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Jan 24th, 2019
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  1. import pandas as pd
  2. import numpy as np
  3.  
  4. class StockPrices:
  5. def most_corr(prices):
  6. return None
  7.  
  8. #For example, with the parameters below the function should return ['FB', 'MSFT'].
  9. prices = {
  10. 'GOOG' : [
  11. 742.66, 738.40, 738.22, 741.16,
  12. 739.98, 747.28, 746.22, 741.80,
  13. 745.33, 741.29, 742.83, 750.50
  14. ],
  15. 'FB' : [
  16. 108.40, 107.92, 109.64, 112.22,
  17. 109.57, 113.82, 114.03, 112.24,
  18. 114.68, 112.92, 113.28, 115.40
  19. ],
  20. 'MSFT' : [
  21. 55.40, 54.63, 54.98, 55.88,
  22. 54.12, 59.16, 58.14, 55.97,
  23. 61.20, 57.14, 56.62, 59.25
  24. ],
  25. 'AAPL' : [
  26. 106.00, 104.66, 104.87, 105.69,
  27. 104.22, 110.16, 109.84, 108.86,
  28. 110.14, 107.66, 108.08, 109.90
  29. ]
  30. }
  31.  
  32. print(Max StockPrices.most_corr(prices))
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