Q31. How to create DataFrame using numpy zeros?

Use np.zeros().

pd.DataFrame(np.zeros((3,3)))

Q32. How to create DataFrame using numpy ones?

Use np.ones().

pd.DataFrame(np.ones((2,2)))

Q33. Create DataFrame with random numbers?

Use np.random.

pd.DataFrame(np.random.rand(3,3))

Q34. Create Series using range?

Use range function.

pd.Series(range(5))

Q35. Create DataFrame with date index?

Use pd.date_range.

pd.DataFrame({'A':[1,2]}, index=pd.date_range('2024-01-01', periods=2))

Q36. Create DataFrame with categorical data?

Use pd.Categorical.

pd.DataFrame({'A':pd.Categorical(['a','b','a'])})

Q37. Create DataFrame from structured array?

Pass structured array.

pd.DataFrame(np.array([(1,'a')], dtype=[('num','i4'),('char','U1')]))

Q38. Create DataFrame using dictionary of Series?

Each Series becomes column.

pd.DataFrame({'A':pd.Series([1,2]),'B':pd.Series([3,4])})

Q39. Create multi-level index DataFrame?

Use pd.MultiIndex.

index = pd.MultiIndex.from_tuples([('A',1),('B',2)]) pd.DataFrame({'val':[10,20]}, index=index)

Q40. Create DataFrame from Excel?

Use read_excel.

pd.read_excel('file.xlsx')

Q41. Create DataFrame from SQL?

Use read_sql.

pd.read_sql(query, connection)

Q42. Create DataFrame from HTML table?

Use read_html.

pd.read_html('url')

Q43. Create DataFrame from clipboard?

Use read_clipboard.

pd.read_clipboard()

Q44. Create DataFrame with custom dtype?

Use dtype parameter.

pd.DataFrame({'A':[1,2]}, dtype='float')

Q45. Create empty Series?

Use pd.Series().

pd.Series()

Q46. Create DataFrame from dict of lists?

Keys become columns.

pd.DataFrame({'A':[1,2],'B':[3,4]})

Q47. Create DataFrame with missing values?

Use None or np.nan.

pd.DataFrame({'A':[1,np.nan]})

Q48. Create DataFrame from list of tuples?

Each tuple is row.

pd.DataFrame([(1,2),(3,4)])

Q49. Create Series with name?

Use name parameter.

pd.Series([1,2], name='numbers')

Q50. Create DataFrame with index labels?

Use index parameter.

pd.DataFrame({'A':[1,2]}, index=['x','y'])

Q51. Create DataFrame using np.arange?

pd.DataFrame(np.arange(6).reshape(2,3))

Q52. Create DataFrame from dictionary of arrays?

pd.DataFrame({'A':np.array([1,2])})

Q53. Create DataFrame using list comprehension?

pd.DataFrame([i for i in range(5)])

Q54. Create Series from scalar?

pd.Series(10, index=[0,1,2])

Q55. Create DataFrame using nested lists?

pd.DataFrame([[1,2],[3,4]])

Q56. Create DataFrame with boolean values?

pd.DataFrame({'A':[True,False]})

Q57. Create DataFrame with string values?

pd.DataFrame({'A':['a','b']})

Q58. Create DataFrame using dictionary comprehension?

pd.DataFrame({i:i*i for i in range(3)}, index=[0])

Q59. Create DataFrame from zip of multiple lists?

pd.DataFrame(list(zip([1,2],[3,4])))

Q60. Create DataFrame with duplicate columns?

pd.DataFrame([[1,2]], columns=['A','A'])

Q61. Create Series with float values?

pd.Series([1.1,2.2])

Q62. Create DataFrame from JSON string?

pd.read_json('{"A":1}')

Q63. Create DataFrame from dict of dict?

pd.DataFrame({'A':{'x':1}})

Q64. Create DataFrame with index and columns?

pd.DataFrame([[1]], index=['i'], columns=['A'])

Q65. Create DataFrame with mixed datatypes?

pd.DataFrame({'A':[1],'B':['x']})