Untitled spreadsheet - Sheet1

Question 1

1. What function is used to check for missing values in a DataFrame?

Answer 1

df.isnull()

Question 2

2. What function is used to check for non-missing values in a DataFrame?

Answer 2

df.notnull()

Question 3

3. How to count the missing values in a DataFrame?

Answer 3

df.isnull().sum()

Question 4

4. How to get a total sum of all missing values in a DataFrame?

Answer 4

df.isnull().sum().sum()

Question 5

5. What function is used to remove rows with missing values?

Answer 5

df.dropna()

Question 6

6. What parameter should you use in dropna() to remove columns with missing values?

Answer 6

axis=1

Question 7

7. How to only drop rows where all columns are NaN?

Answer 7

df.dropna(how=’all’)

Question 8

8. What does df.dropna(thresh=n) do?

Answer 8

Drops rows that have less than n non-NaN values

Question 9

9. What does df.fillna(value) do?

Answer 9

It fills NaN values with a specified ‘value’

Question 10

10. How to fill missing values with the previous value in the DataFrame?

Answer 10

df.fillna(method=’ffill’)

Question 11

11. How to fill missing values with the next value in the DataFrame?

Answer 11

df.fillna(method=’bfill’)

Question 12

12. How to limit the amount of consecutive NaN filled with the ffill or bfill method?

Answer 12

df.fillna(method=’ffill’, limit=n)

Question 13

13. How to replace all NaN values with the mean of the DataFrame?

Answer 13

df.fillna(df.mean())

Question 14

14. How to replace all NaN values with the median of the DataFrame?

Answer 14

df.fillna(df.median())

Question 15

15. How to replace NaN in a specific column with the mean of that column?

Answer 15

df[‘column’].fillna(df[‘column’].mean())

Question 16

16. How to replace NaN in a specific column with the median of that column?

Answer 16

df[‘column’].fillna(df[‘column’].median())

Question 17

17. How to interpolate missing values?

Answer 17

df.interpolate()

Question 18

18. How to interpolate missing values with a limit?

Answer 18

df.interpolate(limit=n)

Question 19

19. What does df.interpolate(method=’polynomial’

Answer 19

order=2) do?

Question 20

20. How to replace NaN values with a specified value in a DataFrame?

Answer 20

df.fillna(value)

Question 21

21. How to replace various NaN values with different values?

Answer 21

df.fillna({‘column1’: value1, ‘column2’: value2})

Question 22

22. How to replace NaN values in a specific column with a specific value?

Answer 22

df[‘column’].fillna(value)

Question 23

23. How to use forward fill method for replacing NaN values in a specific column?

Answer 23

df[‘column’].fillna(method=’ffill’)

Question 24

24. How to use backward fill method for replacing NaN values in a specific column?

Answer 24

df[‘column’].fillna(method=’bfill’)

Question 25

25. What does interpolate method do with missing data?

Answer 25

Interpolate method uses various interpolation technique to guess the missing values from the other values in the DataFrame

Question 26

26. How to replace NaN values in a DataFrame with the mode?

Answer 26

df.fillna(df.mode().iloc[0])

Question 27

27. What does ‘inplace’ parameter do in fillna

Answer 27

dropna methods?

Question 28

28. How to drop the columns where any value is missing in a DataFrame?

Answer 28

df.dropna(axis=’columns’)

Question 29

29. How to drop the columns where all values are missing in a DataFrame?

Answer 29

df.dropna(how=’all’, axis=’columns’)

Question 30

30. How to keep the DataFrame with valid entries in the same variable?

Answer 30

df.dropna(inplace=True)

Question 31

31. How to replace NaN values in a DataFrame with zero?

Answer 31

df.fillna(0)

Question 32

32. How to drop rows where NaN appear in certain columns only?

Answer 32

df.dropna(subset=[‘column1’, ‘column2’])

Question 33

33. How to use pad method for replacing NaN values in DataFrame?

Answer 33

df.fillna(method=’pad’)

Question 34

34. How to replace missing values in a DataFrame with the value from the previous row or column?

Answer 34

df.fillna(method=’pad’)

Question 35

35. How to fill the missing values in a DataFrame with the most frequent value in a column?

Answer 35

df[‘column’].fillna(df[‘column’].mode()[0])

Question 36

36. How to drop the row if any of the column has missing value in DataFrame?

Answer 36

df.dropna(how=’any’)

Question 37

37. How to drop the row if all of the columns have missing value in DataFrame?

Answer 37

df.dropna(how=’all’)

Question 38

38. How to drop the rows only if missing values are present in the specified columns in DataFrame?

Answer 38

df.dropna(subset=[‘column_name’])

Question 39

39. How to drop the column if any of the value is missing in DataFrame?

Answer 39

df.dropna(axis=1, how=’any’)

Question 40

40. How to drop the column if all of the values are missing in DataFrame?

Answer 40

df.dropna(axis=1, how=’all’)

Question 41

41. How to keep the DataFrame with non NaN values in the same variable?

Answer 41

df.dropna(inplace=True)

Question 42

42. How to replace NaN values in a DataFrame with a constant text?

Answer 42

df.fillna(‘CONSTANT’)

Question 43

43. How to replace NaN values in a DataFrame with an interpolated value?

Answer 43

df.interpolate()

Question 44

44. How to replace NaN values in a DataFrame with the value that comes directly after it in the same column

Answer 44

then replace all remaining na with 0?

Question 45

45. How to replace NaN values in a DataFrame with the mean value of each column?

Answer 45

df.fillna(df.mean())

Question 46

46. How to replace NaN values in a DataFrame with the median value of each column?

Answer 46

df.fillna(df.median())

Question 47

47. How to replace NaN values in a DataFrame with the mode value of each column?

Answer 47

df.fillna(df.mode().iloc[0])

Question 48

48. How to replace NaN values in a DataFrame with the value from the previous row in the same column?

Answer 48

df.fillna(method=’ffill’, axis=0)

Question 49

49. How to replace NaN values in a DataFrame with the value from the next row in the same column?

Answer 49

df.fillna(method=’bfill’, axis=0)

Question 50

50. How to replace NaN values in a DataFrame with an arbitrary value?

Answer 50

df.fillna(value)