How to square-form a dataframe with pair index

I have a JSON data like:

a={('A', 'B'): 0.8333333333333334, ('A', 'C'): 0.5, ('B', 'C'): 0.625}

I need to draw a heatmap based on that data set. but the dataframe I obtained by

df=pd.DataFrame(a,index=['value']).T.reset_index()

is like:

and this seems can not be used to draw a heat map. And the result dataframe should be looked like this:

df=pd.DataFrame({'A':{'A':1,'B':0.83333,'C':0.5},'B':{'A':0.83333,'B':1,'C':0.625},'C':{'A':0.5,'B':0.625,'C':1}})

>Solution :

Assuming:

a = {('A', 'B'): 0.8333333333333334, ('A', 'C'): 0.5, ('B', 'C'): 0.625}

you can convert to Series and unstack to get a DataFrame:

df = pd.Series(a).unstack()

output:

          B      C
A  0.833333  0.500
B       NaN  0.625

but this gives only single combinations. If you want both ways, combine_first with the transpose (T):

df = df.combine_first(df.T).fillna(1)

output:

          A         B      C
A  1.000000  0.833333  0.500
B  0.833333  1.000000  0.625
C  0.500000  0.625000  1.000

For your heatmap, you can use seaborn.heatmap:

import seaborn as sns
sns.heatmap(df)

output: