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- Use the iloc() function to extract the first 20 features of the dataframe har_train. Save this new dataframe to first_twenty. Next, using the seaborn library create a heatmap for the correlation matrix. First you have to create the correlation matrix from the pandas dataframe (save it in a dataframe called corr) and then plot it using seaborn with these customizations: Set the seaborn style to white. Generate a mask using np.triu(np.ones_like()) with the dtype as boolean to only show the lower triangle of the correlation matrix. Save it in a variable called mask. Set up the figure with matplotlib with figsize=(11,9). Use fig, ax = ... Generate a custom diverging colormap for the heatmap with the arguments (220, 10, as_cmap=True). Save it in a variable called cmap. Draw the heatmap with the mask and correct aspect ratio, using the arguments corr, mask=mask, cmap=cmap, vmax=.3, center=0, square=True, linewidths=.5, cbar_kws={"shrink": .5}). Finally, use fig.tight_layout() just before…I imported the file from Excel and made a csv file, but when I tried making it a dat file, it didn't recognize the csv file. I know you probably don't have the data file (you might not need it), but if you could help with the commands, I would be grateful. Thank you. Open the "Goals Data" file. Save the "Data" sheet into its own *.csv file. Import the *.csv file into an R data frame. Name the data frame "Sales." Summarize the "Sales" data frame using an appropriate R command(s) to ensure that the data was imported. Perform the following commands to load the "Export Tables to LaTeX" or "HTML" package: install.packages("xtable") followed by: library("xtable"). Using an appropriate command from the xtable package, export Sales to an *.html file. Name the file "Sales.html."Using R, create an interesting visual using the ggplot library. You may use a dataset of your choice, but be sure to attach the dataset you use. Use ggplot elements and show creativity and complexity in the visual. Show final R code in your answer. Once you create the visual, write an explanation talking about why you chose the visual you did (~1 paragraph).
- Automated Title: In eq_world_map_3.py, we specified the title manually when defining my_layout, which means we have to remember to update the title every time the source file changes. Instead, you can use the title for the data set in the metadata part of the JSON file. Pull this value, assign it to a variable, and use this for the title of the map when you’re defining my_layout.Using R, create an interesting visual using the ggplot library. You may use a dataset of your choice, but be sure to attach the dataset you use. Use ggplot elements and show creativity and complexity in the visual. Show final R code in your answer. Do not copy any code and write your own unique code. Once you create the visual, write an explanation talking about why you chose the visual you did (~1 paragraph).Computer Science I imported the file from Excel and made a csv file, but when I tried making it a dat file, it didn't recognize the csv file. I know you probably don't have the data file (you might not need it), but if you could help with the commands, I would be grateful. Thank you. Open the "Goals Data" file. Save the "Data" sheet into its own *.csv file. Import the *.csv file into an R data frame. Name the data frame "Sales." Summarize the "Sales" data frame using an appropriate R command(s) to ensure that the data was imported. Perform the following commands to load the "Export Tables to LaTeX" or "HTML" package: install.packages("xtable") followed by: library("xtable"). Using an appropriate command from the xtable package, export Sales to an *.html file. Name the file "Sales.html."
- Objectives– Demonstrate use of associative arrays- Demonstrate knowledge of use of $_GET super global variable in data validation- Demonstrate handling of missing data in $_GETPHP $_GET is a PHP super global variable that can be used to collect form data after submitting an HTML form with method="get". The PHP $_GET super global variable can be used to collect data sent in the URL.Task: You will modify given code, part-2.php, to collect a course number and display its title. For instance, user will click on the hyperlink CSIS152, and this will cause the corresponding title “Introduction to Computers and Programming I-a”, to be displayed.1. Create an associative array, to reflect data in the following table. Store the array in a variable called $electives. (see pages 44 and 45 in course text) Key Value CSIS-335 Graphical User Interface Programming SIS-336 C#.Net Programming CSIS-341 System and Network Administration CSIS-360 Linux Programming and…This exercise allows a user to load one of two CSV files and then perform histogram analysis and plots for select variables on the datasets. The first dataset represents the population change for specific dates for U.S. regions. The second dataset represents Housing data over an extended period of time describing home age, number of bedrooms and other variables. The first row provides a column name for each dataset. The following columns should be used to perform analysis: PopChange.csv: Pop Apr 1 Pop Jul 1 Change Pop Housing.csv: AGE BEDRMS BUILT ROOMS UTILITY Notice for the Housing CSV file, there are more columns in the file than are required to be analyzed. You can and should still load each column. Specific statistics should include: Count Mean Standard Deviation Min Max Histogram A user interface might look similar to this: ***************** Welcome to the Python Data Analysis App********** Select the file you want to analyze: 1. Population Data 2.…TODO 11 Using the clean_df split our columns into features and labels. Index/slice our label 'area' and store the output into the variable y. Index/slice all other features EXCEPT 'area' into the variable X. To do so you can use the Pandas DataFrame drop() method or slicing with iloc, loc or [ ]. #TODO 11.1 # TODO 11.2X = display(X) todo_check([ (X.shape == (517, 29), 'X does not have the correct shape of (517, 29)! Make sure the `area` column is not included!'), (np.all(np.isclose(X.values[-5:, -4], np.array([27.8, 21.9, 21.2, 25.6, 11.8]),rtol=.01)),'X has the incorrect values'),])
- • Use the provided ViewController.swift file to programmatically add, constrain, and implement a UITableView using AstrologicalSign.allCases as a data set. // HINT: - Create an Xcode project to complete and test your work. This is an Xcode swift project, please show the codes, thank you.Data Frame: my code import numpy as npimport pandas as pdnp.random.seed(1)import datetimetoday = datetime.date.today()someday = datetime.date(2016, 1, 1)diff = today - somedayrows,cols = diff.days,6data = np.random.rand(rows,cols) tidx = pd.date_range('2016-01-01', periods=rows, freq='D')data_frame = pd.DataFrame(data, columns=['a','b','c','d','e','f'], index=tidx)print(data_frame) Question - Plot the six sets of row values of df_accumulate in separate graphs using subplots , then plot the accumulate sum of each of the columns (random numbers).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,…