Section: Debugging Define and describe 1. What a bug is. 2. What debugging is and why debugging is challenging. 3. What a debugger is. Provide a screenshot image of your desktop where you are debugging the provided C++ code that clearly shows breakpoints that will stop the execution of the program when an alert is sent, and when the blood pressure is determined. Provide details to the reader of the report detailing how each of your breakpoints will allow the reader of the report to understand about the program.
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Section: Debugging
Define and describe
1. What a bug is.
2. What debugging is and why debugging is challenging.
3. What a debugger is.
Provide a screenshot image of your desktop where you are debugging the provided C++ code that
clearly shows breakpoints that will stop the execution of the
when the blood pressure is determined. Provide details to the reader of the report detailing how
each of your breakpoints will allow the reader of the report to understand about the program.
Step by step
Solved in 3 steps
- The tasks are relevant to the dataset "College.csv" college.csv file at the path: https://drive.google.com/file/d/1StNKOnI0IDQKgZ35b-VZf1_5a_Dono-N/view?usp=sharing request code python : K nearest neighbor: a. Create a binary attribute Apps01 that contains a 1 if Apps contains a value equal to or above its median, and a 0 if Apps contains a value below its median. Create a single data set d containing both Apps01 and the other College features. Split the data into d.train training set and d.test test set 80:20.b. Perform k-NN with several values of k in order to predict Apps01 using all the features.c. Display the comparison of validation error rate for different values of k.Load the diamonds.csv file, and make 80% of the data in the order of the data as the training data.Average the price of the top 100 data by price. https://1drv.ms/u/s!ArouXkp1zam8g278gqoGxGBsu8W8?e=dyY60S This is the diamonds.csv file answer : ? executable code : ? Using jupyter notebookcreate this html page link image 1 https://e.edim.co/205361572/xnxVrIs7fmJ3ONIy.png?response-content-disposition=filename%3D%22email.png%22%3B%20filename%2A%3DUTF-8%27%27email.png&Expires=1641843436&Signature=JJJVyz7d8KxVOL5PKkQWHDAiEwHywB-p-fWML3jIsZFCg1D8fuBV-HcTblHIugF~j387r-dlYQ14TUsTwIfrKGU1B95GjRcGXjBEov9Y1HD3rtJG1YxZedk96PQoilleaKmQqLTDa41Ln96Go4INrRhWRCoc4q5iZkqWRN5kc7dNG~bni9kFR0EG5-Gs68uipZTtzK-VSikLWqMhgkg4pY-M18cLF8uVEiDS-g-k1UVFIwC1d-6DZ9VAqbh949I1C87GGPIrvixosbcZ3q1CTp50ESyUz3wT9Thh4UawBHkLFAk5n~apwZ0QRMCfINMtdsoXyEzHa7ucbWbUelSlFg__&Key-Pair-Id=APKAJMSU6JYPN6FG5PBQ 2…
- Please solve the question 3 from the given pdf. Use the database which is provided in question 1 & 2 Please do it in MySQL and use workbench. Assignment link: https://smallpdf.com/result#r=3870a27b9c070c56f95497e8ae92217c&t=share-document Please provide appropriate snipsyou can download the Dataset from this link - https://drive.google.com/file/d/1wlepxNIAc_6EQgv9M6WmYtSRJ7eQoty/view?usp=share_link Draw a bar chart to view of the distribution of spam and non-spam email samples in the dataset. How many emails are in the dataset? How many of the emails are spam? (Please answer this question based on implemeted code. You can use any programming language)Write a Python program to visualize the state/province wise Active cases of Novel Coronavirus (COVID-19) in USA. import pandas as pdcovid_data= pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports/03-17-2020.csv')us_data = covid_data[covid_data['Country/Region']=='US'].drop(['Country/Region','Latitude', 'Longitude'], axis=1)us_data = us_data[us_data.sum(axis = 1) > 0]us_data = us_data.groupby(['Province/State'])['Deaths'].sum().reset_index()us_data_death = us_data[us_data['Deaths'] > 0]state_fig = covid_data.plot.bar(us_data_death, x='Province/State', y='Deaths', title='State wise deaths reported of COVID-19 in USA', text='Deaths')state_fig.show() the parts in bold are the parts i am most confused about. for covid_data, i don't know which part of the code i should be referencing to use plot.bar. for the x, when running the program, i get an error message that says that there are multiple values for arguement…
