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 notebook
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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 notebook
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- 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) +…Import the pets.csv dataset from your data file into Rstudio. Use the unique function on the pet column to find all the unique pets in the data. Which is the second pet in the resulting output?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,…
- Type the command to create an xz compressed archive with the name backups, using the files Horde4.txt, Horde5.txt, and Horde5_Copy.txt. Be sure to add the appropriate extension when naming the archive! When finished, run the appropriate command to list the contents of the newly created archive.Write a pseudo-code on how to import global COVID cases data. Assume you have a CSV file containing all countries' daily COVID cases and mortality rates. What likely syntax/command will you write for your code to display the COVID data for only two countries?ask 1. Import the data into R and give an overview over the data, using summary statistics asappropriate. If you access the data directly from the UK government webpage, it may be easiestto first load the data into Microsoft Excel and then to save the relevant section of the spreadsheetas a csv file. Make sure to read the explanations in the Excel file.As hinted at in the original spreadsheet, rows are duplicated, with the duplicates differing onlyin the column ‘Licence Category’. Since we are not interested in licence categories, remove thecolumn ‘Licence Category’ from the data, and then use the command unique() to remove theexcess rows. (You can type ‘help(unique)‘ to learn how this command works.) Your reportshould at least address the following issues: Give some general information about the data set. Convince the reader that you have imported the data correctly. State how many rows were removed as duplicates. What is the most common vessel name?
- 1. Read a give “data.csv” file, analyze the data, write the analysis result to“report.txt” file :in the report.txt file: include information of:1). How many rows in this dataset, for example: “This dataset has 10 rows”2). How many columns in this dataset, for example:”This dataset has 3 col-umns.”3). What are the name for the columns, print the all the column names, forexample, “The 3 columns are: name,age,gpa”4). How many numeric column(s), for example, “ This dataset has 2 numericcolumns, they are age, and gpa”5). The mean (avarage) of each column, for example, “The means are:mean1, mean2” pythonIn R please provide the code and steps for the following Install the dplyr package and load the library. Load the starwars data set Make a new dataframe that only contains the height and species columns from the original data set Remove all of the rows from the new dataframe that have missing values. How many rows of data were lost when the n/a values were removed? It is recommended that you use the na.omit() function for this ex: myData <- mydata %>% na.omit() Create two new dataframes that contain the heights of humans and aliens (not humans and not droids) respectively. Read the help documentation for the par() function – the first example listed is especially relevant. Create 4 images in the same window Top Left : histogram of human heights Top Right: histogram of alien heights Bottom Left: qq plot of human heights Bottom Right: qq plot of alien heights Describe the shape of the distributions and what your observations are about the heights of these two…Read the ckd dataset (ckd.xlsx) and save it as df_ckd Read the AAPL dataset (AAPL.csv) and save it as df_aapl Read the telco_churn dataset (telco_churn.csv) and save it as df_churn Datasets are saved in the content folder of the blackboard under Assignment Datasets. import pandas as pd df_ckd = # fill in here # df_appl = # fill in here # df_churn = # fill in here #
- Create a pandas DataFrame with two columns. The first column should be titled F for Fahrenheit, and should contain the numbers from 0 to 100, counting by fives. The second column should be titled C for Celsius, and contain the corresponding temperature in degrees Celsius for the number in the first column.data.csv: Product Name, PricePen, 10Pencil, 20Eraser, 5 What is output? import csvwith open('data.csv','r+') as file: csvFile = csv.reader(file) for row in csvFile: print(row) a. ['Product Name', 'Price'] ['Pen', '10'] ['Pencil', '20'] ['Eraser', '5'] b. Product Name, Price Pen, 10 Pencil, 20 Eraser, 5 c. Product Name Price Pen 10 Pencil 20 Eraser 5 d. [Product Name, Price] [Pen, 10] [Pencil, 20] [Eraser, 5]Write The preceding code for the seeders file for the posts, but instead, we are now inserting users with the correct fields. Every user receives an auto-incremented ID by our MySQL server when inserting a user.
