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Given Dataframe, df:
Based on the above data, solve questions:
| State | Geographical_Area | Area_Under_Dense_Forest | |
| 1 | Manipur | 78438 | 2797 |
| 2 | Delhi | 1483 | 6.72 |
| 3 | Kerala | 38852 | 1663 |
| 4 | Tamil Nadu | 40699 | 1904 |
Based on the above data, solve questions:
Question: 1
Identify the meaning of the given python code with respect to the given dataframe, df df = df.drop(['state'], axis = 1)
Identify the meaning of the given python code with respect to the given dataframe, df df = df.drop(['state'], axis = 1)
Updated On: Oct 18, 2024
- The given code statement has an error
- The given code statement is able to delete the State column and shows the rest dataframe
- The given code statement makes the empty dataframe
- The given code remove duplicate rows from the dataframe
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The Correct Option is B
Solution and Explanation
The correct option is (B) : The given code statement is able to delete the State column and shows the rest dataframe
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Question: 2
Based on the above data, solve questions: Identify the correct code to set the Geographical area of all states to 70000:
Based on the above data, solve questions: Identify the correct code to set the Geographical area of all states to 70000:
Updated On: Oct 18, 2024
- df.loc[State] = 70000
- df['State',:] = 70000
- df['State'] = 70000
- dfGeographical_Area'] = 70000
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The Correct Option is D
Solution and Explanation
The correct option is (D) :dfGeographical_Area'] = 70000
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Question: 3
Identify the error that shows on the screen while executing the given code : df.Ioc[5] = ['Meghalaya', 70000)
Identify the error that shows on the screen while executing the given code : df.Ioc[5] = ['Meghalaya', 70000)
Updated On: Oct 18, 2024
- Value Error : Length of values does not match length of index
- Value Error : Cannot set a row with mismatched columns
- Value Error : Too few parameters
- Value Error : Enough values
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The Correct Option is B
Solution and Explanation
The correct option is (B) :Value Error : Cannot set a row with mismatched columns
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Question: 4
Identify the correct code to display Area_under_dense forest column.
Identify the correct code to display Area_under_dense forest column.
Updated On: Oct 18, 2024
- df.loc[:,'Area_under_dense_forest']
- df.loc[2]
- df.loc[Area_under_dense_forest']
- df[Area_under_dense_forest]
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The Correct Option is A
Solution and Explanation
The correct option is (A) :df.loc[:,'Area_under_dense_forest']
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Question: 5
Find the output for : df.loc['Kerala']\(>30000:\)
Find the output for : df.loc['Kerala']\(>30000:\)
Updated On: Oct 18, 2024
- Geographical_Area 38852
- Geographical Area 38852 Area_under_dense_forest 1663
- Geographical Area True Area under dense forest False
- Kerala 38852
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The Correct Option is C
Solution and Explanation
The correct option is (C) :
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