(using jupyter notebook)You are going to compute the summary statistics for the data set Iris, which can be download at: https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data. The data set information is available at https://archive.ics.uci.edu/ml/datasets/iris and the attribute information is listed in the page https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.names. You may need to study the data set information before answering the following questions. Load the data from the URL. Store it in a variable named data.Extract the data column sepal length and stores into a variable named sepal_length.Find the mean and standard deviation of the sepal_length, store in variables named mean and std respectively.Create a histogram with 20 bins for the sepal length.Add vertical lines to indicate the mean (red solid line) and standard deviation (two yellow dotted lines) on the histogram.Add figure title 'Distribution of sepal length'.Add xlabel as 'sepal length (cm)', ylabels as 'number of samples'.

In questions with many questions, we must do 3.

Answered: using jupyter notebook) You are going…

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

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(using jupyter notebook)

You are going to compute the summary statistics for the data set Iris, which can be download at: https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data. The data set information is available at https://archive.ics.uci.edu/ml/datasets/iris and the attribute information is listed in the page https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.names. You may need to study the data set information before answering the following questions.

Load the data from the URL. Store it in a variable named data.
Extract the data column sepal length and stores into a variable named sepal_length.
Find the mean and standard deviation of the sepal_length, store in variables named mean and std respectively.
Create a histogram with 20 bins for the sepal length.
Add vertical lines to indicate the mean (red solid line) and standard deviation (two yellow dotted lines) on the histogram.
Add figure title 'Distribution of sepal length'.
Add xlabel as 'sepal length (cm)', ylabels as 'number of samples'.