Page 75 - IPP-12-2024

0 car Ford 7000000
1 AC Hitachi 5000
2 Aircooler Symphony 12000
3 Washing Machine LG 14000
Result after Filtering DataFrame
itemcat expenditure
itemcat
AC AC 5000
Aircooler Aircooler 12000
Washing Machine Washing Machine 14000
car car 7000000

th
Program 4: Write a program to print all the elements that are above the 75 percentile from the given
series.
Solution:

import numpy as np
series = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
percentile_75 = np.percentile(series, 75)
above_75th = [elem for elem in series if elem > percentile_75]
print(above_75th)
Output:
[80, 90, 100]

Program 5: Write a program to create a data frame for examination result and display row labels,
column labels data types of each column and the dimensions.
Solution:
import pandas as pd

dic={'Class':['I','II','III','IV','V','VI','VII','VIII','IX','X','XI',
'XII'],

'Pass_Percentage':[100,100,100,100,100,100,100,100,100,98.6,100,99]}
result=pd.DataFrame(dic)

print(result)
print(result.dtypes)
print('shape of the dataframe is::::')

print(result.shape)
Output:
Class Pass_Percentage
0 I 100.0
1 II 100.0
2 III 100.0
3 IV 100.0
4 V 100.0
5 VI 100.0
6 VII 100.0
7 VIII 100.0
8 IX 100.0
9 X 98.6
10 XI 100.0