Modify this code in to Mofify the code to display distribution of a continous variable like range of counts and percentage import matplotlib.pyplot as plt # Sample data referral_sources = ['Website', 'Word of Mouth', 'Advertisement', 'Social Media'] counts = [250, 400, 300, 350] plt.bar(referral_sources, counts) plt.title('Referral Sources Count') plt.xlabel('Referral Source') plt.ylabel('Count')

Modify this code in to Mofify the code to display distribution of a continous variable like range of counts and percentage import matplotlib.pyplot as plt # Sample data referral_sources = ['Website', 'Word of Mouth', 'Advertisement', 'Social Media'] counts = [250, 400, 300, 350] plt.bar(referral_sources, counts) plt.title('Referral Sources Count') plt.xlabel('Referral Source') plt.ylabel('Count')

Oracle 12c: SQL

3rd Edition

ISBN:9781305251038

Author:Joan Casteel

Publisher:Joan Casteel

Chapter3: Table Creation And Management

Section: Chapter Questions

Problem 11MC

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def print_table( values: tuple[float, ) -> None: ], drag_coeff: float, increments: int, step: float 3 4 Parameters: 6 values (tuple[float, ...]): mass, force, ref_area, density, init_velocity, lift_velocity, start_position, time_inc drag_coeff (float): The drag coefficient. increments (int): The number of drag coefficients displayed. step (float): The difference between each drag coefficient. 8 9 10 11 12 Returns: 13 None 14 II II 15 For this function you need to compute the distance before lift-off for a range of drag coefficients and then you need to print these results in a table. The drag coefficient of an aeroplane has a significant impact on the plane's ability to lift-off. If the drag coefficient is sufficiently high, the plane will not actually be able to generate enough speed to lift off. In this task you will write a function which will explore this phenomenon.
The Movie table has the following columns: ID - positive integer Title - variable-length string Genre - variable-length string RatingCode - variable-length string Year - integer Write ALTER statements to make the following modifications to the Movie table: Add a Producer column with VARCHAR data type (max 50 chars). Remove the Genre column. Change the Year column's name to ReleaseYear, and change the data type to SMALLINT.
This dataset “Birthweight_reduced_kg_R" contains information on new born babies and their parents. In the following a description of each variable is given: Name Variable Baby number Length of baby (cm) Weight of baby (kg) headcirumference Head Circumference ID length Birthweight Gestation Gestation (weeks) smoker Mother smokes 1 = smoker 0 = non-smoker motherage Maternal age Number of cigarettes smoked per day by mother mnocig Mothers height (cm) Mothers pre-pregnancy weight (kg) Father's age mheight mppwt fage Father's years in education Number of cigarettes smoked per day by father fedyrs fnocig Father's height (kg) Low birth weight, 0 = No and 1 = yes Mother over 35, 0 = No and 1 = yes fheight lowbwt mage35 Task 1: Load the csv file into Python environment and get the required columns to be used as x and y. Task 2: Use correlation coefficient to find and discuss the following: 1. Relationship between maternal height and baby length. 2. Relationship between mother's pre-pregnancy…
3. In file 'R-Factor-Basics.docx', page 4, use the factor() command to modify the column dat$Group so that the control group is plotted last.e
JS-> // selecting required elementconst element = document.querySelector(".pagination ul");let totalPages = 10;let page = 2; //calling function with passing parameters and adding inside element which is ul tagelement.innerHTML = createPagination(totalPages, page);function createPagination(totalPages, page){ let liTag = ''; let active; let beforePage = page - 1; let afterPage = page + 1; if(page > 1){ //show the next button if the page value is greater than 1 liTag += <liclass=btn prevonclick=createPagination(totalPages, ${page - 1})><span><iclass=fas fa-angle-left><i>Prev<span><li>; } // how many pages or li show before the current li if (page == totalPages) { beforePage = beforePage - 2; } else if (page == totalPages - 1) { beforePage = beforePage - 1; } // how many pages or li show after the current li if (page == 1) { afterPage = afterPage + 2; } else if (page == 2) { afterPage = afterPage + 1; } for (var…
