StockPrices


Data analysis Correlation Data aggregation Python Public New

Easy  

30min

You are given a list of stocks and their daily closing prices for a given period of time. Your task is to determine which pair of stocks had the most highly correlated daily percentage changes of closing prices.

DAY

GOOG

FB

MSFT

AAPL

1

742.66

108.40

55.40

106.00

2

738.40

107.92

54.63

104.66

3

738.22

109.64

54.98

104.87

4

741.16

112.22

55.88

105.69

5

739.98

109.57

54.12

104.22

6

747.28

113.82

59.16

110.16

7

746.22

114.03

58.14

109.84

8

741.80

112.24

55.97

108.86

9

745.33

114.68

61.20

110.14

10

741.29

112.92

57.14

107.66

11

742.83

113.28

56.62

108.08

12

750.50

115.40

59.25

109.90

Python 3.5.1
   

  •   Example case: TypeError: 'NoneType' object is not iterable:
  •   Medium case: File "stockpricestest.py", line 157, in random_test: TypeError
  •   Big case: File "stockpricestest.py", line 157, in random_test: TypeError