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Class 12 info

Authored by Vijayalakshmi Kavoor

Computers

12th Grade

Used 1+ times

Class 12 info
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10 questions

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1.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

Seven Brothers Fashion Inc. is a fashion company with design and market unit 130 m away from each other. The company recently connected their LANs using Ethernet cable to share stock related information. But after joining the LAN, they are not able to share the information due to loss of signal in between. Which device out of the following should you suggest to be installed for smooth communication?

Modem

Repeater

UPS

2.

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

Devices that are used to connect different types of networks. It performs the necessary translation so that the connected networks can communicate properly.

Router

Modem

WAN

3.

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

Which of the following method is used to delete row/column from a dataframe?

delete()

remove()

discard()

drop()

4.

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

To delete a row from dataframe, which of the following method is correct? A dataframe is indexed with names.

df.drop(df.row_index=’Jay’)

df.drop(‘Jay’)

df.drop(df.row=’Jay’)

df.drop(df[‘Jay’])

5.

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

Which of the following method is correct for following dataframe to delete row by specifying index name? dt= ({‘Year1’:[1200,1220,1500]}, {‘Year2’:1800,1700,1400})

df = pd.DataFrame(dt,index=[‘T1′,’T2’])

Which of the following is correct to delete T2 index record from dataframe?

df.drop(df.index[‘T2’])

df.drop(df.idx=’T2′)

df.drop(index=’T2′)

df.drop(idx=’T2′)

6.

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

When you perform delete operation on dataframe, it returns a new dataframe always without changing the old dataframe. To avoid this which parameter you will use to change the original dataframe?

intact = True

inplace = True

update = True

replace = True

7.

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

Ankita is working on dataframe wihch has 4 rows and 3 columns. She wrote df.drop(df.index[[1,3]]). Which rows will be deleted from the dataframe?

No rows

Row 1 and Row 3

Rows between 1 and 3

Row 2

All rows from row no. 1 to index row no. 3

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