How can I create correlation heatmaps of multiple users by 'Label' column. I want to compare all of them at once.
Would be helpful if I could filter values where (absolute) correlation is above 90%.
Index(['DATE', 'Creation_Date', 'Target_CPA', 'Site', 'Status', 'Label',
'Campaign_Name', 'Campaign_Query', 'COST', 'REVENUE', 'AdWords_Clicks',
'AdSense_Clicks', 'AdSense_IMPR', 'Adwords_IMPR', 'Conv', 'AdWords_CPC',
'AdSense_CPC'],
dtype='object')
Currently, I'm using this code by creating separate csv for each Label row value-
df.corr().unstack().sort_values(ascending=False).drop_duplicates()
Result:
Target_CPA Target_CPA 1.000000
AdWords_Clicks AdSense_IMPR 0.996090
Conv AdSense_Clicks 0.980790
COST AdWords_Clicks 0.963979
AdSense_IMPR COST 0.959211