Data Engineering with Python

Q1. Which of the following methods is used for transforming a SparseSeries indexed by a MultiIndex to a scipy.sparse.coo_matrix ?

SparseSeries.to_coo()
Series.to_coo()
SparseSeries.to_cooser()
None of the above

Q2. Which of the following makes use of pandas and returns data in a Series or DataFrame ?

freedapi
OutPy
pandaSDMX
None of the above

Q3. Which of the following plots are used to check if a data set or time series is random?

Random
Lead
Lag
None of the above

Q4. Which of the following is implemented on DataFrame to compute the correlation between like-labeled Series contained in different DataFrame objects?

None of the above
corwith
corrwith
corwit

Q5. Which of the following library is similar to Pandas ?

NumPy
OutPy
RPy
None of the above

Q6. Which of the following works analogously to the form of the dict constructor ?

DataFrame.from_dict
All of the above
DataFrame.from_items
DataFrame.from_records

Q7. Which of the following is prominent python “statistics and econometrics library” ?

Bokeh
Statsmodel
Seaborn
Image

Q8. Which of the following methods produces a data ranking with ties being assigned the mean of the ranks for the group?

partition_rank
dense_rank
All of the above
rank

Q9. Which of the following takes a dict of dicts or a dict of array-like sequences and returns a DataFrame?

DataFrame.from_items
All of the above
DataFrame.from_records
DataFrame.from_dict

Q10. Which of the following is used to generate an index with time delta ?

None of the above
LeadIndex
TimeIndex
TimedeltaIndex

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