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1.3 KiB
1.3 KiB
- This question is validated if the outputted DataFrame's shape is
(1305, 5)
and ifmerged.head()
returns a similar table:
Open | Close | Close_Adjusted | |||
---|---|---|---|---|---|
(Timestamp('2021-01-01 00:00:00', freq='B'), 'AAPL') | 0.0991792 | -0.31603 | 0.634787 | -0.00159041 | 1.06053 |
(Timestamp('2021-01-01 00:00:00', freq='B'), 'FB') | -0.123753 | 1.00269 | 0.713264 | 0.0142127 | -0.487028 |
(Timestamp('2021-01-01 00:00:00', freq='B'), 'GE') | -1.37775 | -1.01504 | 1.2858 | 0.109835 | 0.04273 |
(Timestamp('2021-01-01 00:00:00', freq='B'), 'AMZN') | 1.06324 | 0.841241 | -0.799481 | -0.805677 | 0.511769 |
(Timestamp('2021-01-01 00:00:00', freq='B'), 'DAI') | -0.603453 | -2.06141 | -0.969064 | 1.49817 | 0.730055 |
One of the answers that returns the correct DataFrame is:
market_data.merge(alternative_data, how='left', left_index=True, right_index=True)
- This question is validated if the numbers that are missing in the DataFrame are equal to 0 and if
filled_df.sum().sum() == merged_df.sum().sum()
gives:True