Pandas DataFrame | 24/100 Days of Python Algo Trading

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Day 24: Pandas DataFrame 

1. How can you create a Pandas Series from a Python list?

A) pd.Series(list)

B) pd.Data(list)

C) pd.List(list)

D) pd.Array(list)

2. What method would you use to calculate the cumulative sum of a Series?

A) Series.cumsum()

B) Series.cumulative_sum()

C) Series.total()

D) Series.sum_all()

3. Which Pandas method is used for boolean indexing on a Series?

A) Series[Series > value]

B) Series.index([True, False, ...])

C) Series.filter([True, False, ...])

D) Series[Series > value]

4. How do you plot a graph of a Series in Pandas?

A) Series.plot()

B) Series.draw()

C) Series.graph()

D) Series.show()

5. Which method would you use to replace all occurrences of a value in a Series?

A) Series.replace(old, new)

B) Series.swap(old, new)

C) Series.change(old, new)

D) Series.update(old, new)

6. What does the Series.idxmax() method return?

A) The index of the first occurrence of the maximum value in the Series

B) The maximum value in the Series

C) The indexes of all maximum values in the Series

D) A boolean Series indicating the maximum value

7. Which Series method is used to apply a function to each element in the Series?

A) Series.apply(function)

B) Series.map(function)

C) Series.call(function)

D) Both A and B

8. How can you convert a Series to a Python list?

A) Series.tolist()

B) Series.to_list()

C) list(Series)

D) Both B and C

9. What is the use of the Series.sort_values() method?

A) To arrange the Series elements in a specified order

B) To count the number of unique values in the Series

C) To add all the values in the Series

D) To plot the Series values in ascending order

10. What does the Series.drop_duplicates() method do?

A) Removes duplicate elements from the Series

B) Deletes the Series

C) Identifies duplicates in the Series

D) None of the above

11. Which function allows combining two Series element-wise with a custom function?

A) Series.combine(another_series, function)

B) Series.merge(another_series, function)

C) Series.join(another_series, function)

D) Series.connect(another_series, function)

12. How do you slice a Series from index 3 to index 6?

A) Series[3:7]

B) Series[3, 6]

C) Series[3:6]

D) Series.slice(3, 6)

13. Which method is not an actual Pandas Series method?

A) Series.delete()

B) Series.dropna()

C) Series.fillna()

D) Series.isnull()

14. What happens when you use the Series.astype(dtype) method?

A) It converts the Series to a specified data type

B) It checks the type of each element in the Series

C) It casts a Series to a specified Python type

D) It returns the type information of the Series

15. How can you aggregate data in a Series using a custom function?

A) Series.aggregate(custom_function)

B) Series.agg(custom_function)

C) Series.reduce(custom_function)

D) Both A and B

16. What method would you use to return items in Series A that are not in Series B?

A) Series.A.difference(Series.B)

B) Series.A.notin(Series.B)

C) Series.A.except(Series.B)

D) Series.A.isin(Series.B)

17. How do you ensure that no data is lost when merging two Series of different lengths?

A) Using Series.combine_first()

B) Using Series.concat()

C) Using Series.join()

D) Using Series.merge()

18. What method would be used to compute the correlation between two Series?

A) Series.corr()

B) Series.correlation()

C) Series.correlate()

D) Series.compute()

19. How can you access the first element of a Series?

A) Series[0]

B) Series.first()

C) Series.head(1)

D) All of the above

20. Which method can you use to quickly find the number of non-NA/null observations in a Series?

A) Series.count()

B) Series.sum()

C) Series.total()

D) Series.number()

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