df_corr_sorted.py

import math

corr = df.corr()
corr_abs = corr.abs()
corr_tuples = []

# get highest corr for each col
for (i, col) in enumerate(corr_abs.columns):
    corr_with_col = corr_abs.iloc[:, i]\
        .sort_values(ascending=False)
    
    highest_corr = corr_with_col[1]
    if not math.isnan(highest_corr):
        col2 = corr_with_col.index[1]
        corr_tuples.append((col, col2, float(highest_corr)))    
        
# sort by corr
corr_tuples = sorted(corr_tuples, key=lambda x: x[2], reverse=True)

# remove duplicates
for i, tup in enumerate(corr_tuples):
    try:
        next_tup = corr_tuples[i + 1]    
        if next_tup[0] == tup[1] and next_tup[1] == tup[0]:
            corr_tuples.remove(tup)
    except IndexError:
        break