Assignment 2: COVID-19 Data Wrangling Name: The purpose of this assignment is to hone your data wrangling skills. Your task for this assignment is to perform the data preparation as instructed in the DTSC670_Assignment_2 pdf listed in Brightspace. After performing all the data preparation tasks outlined in the document, run the code in the "Prepare DataFrames for Grading" section. You are supplied an Excel file called BrazilcOVIDData.xlsx - be sure to put the data file in the same directory as this Jupyter Notebook. Please note that it may take around 5 minutes to read-in all of the data in this file. ]: ### ENTER CODE HERE ### # Insert as many cells as you need, but be sure your code is very neat and very well documented. ]: # Get Final Features DataFrame # features = ### ENTER CODE HERE ### # Get Final Response DataFrame # response = ### ENTER CODE HERE ###

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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Prepare DataFrames for Grading
Do not make changes to the below code
After completing all data preparation tasks, run the following four cells to prepare your DataFrame for grading by:
1. Outputting the features and response DataFrames (you do not need to print).
2. Using the NumPy around() function to round all the values in both DataFrames to ZERO decimal places. You are calling these features_round and
response_round , respectively.
3. Computing the sum of every column for both features_round and response_round , and saving those values as features_final and
response_final
Finally, you are printing your final answer using the print() function.
Be sure to run all cells of your notebook prior to submitting, so that all output is rendered, visible and there are no error messages.
In [ ]:
features
In [ ]:
I response
In [ ]:
I features_round = np.around (features, decimals=0)
features_final = features_round.sum(axis=0)
print(features_final)
In [ ]: N response_round = np.around (response, decimals=0)
response_final = response_round.sum(axis=0)
print(response_final)
Transcribed Image Text:Prepare DataFrames for Grading Do not make changes to the below code After completing all data preparation tasks, run the following four cells to prepare your DataFrame for grading by: 1. Outputting the features and response DataFrames (you do not need to print). 2. Using the NumPy around() function to round all the values in both DataFrames to ZERO decimal places. You are calling these features_round and response_round , respectively. 3. Computing the sum of every column for both features_round and response_round , and saving those values as features_final and response_final Finally, you are printing your final answer using the print() function. Be sure to run all cells of your notebook prior to submitting, so that all output is rendered, visible and there are no error messages. In [ ]: features In [ ]: I response In [ ]: I features_round = np.around (features, decimals=0) features_final = features_round.sum(axis=0) print(features_final) In [ ]: N response_round = np.around (response, decimals=0) response_final = response_round.sum(axis=0) print(response_final)
DTSC670: Foundations of Machine Learning Models
Module 1
Assignment 2: COVID-19 Data Wrangling
Name:
The purpose of this assignment is to hone your data wrangling skills. Your task for this assignment is to perform the data preparation as instructed in the
DTSC670_Assignment_2 pdf listed in Brightspace. After performing all the data preparation tasks outlined in the document, run the code in the "Prepare
DataFrames for Grading" section.
You are supplied an Excel file called BrazilcOVIDData.xlsx - be sure to put the data file in the same directory as this Jupyter Notebook. Please note that it
may take around 5 minutes to read-in all of the data in this file.
In [ ]:
N ### ENTER CODE HERE ###
# Insert as many cells as you need, but be sure your code is very neat and very well documented.
In [ ]:
N # Get Final Features DataFrame
# features = ### ENTER CODE HERE ###
# Get Final Response DataFrame
# response = ### ENTER CODE HERE ###
Transcribed Image Text:DTSC670: Foundations of Machine Learning Models Module 1 Assignment 2: COVID-19 Data Wrangling Name: The purpose of this assignment is to hone your data wrangling skills. Your task for this assignment is to perform the data preparation as instructed in the DTSC670_Assignment_2 pdf listed in Brightspace. After performing all the data preparation tasks outlined in the document, run the code in the "Prepare DataFrames for Grading" section. You are supplied an Excel file called BrazilcOVIDData.xlsx - be sure to put the data file in the same directory as this Jupyter Notebook. Please note that it may take around 5 minutes to read-in all of the data in this file. In [ ]: N ### ENTER CODE HERE ### # Insert as many cells as you need, but be sure your code is very neat and very well documented. In [ ]: N # Get Final Features DataFrame # features = ### ENTER CODE HERE ### # Get Final Response DataFrame # response = ### ENTER CODE HERE ###
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