Informatics Practices
Consider the same Series object, S, given in the previous question. What output will be produced by following code fragment ?
S.index = ['AMZN', 'AAPL', 'MSFT', 'GOOG']
print(S)
print(S['AMZN'])
S['AMZN'] = 1.5
print(S['AMZN'])
print(S)
Python Pandas
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Answer
AMZN 0.430271
AAPL 0.617328
MSFT -0.265421
GOOG -0.836113
dtype: float64
0.430271
1.5
AMZN 1.500000
AAPL 0.617328
MSFT -0.265421
GOOG -0.836113
dtype: float64
Working
The provided code fragment first changes the index labels of the Series S to ['AMZN', 'AAPL', 'MSFT', 'GOOG'], prints the modified Series S, and then proceeds to print and modify the value corresponding to the 'AMZN' index. Specifically, it prints the value at the 'AMZN' index before and after assigning a new value of 1.5 to that index. Finally, it prints the Series S again, showing the updated value at the 'AMZN' index.
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Consider following Series object namely S :
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(a) S * 100
(b) S > 0
(c) S1 = pd.Series(S)
(d) S2 = pd.Series(S1) + 3
What will be the values of Series objects S1 and S2 created above ?
What will be the output produced by the following code ?
Stationery = ['pencils', 'notebooks', 'scales', 'erasers'] S = pd.Series([20, 33, 52, 10], index = Stationery) S2 = pd.Series([17, 13, 31, 32], index = Stationery) print(S + S2) S = S + S2 print(S + S2)What will be the output produced by following code, considering the Series object S given above ?
(a) print(S[1:1])
(b) print(S[0:1])
(c) print(S[0:2])
(d)
S[0:2] = 12 print(S)(e)
print(S.index) print(S.values)