tuples of columns against one another looping through the dictionary keys.

Kind of like this:

Key1 = (‘HCT’, ‘HGB’)

sns.lmplot(y = ‘HCT’  x=’HGB’, data= originaldata, hue=huevar, col=colvar, palette='Set1')

Key2 = (‘ALT’, ‘AST’)

sns.lmplot(y = ‘HCT’  x=’HGB’, data= originaldata, hue=huevar, col=colvar, palette='Set1')

In a sense I want to “unpack” (don’t know if I am using that word right) these tuples and plot them against each other?

Is this possible, or am I just trippin’?

Thanks in avbance

Answer

You can iterate over dictionary keys in a for loop and then subset each element within the tuple:

for key in top_corrs:    
    sns.lmplot(y = key[0],  x=key[1], data=originaldata, palette='Set1')

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Answer