Python series

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 pd1

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

t = pd1.Series([1,2,4])

u=s-t

print (u)

• 0 1

  1 0

  2 1

  dtype: int64

• 0 0

  1 0

  2 1

  dtype: int64

• 0 0

  1 0

  2 -1

  dtype: float64

• 0 0

  1 0

  2 -1

  dtype: int64

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

Create an empty series S1

• S1 = pandas.Series(empty)

• S1 = pandas.series(numpy.Nan)

• S1 = pandas.Series()

• S1 = pandas.Series(null)

To specify data type int 16 for a series object s1 we can write

• s1 = pd.Series(data = numpy.array([2,3,4]), dtype = int16)

• s1 = pd.Series(data = numpy.array([2,3,4]), dtype = numpy. int16)

• s1 = pd.Series(data = numpy.array([2,3,4]), dtype =pandas. int16)

• all of the above

Which is the correct Pandas syntax to read in a csv file and assign it to a DataFrame df?

• df = read_csv('file.csv')

• df = read('file.csv', type = 'csv')

• df = pd.read_csv('file.csv')

• df = with open('file.csv') as pd.DataFrame

Type the syntax that returns the top 5 rows in DataFrame df with the native Pandas function (not slicing):

How many rows of data will be retrieved by default from the series if you use tail( ) method ?

• 2

• 3

• 4

• 5

What will be the index of the following series?

import pandas as pd

import numpy as np

info = {'x' : 0., 'y' : 1., 'z' : 2.}

a = pd.Series(info)

print (a)

• 0 1 2

• 1 2 3

• x y z

• None of the above