Step 1: Write a function to create a new dataframe(s) for a given weight class. (Inputs should be base dataframe and weight class; Output should be anew dataframe containing only that weight class.)Use examples to justify that your dataframes have been created correctly.In [ ]: # Put your pseudocode and code here# List to help extract information from the base dataframeweight_class_list =frame_names_list['47', '52', '57', '63', '72', '84', '84+', '59', '66', '74', '83', '93', '105', '120', '120+']['class_47kg','class_52kg','class_57kg','class_63kg','class_72kg','class_84kg','class_84pluskg',\'class_59kg','class_66kg','class_74kg','class_83kg','class_93kg','class_105kg','class_120kg','clStep 2: Loop through all the weight classes and store the dataframes for each weight classs in a list (Lists can store all types of variables includingPandas dataframes!)In [ ]: # Put your pseudocode and code here Write a function to calculate the mean, median, and standard deviation for a single weight class. Then, write a loop through all of the weightclasses and save the results of your calculations for plotting.]: # Put your pseudocode and code here

Step 1: import pandas as pd weight_class_list= ['47', '52' ,'57' ,'63', '72' ,'84' ,'84+', '59'…

new dataframe containing only that weight class.) Use examples to justify that your dataframes have been created correctly. In [ ]: # Put your pseudocode and code here # List to help extract information from the base dataframe weight_class_list = ['47', '52', '57', '63', '72', '84', '84+', '59', '66', '74', '83', '93', '105', '120', frame_names_list = ['class_47kg','class_52kg','class_57kg','class_63kg','class_72kg','class_84kg','class_84 'class_59kg','class_66kg','class_74kg','class_83kg','class_93kg','class_105kg','class_1 Step 2: Loop through all the weight classes and store the dataframes for each weight classs in a list (Lists can store all types of variables Pandas dataframes!) In [ ]: # Put your pseudocode and code here

new dataframe containing only that weight class.) Use examples to justify that your dataframes have been created correctly. In [ ]: # Put your pseudocode and code here # List to help extract information from the base dataframe weight_class_list = ['47', '52', '57', '63', '72', '84', '84+', '59', '66', '74', '83', '93', '105', '120', frame_names_list = ['class_47kg','class_52kg','class_57kg','class_63kg','class_72kg','class_84kg','class_84 'class_59kg','class_66kg','class_74kg','class_83kg','class_93kg','class_105kg','class_1 Step 2: Loop through all the weight classes and store the dataframes for each weight classs in a list (Lists can store all types of variables Pandas dataframes!) In [ ]: # Put your pseudocode and code here

C++ for Engineers and Scientists

4th Edition

ISBN:9781133187844

Author:Bronson, Gary J.

Publisher:Bronson, Gary J.

Chapter7: Arrays

Section7.5: Case Studies

Problem 3E

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