Create a dataframe variable 'a' with this dataset. This dataframe should have all the 569 instances,30 features and the class of 569 instances as 0 (Malignant) or 1 (Benign). The column that containsthe classes should be labeled as 'typeofcancer'. Show the output of the following input:In [13]:▸a.shape[Hints: the outputs should be same as below.Out [13] (569, 31)(b) Now create a dataframe variable 'df' by slicing dataframe 'a'. The new dataframe 'df' shouldhave all the instances, their labels but with the following three features: mean radius, meanperimeter and mean area. [Hints: use. iloc method to extract necessary columns from 'a’](i) Show the first two rows.[Hint: The output should be same as below.Out [16]:01mean radius mean perimeter17.9920.57122.8132.9mean area typeofcancer1001.01326.0(ii) Show the rows with indexes 17, 18, 19, 20, 21.00

Answered: Create a dataframe variable 'a' with…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Question

Create a dataframe variable 'a' with this dataset. This dataframe should have all the 569 instances,
30 features and the class of 569 instances as 0 (Malignant) or 1 (Benign). The column that contains
the classes should be labeled as 'typeofcancer'. Show the output of the following input:
In [13]:
▸a.shape
[Hints: the outputs should be same as below.
Out [13] (569, 31)
(b) Now create a dataframe variable 'df' by slicing dataframe 'a'. The new dataframe 'df' should
have all the instances, their labels but with the following three features: mean radius, mean
perimeter and mean area. [Hints: use. iloc method to extract necessary columns from 'a’]
(i) Show the first two rows.
[Hint: The output should be same as below.
Out [16]:
0
1
mean radius mean perimeter
17.99
20.57
122.8
132.9
mean area typeofcancer
1001.0
1326.0
(ii) Show the rows with indexes 17, 18, 19, 20, 21.
0
0

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pandas:-

A Python module called pandas offers quick, adaptable, and expressive data structures that are intended to make dealing with "relational" or "labeled" data simple and natural. It aspires to serve as Python's core, the high-level building block for performing useful, in-the-real-world data analysis.

Pandas is a term used to describe an open-source Python library that offers high-performance data manipulation. Pandas, which means Econometrics from Multidimensional Data, gets its name from the phrase panel data. Wes McKinney created it in 2008 and uses Python to analyze data.

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