मराठी

Which of the following statement will import pandas library?

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प्रश्न

Which of the following statement will import pandas library?

पर्याय

  • Import pandas as pd

  • import Pandas as py

  • import pandas as pd

  • import panda as pd

MCQ
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उत्तर

import pandas as pd

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संबंधित प्रश्‍न

Assertion (A): To create a series from array, we have to import the NumPy module and then use array () method.

Reason (R): NumPy is an open-source numerical Python library. NumPy contains a multi-dimensional array and matrix data structures.


Select the correct statement:


Pandas Series is a ______.


By default, Series.tail() function display last ______ rows.


Write Python series to print scalar value “10” 5 times.


Select code to display the sum of Series M1 and Series M2:

(i) print (sum(M1,M2))

(ii) print(M1+M2)

(iii) print(M1.add(M2))

(iv) print(M1.sum(M2))


Select code to show rows where values of series M1 greater than 75.


Set the series name “Marks1” of M1 series:


The keys of the dictionary are used to represent the ______ of the Series.


Series to print scalar value “100” 5 times:


Assuming the given series, named stud, which command will be used to print 5 as output?

1 5
2 10
3 15
4 20
5 25

Which attribute is used to return the data type of the underlying data for the given Series object?


Which code is correct to show rows those empno are greater than 103?

empno=[101,102,103,104,105,106,107]
p=pd.Series(empno)


Which statement is not correct to print the top 5 rows from series s?


Write the output of the given command:

import pandas as pd
s=pd.Series([10,20,30,40,50],[1,2,3,4,5])
print(s.loc[2])

Write the output of the given command:

import pandas as pd
s=pd.Series([10,20,30,40,50],[1,2,3,4,5])
print(s[2]+s.iloc[2])

Write the output of the given command:

import pandas as pd
s=pd.Series([10,20,30,40,50],[1,2,3,4,5])
print(s.loc[2]*2)

To display the last five rows of a series object ‘S’, you may write ______


What will be the output of the following code:

>>>import pandas as pd
>>>A = pd.Series(data = [35, 45, 55, 40])
>>>print(A > 45)

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