Question Aapython please for the commented steps. ✓OsOsExploring and Visualizing The DataExploring your data using different types of visualizations is always a good practice when doing EDA.You'll start by plotting a histogram of the target column (w) so you can see the distribution of wins.[79][ ][]1 #importing matplotlib23 import matplotlib.pyplot as plt4 %matplotlib inline.56 #### the statement below ask matplotlib to use the 'ggplot' style7 #### you should consider using that8plt.style.use('ggplot')1 #### Complete your code below2 #### create a histogram `hist()` over the column `df [ 'W']`34 #### adding elements to your visualization to increase the readability5 #### you should always have title and axis name (s) in your visualization6 #### name your x-axis label as `Wins`789 #### name your visualization title as `Distribution of Wins`101112 #### show your visualization131 #### We can also check the descriptive stats of `df [ 'W']` using `.describe()2

1 # create histogram2 plt.hist(df['W'], bins=10)34 # add x-axis label5 plt.xlabel('Wins')67 # add…

Exploring and Visualizing The Data Exploring your data using different types of visualizations is always a good practice when doing EDA. You'll start by plotting a histogram of the target column (w) so you can see the distribution of wins. [79] 1 #importing matplotlib

Exploring and Visualizing The Data Exploring your data using different types of visualizations is always a good practice when doing EDA. You'll start by plotting a histogram of the target column (w) so you can see the distribution of wins. [79] 1 #importing matplotlib

COMPREHENSIVE MICROSOFT OFFICE 365 EXCE

1st Edition

ISBN:9780357392676

Author:FREUND, Steven

Publisher:FREUND, Steven

Chapter8: Working With Trendlines, Pivottables, Pivotcharts, And Slicers

Section: Chapter Questions

Problem 8EYW

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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…
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# Create Custom Transformer Create a custom transformer, just as we did in the lecture video entitled "Custom Transformers", that performs two computations: 1. Adds an attribute to the end of the numerical data (i.e. new last column) that is equal to $\frac{x_1^3}{x_5}$ for each observation. In other words, for each instance, you will cube the $x_1$ column and then divide by the $x_5$ column. 2. Drops the entire $x_4$ feature column if the passed function argument `drop_x4` is `True` and doesn't drop the column if `drop_x4` is `False`. (See further instructions below.) You must name your custom transformer class `Assignment4Transformer`. Your class should include an input parameter called `drop_x4` with a default value of `True` that deletes the $x_4$ feature column when its value is `True`, but preserves the $x_4$ feature column when you pass a value of `False`. This transformer will be used in a pipeline. In that pipeline, an imputer will be run *before* this transformer. Keep…
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plz run in r studio n answer all the questions biostats........ Worksheet T tests, Wilcoxon’s test, Mc Nemar’s TestAnswer the following questions using R studio and submit the MSword format from via Moodle.1. Test whether the marginal probabilities are the same or differentfor the following dataset. Create the dataset by using the followingScripts:> set.seed(50)>data <- data.frame(before = sample(c("Positive", "Positive", "Positive", "Positive", "Negative"), 250, replace = TRUE), after = sample(c("Positive", "Positive", "Positive", "Positive", "Negative"), 250, replace = TRUE))>dataNote: Prepare a contingency table using the table function, beforechoosing and running your analysis.2. The following data were recorded as independent observationsfor heights (cm) of Guava Plants treated with NPK nutrients. Wewant to know, if the average height of the these plants statisticallydiffers from 19 cm?18.50, 18.55, 18.60, 18.65, 18.70, 18.75, 18.80, 18.85, 18.90,18.95, 19.00,…
Using the Pandas DataFrame isnull() function, convert our forestfire_df to a boolean DataFrame (here true indicates an element is a missing value) (docs). Put the result in the forestfire_isnull variable. # TODO 1.1 forestfire_isnull = display(forestfire_isnull) todo_check([ (forestfire_isnull.shape == (517,13),"forestfire_isnull shape does not match (517, 13)"), (np.all(forestfire_isnull.iloc[10:20,0].values == np.array([False,False,False,False,False,False,False,False,False,False])),"The values of forestfire_isnull were incorrect!") ])
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.
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 11.1y = display(y) todo_check([ (y.shape == (517,), 'y does not have the correct shape of (517,)'), (np.all(np.isclose(y.values[-5:], np.array([2.00687085, 4.01259206, 2.49815188, 0. , 0. ]),rtol=.01)),'y has the incorrect values'),]) # 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'),])
Ap is of the Apple type, and the only values it may be assigned (or contain) are those described by the enumeration. This, for example, ap = Apple.RedDel; Create code
What function does this Syntax perform? function myMap() {var map Canvas = document.getElementById("map");var mapOptions = {center: new google.maps.LatLng(51.5, -0.2),zoom: 10};var map = new google.maps.Map(mapCanvas, mapOptions);}
Write a PHP script to do the following: Create the following two dimensional array $students: ID Name Score 100 Ali 76 200 Khaleed 33 300 Fatema 89 400 Sumaya 45 Use foreach to display the array $students in an HTML table. Display the number of pass and fail students (pass if the score is greater than 50 and fail otherwise).
Python Language Item 2 [hint: use linspace and meshgrid to generate a gridded coordinates] I want you to create random sampling (10 sets, 500 random points from -20 to 20) first z1-value: use the 2D gaussian formula to get the z second z2-value: use the interpolation using x&y random points as query points xi Task1: then compare (% diff) between z1 and z2 for each set. Task2: then compare (% diff) between z1 and z2 average of the 10 sets. Task3: using the averaged value of z1-values, interpolate it onto a new grid with the size of 50x50 grid and plot the result. Task4: plot individually all the random samplings for z1 and z2 ------------------------------------------------ I did a code for this but it runs "error" , how do you fix this?