dataframe

Full form of NaN is

• Not a Null

• Not a Number

• Not a Numeric

• None of these

Data structures in Pandas can be mutated in the terms of ____ but not of _____.

• size, value

• value, size

• semantic, size

• none of the above

pandas is a:

• Data Structure

• Series

• Dataframe

• Library

Write the output for the following:

import pandas as pd1

s = pd1.Series(5, index=[0, 1, 2, 3])

print(s)

• 0 5

• 0 5

  1 5

  2 5

  3 5

  dtype: int64

• 1 5

  2 5

  2 5

  4 5

  dtype: int64

• 0 5

  1 5

  2 5

  3 5

  dtype: object

write the output:

import pandas as pd

s=pd.Series([1,2,3,4],index=['a','b','c','d'])

print(s.iloc[2:4])

• b 2

  c 3

  d 4

  dtype: int64

• b 3

  c 4

  dtype: int64

• c 3

  d 4

  dtype: int64

• none of the above

write the output:

import pandas as pd

s=pd.Series([1,2,3,4],index=['a','b','c','d'])

print(s.loc['b':'d'])

• b 2

  c 3

  d 4

  dtype: float64

• b 2

  c 3

  d 4

  dtype: object

• c 3

  d 4

  dtype: int64

• b 2

  c 3

  d 4

  dtype: int64

Series.tail(3) will return how many values.

• 3 values from front

• 3 values from last

• 5 values

• none

Series.head() will return how many rows.

• 2

• 4

• 3

• 5

Which of the following commands is used to convert array named "grades" into data frame named "df_grades"?

• df_grades = grades

• df_grades = pd.DataFrame(grades)

• df_grades = pd.DataFrame("grades")

• grades = pd.DataFrame(df_grades)

Which among the following options can be used to create a DataFrame in Pandas?

• A scalar value

• An ndarray

• A python dict

• All of the above