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).

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).

New Perspectives on HTML5, CSS3, and JavaScript

6th Edition

ISBN:9781305503922

Author:Patrick M. Carey

Publisher:Patrick M. Carey

Chapter7: Designing A Web Form: Creating A Survey Form

Section: Chapter Questions

Problem 5CP1

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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).
show each element with visualise
def custom_transform(data): """ Transform the `spiral.csv` data such that it can be more easily classified. To pass test_custom_transform_hard, your transformation should create at most three features and should allow a LogisticRegression model to achieve at least 90% accuracy. You can use free_response.q2.visualize_spiral() to visualize the spiral as we give it to you, and free_response.q2.visualize_transform() to visualize the 3D data transformation you implem
Show with an example how flex layout is different from horizontal and vertical box layout. The example must show the implementation of views, images and textinputs.
Complete the docstring using the information attached (images):def upgrade_stations(threshold: int, num_bikes: int, stations: List["Station"]) -> int: """Modify each station in stations that has a capacity that is less than threshold by adding num_bikes to the capacity and bikes available counts. Modify each station at most once. Return the total number of bikes that were added to the bike share network. Precondition: num_bikes >= 0 >>> handout_copy = [HANDOUT_STATIONS[0][:], HANDOUT_STATIONS[1][:]] >>> upgrade_stations(25, 5, handout_copy) 5 >>> handout_copy[0] == HANDOUT_STATIONS[0] True >>> handout_copy[1] == [7001, 'Lower Jarvis St SMART / The Esplanade', \ 43.647992, -79.370907, 20, 10, 10] True """
Create Second Image Use the following x_fit and y_fit data to compute z_fit by invoking the model's predict() method. This will allow you to plot the line of best fit that is predicted by the model. Any dataset would be good. Just want to understand it. Please use the same format below that I am using so I can follow along with your explanation. CODE GIVEN from mpl_toolkits import mplot3d from matplotlib.ticker import LinearLocator, FormatStrFormatter %matplotlib inline %matplotlib notebook x_fit = np.linspace(-21,21,1000) y_fit = x_fit x_fit = x_fit.reshape(-1,1) y_fit = y_fit.reshape(-1,1)
Please. need help with this. I attached how the final image should look There are two logic errors in setting up the global constants. Locate and fix those errors. Go to the calcTotal() To guard against users entering a zero or negative value for the estimated weight, replace the statement totalCost += wgtBox.value * COST_PER_LB; with a try catch statement that does the following: 0. Tests whether wgtBox.value is not greater than 0 by using the expression ! (wgtBox.value > 0). If that expression is true, throw an exception with the error message “!! Enter a positive weight” If no exception is thrown then run the command totalCost += wgtBox.value * COST_PER_LB;. If an exception is caught, set the value of msgBox. inner HTML to the error message you defined for the thrown exception. Repeat Step 5, for the estimated distance…
Create an interactive sign-up sheet.● Make the sign-up sheet interactive for the user.● Add a selection element to ask the user for their gender. Add the options “Male,” “Female,” and “Prefer not to mention.”● Use onblur and onfocus to add red borders to the input elements when the user leaves without any input, and a green border if a value is typed and the user is done with the input element.● Upon submission of the form, print all the information that the user has provided on a div or p tag at the bottom of the page.● Use fieldset and legend tag to separate the input part from the output part of the form.● Include a reset button to clear users input and also the information displayed at the bottom of the page.● Feel free also to design your own version and add other features.
Please help me fix the code Make it like the first picture(expect). And show the step 16-19 Thank you
. Write down the code for Image Slideshow and insert buttons for “Previous” and “Next” pictures to the left and right of the main picture respectively.
Area in the grey can not be edited. (lines 1-6) and (lines 13 - 18 or end of code).
Please do not give solution in image format thanku Finally, create a table with three columns. The first column should be your X, also known as the flipper_length_mm column from your cool_penguins table. The second column should be your Y, also known as the body_mass_g column from your cool_penguins table. The third column will be something you create. It should be called predicted_body_mass_g. Using the slope and intercept that you have calculated, compute the estimated body mass using the flipper_length_mm as the predictor variable. HINT 1: Look at Q12 of HW4 to see how you computed the regression line HINT 2: What you produced in that question (predicted_rnaseq) is an array of predicted numbers. How do you add an array of numbers to a table as a column? In [21]: # While it's possible to do this in one line, breaking this problem into steps might be more helpful!prediction = ...prediction.show(5)