- Inspect this XML file (plants.xml Download plants.xml BELOW) and then complete the XPath expression below that finds the botanical name of all plants that require 'Mostly Shady' light. Do not add extraneous spaces. //PLANT______/BOTANICAL Answer <CATALOG><PLANT><COMMON>Bloodroot</COMMON><BOTANICAL>Sanguinaria canadensis</BOTANICAL><ZONE>4</ZONE><LIGHT>Mostly Shady</LIGHT><PRICE>$2.44</PRICE><AVAILABILITY>031599</AVAILABILITY></PLANT><PLANT><COMMON>Columbine</COMMON><BOTANICAL>Aquilegia canadensis</BOTANICAL><ZONE>3</ZONE><LIGHT>Mostly Shady</LIGHT><PRICE>$9.37</PRICE><AVAILABILITY>030699</AVAILABILITY></PLANT><PLANT><COMMON>Marsh Marigold</COMMON><BOTANICAL>Caltha palustris</BOTANICAL><ZONE>4</ZONE><LIGHT>Mostly…Please help with the 1 Python question Data File: https://docs.google.com/spreadsheets/d/1-S_xnAQXa1QCoWQt7xyvxo42XRNC1QBd/edit?usp=sharing&ouid=112107649557425878726&rtpof=true&sd=true %%capture############################################################## EXECUTE THIS CELL BEFORE YOU TO TEST YOUR SOLUTIONS ##############################################################import imp, os, syssol = imp.load_compiled("solutions", "./solutions.py")sol.get_solutions("imdb.xlsx")from nose.tools import assert_equalfrom pandas.util.testing import assert_frame_equal, assert_series_equal # Loading the dataimport pandas as pdimport numpy as np xls = pd.ExcelFile('imdb.xlsx')df = xls.parse('imdb')df_directors = xls.parse('directors')df_countries = xls.parse('countries') df = pd.merge(left=df, right=df_countries, how='inner', left_on='country_id', right_on='id') df = pd.merge(left=df, right=df_directors, how='inner', left_on='director_id',…Read the Yahoo! Finance data in quiz-4.csv into a long data frame named df_long. You must use a relative file path for quiz-4.csv instead of an absolute file path. Gradescope will place quiz-4.csv in the same folder as your notebook and will not find any other folders. Reshape df_long to a wide data frame named df with: a row index named Date in chronological order a column multi-index named Variable and Ticker Ignore the CSV file I just need the PYTHON code of this.
- Please help me Below here I have written the code for extracting the data using scrapy for the given url for state=uttarpradesh and districts=[SANT RAVIDAS NAGAR, AGRA, VARANASI] But the data present in all pages is not saving in the excel sheet can u provide the code where to add the code and all to save all pages of data in excel sheet import scrapy import pandas as pd class HandicraftSpider(scrapy.Spider): name = "handicrafts" start_urls = [ 'http://www.handicrafts.nic.in/ArtisanData.aspx?MID=SZmOd%2fCrxTo9CHD2XKF+pA%3d%3d' ] def parse(self, response): yield scrapy.FormRequest.from_response( response, formdata={'__EVENTTARGET': '', '__EVENTARGUMENT': '', '__LASTFOCUS': '', '__VIEWSTATE': response.css('input#__VIEWSTATE::attr(value)').get(), '__VIEWSTATEGENERATOR': response.css('input#__VIEWSTATEGENERATOR::attr(value)').get(), '__EVENTVALIDATION': response.css('input#__EVENTVALIDATION::attr(value)').get(), 'ddlstate': 'Uttar Pradesh', 'ddldist': 'Sant Ravidas Nagar, Agra,…I am a newbie to python. I am working on a CSV file where it has over a million records. In the data, every Location has a unique ID (SiteID). I want to filter for and remove any records where there is no value or mismatch between SiteID and Location in my CSV file. (Note: This script should print the lines number and mismatch field values for each record.)lines = []count = 0 # read linewith open(r"air-quality-data-continuous.csv",'r') as fp: # read an store all lines into list lines = fp.readlines() print(str(len(lines)) + 'lines in input file') with open(r"crop.csv", 'w') as fp: fp.write(lines.pop(0)) #iterate each line for number, line in enumerate(lines): if (line[4] == 'NaN'): print('Empty Site ID found in line:' + str(number)) continue if(str(line[4]) != line[17]): fp.write(line) count +=1 print(str(count + 1) + 'lines written to filter.csv') print(str(count + 1) +…Demonstrate the use of CRUNCH tool to create a wordlist file to generate a minimum and maximum word length (1-8) based on combination of your MIT ID and two unique special characters. Store the result in file ‘wordlist.txt’. List any two example generated passwords. Demonstrate the use of Hydra Tool to attack an FTP Server ftp://192.168.26.37 with the username “admin”. For the password use the wordlist file ‘wordlist.txt’ generated using the Crunch Utility in the previous step. Note: You only need to write the commands and are not required to implement on the system as it will demonstrate your implementation skills.