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प्रश्न
To display the last five rows of a series object ‘S’, you may write ______
विकल्प
S.Head()
S.Tail(5)
S.Head(5)
S.tail()
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उत्तर
To display the last five rows of a series object ‘S’, you may write S.tail().
APPEARS IN
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 ______.
Give the output of:
s=pd.Series([10,20,30,40,50],index =[‘a’,‘b’,‘c’,0,1])
print(s.loc[1])
By default, Series.tail() function display last ______ rows.
Command to create empty Series is ______.
Pandas Series is capable of holding ______ data type.
Size and values of data of Series are ______.
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))
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)Which of the following statement will import pandas library?
What will be the output of the following code:
>>>import pandas as pd
>>>A = pd.Series(data = [35, 45, 55, 40])
>>>print(A > 45)