The constants are: COLUMN_ID = 0COLUMN_NAME = 1COLUMN_HIGHWAY = 2COLUMN_LAT = 3COLUMN_LON = 4COLUMN_YEAR_BUILT = 5COLUMN_LAST_MAJOR_REHAB = 6COLUMN_LAST_MINOR_REHAB = 7COLUMN_NUM_SPANS = 8COLUMN_SPAN_DETAILS = 9COLUMN_DECK_LENGTH = 10COLUMN_LAST_INSPECTED = 11COLUMN_BCI = 12 INDEX_BCI_YEARS = 0INDEX_BCI_SCORES = 1MISSING_BCI = -1.0 EARTH_RADIUS = 6371 This is an example of one of the bridges which is a list. def create_example_bridge_1() -> list:"""Return a bridge in our list-format to use for doctest examples. This bridge is the same as the bridge from row three of the dataset.""" return [1, 'Highway 24 Underpass at Highway 403','403', 43.167233, -80.275567, '1965', '2014', '2009', 4,[12.0, 19.0, 21.0, 12.0], 65.0, '04/13/2012',[['2013', '2012', '2011', '2010', '2009', '2008', '2007','2006', '2005', '2004', '2003', '2002', '2001', '2000'],[MISSING_BCI, 72.3, MISSING_BCI, 69.5, MISSING_BCI, 70.0, MISSING_BCI,70.3, MISSING_BCI, 70.5, MISSING_BCI, 70.7, 72.9, MISSING_BCI]]] def…
ggplot(data, aes(Month,Temp, fill = Month)) + ggtitle("Varying Temperatures thoughout the Months") + xlab("Months") + ylab("Temperatures") + geom_boxplot() How do I reorder/arrange the boxplot from least to most(lowest to Highest) using R
Json document: P = { "p": [ { "logType": “PDF, "accountId": “xxxx” }, { "logType": “PDF”, "accountId": “xxxx” }, { "logType": “PDF”, "accountId": “xxxx” }, { "logType": “PDF”, "accountId": “xxxx” }, { "logType": “PDF”, "accountId": “xxxx” } ] } Then, I want to count the total of logType and accountId like this in python { "logType": 5, "accountId": 5 }
The management of your team wants to compare the team with the assigned team (the Bulls in 1996-1998). They claim that the skill level of your team in 2013-2015 is the same as the skill level of the Bulls in 1996 to 1998. In other words, the mean relative skill level of your team in 2013 to 2015 is the same as the mean relative skill level of the Bulls in 1996-1998. Test this claim using a 1% level of significance. Assume that the population standard deviation is unknown. Make the following edits to the code block below: 1. Replace ??DATAFRAME_ASSIGNED_TEAM?? with the name of assigned team's dataframe. See Step 1 for the name of assigned team's dataframe. 2. Replace ??DATAFRAME_YOUR_TEAM?? with the name of your team's dataframe. See Step 2 for the name of your team's dataframe. 3. Replace ??RELATIVE_SKILL?? with the name of the variable for relative skill. See the table included in Project Two instructions above to pick the variable name. Enclose this variable in single quotes. For…
JAVA Script Create a form that has a last name, a first name, an email address, a drop-down listing of 10 cities in Massachusetts. The list is to be sorted (hint: think array), an email address, and a zip code field. Each field is to be process through a validation function. You may use one function for each but if you are creative you should be able to use just one function. The drop-down listing will not require validation because they will be choosing from a list that you are providing. This input from must be styled and show an effect to the user as to which field that are currently providing input.
PYTHON CODE Using Artists.csv (link below), write a query that returns all lines that are female artists only, with begin date greater than 1950 but no greater than 2000 Write a query that will return all lines of British Male artists, who's first names starts with the letter ‘A’ and has an end date earlier than 1990 Write a query that will write to a file all lines that have Japanese Artists who’s difference of end date and begin date exceeds 100 years. I.e. if artist begins in 1900 and ends in 2005, then they would be included in the output (2005-1900 = 105 years) Write a query that will write and find to a file the artist who’s been at the Museum the longest (the widest gap between Begin Date and End Date) Artists.csv: https://media.githubusercontent.com/media/MuseumofModernArt/collection/master/Artists.csv
The parameter represents converted station data for a single station. is_app_only The function should return True if and only if the given station requires the use of an app because it does NOT have a kiosk. Recall that a station requires the use of an app if and only ("Station") -> bool if the string that the constant NO_KIOSK refers to is part of its station name.