Python for Data Analysis

1. Question 1
   • Performs standard division and returns a float
   • Calculates the remainder of a division
   • Performs floor division and returns an integer result
   • Raises a number to a power
2. Question 2
   • my_list = [1, 2, 3]
   • my_list = (1, 2, 3)
   • my_list = {1, 2, 3}
   • my_list = <1, 2, 3>
3. Question 3
   • IndexError: string index out of range
   • 'P'
   • 'n'
   • 'o'
4. Question 4
   • It returns None
   • It raises a NameError
   • It raises a SyntaxError
   • It automatically creates a new variable with a value of 0
5. Question 5
   • x == 5
   • x := 5
   • x -> 5
   • x = 5
6. Question 6
   • The number of elements in the list
   • The data type of the list
   • The memory size of the list in bytes
   • The index of the last element
7. Question 7
   • func my_func():
   • define my_func():
   • def my_func():
   • function my_func():
8. Question 8
   • Tuples can only contain numbers
   • Lists cannot be indexed
   • Lists are mutable, tuples are immutable
   • Lists are immutable, tuples are mutable
9. Question 9
   • [0, 1, 2, 3, 4]
   • [5, 6, 7, 8, 9, 10]
   • An error because range requires a single argument
   • [5, 6, 7, 8, 9]
10. Question 10
    • 2
    • KeyError
    • 4
    • 3
11. Question 11
    • {'Alice': 10, 'Bob': 8, 'Charlie': 7}
    • {'Alice': 10, 'Bob': 5, 'Charlie': 7}
    • Error: dictionary changed size during iteration
    • {'Alice': 10, 'Bob': 8}
12. Question 12
    • France
    • None
    • KeyError
    • True
13. Question 13
    • 150
    • 120
    • 90
    • 60
14. Question 14
    • 5
    • 3
    • 7
    • 2
15. Question 15
    • 4
    • KeyError
    • 3
    • 2
16. Question 16
    • Installs the pandas library
    • Reads a CSV file into a pandas DataFrame
    • Creates a new pandas DataFrame
    • Imports the pandas library and gives it the alias pd
17. Question 17
    • pd.open_csv()
    • pd.load_csv()
    • pd.read_csv()
    • pd.import_csv()
18. Question 18
    • df.tail(8)
    • df.head(8)
    • df.top(8)
    • df.first(8)
19. Question 19
    • df.details()
    • df.summary()
    • df.info()
    • df.describe()
20. Question 20
    • A list of all unique values in the DataFrame
    • The data type of each column in the DataFrame
    • The number of rows in the DataFrame
    • The shape of the DataFrame as a tuple
21. Question 21
    • df.export_excel()
    • df.save_excel()
    • df.to_excel()
    • df.write_excel()
22. Question 22
    • To measure the memory usage of the DataFrame
    • To delete the last few rows of the DataFrame
    • To display the first n rows of a DataFrame for inspection
    • To calculate summary statistics for all numeric columns
23. Question 23
    • int64
    • bool
    • object
    • float64
24. Question 24
    • df.columns
    • df.dtypes
    • df.index
    • df.shape
25. Question 25
    • missing_values='N/A'
    • na_values='N/A'
    • fillna='N/A'
    • null_values='N/A'
26. Question 26
    • Those columns contain missing values.
    • The data types of those columns are incorrect.
    • The DataFrame has duplicate rows.
    • The CSV file had inconsistent delimiters in those columns.
27. Question 27
    • df.info()
    • df.sample(5)
    • df.describe()
    • df.dtypes
28. Question 28
    • The index is saved as a separate column without a header.
    • The index is saved as a separate column with a header.
    • The index is saved as the first row of the file.
    • The index is not saved.
29. Question 29
    • A random sample of three rows from the end of the DataFrame.
    • The first three rows of the DataFrame.
    • The last three rows of the DataFrame.
    • The last three columns of the DataFrame.
30. Question 30
    • skiprows=1
    • header=None
    • no_header=True
    • names=False

Flashcards will appear here once they are ready.