1. Using the values on the Data worksheet, create a column chart. 2. Change the column chart so it uses the Year values in cells A3:A9 as the horizontal (category) axis values, and the Volume values in cells B3:B9 as the vertical axis values. 3. Using the same set of values, create a line chart. 4. Using the Quick Analysis Lens, create a pie chart from the same data..
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1. Using the values on the Data worksheet, create a column chart. 2. Change the column chart so it uses the Year values in cells A3:A9 as the horizontal (category) axis values, and the Volume values in cells B3:B9 as the vertical axis values. 3. Using the same set of values, create a line chart. 4. Using the Quick Analysis Lens, create a pie chart from the same data..
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- 1. Load the tidyverse package first and then explore the diamonds dataset. What’s the average price of premium cut diamonds in the diamonds dataset? 2. Which is true about mutate() and transmute()? Select all the correct answers. Group of answer choices: A. They both create new columns that are based upon existing columns. B. mutate(flights, gain = dep_delay - arr_delay, speed = distance / air_time * 60) and transmute(flights, gain = dep_delay - arr_delay, hours = air_time / 60, gain_per_hour = gain / hours) returns the same output. C. If you only want to keep the new variables that you have created, use transmute() instead of mutate(). No hand written and fast answer with explanationLoad & check the data:1. Load the data into a pandas dataframe named data_firstname where first name is you name.2. Carryout some initial investigations:a. Check the names and types of columns.b. Check the missing values.c. Check the statistics of the numeric fields (mean, min, max, median, count..etc.)d. In you written response write a paragraph explaining your findings about each column.Pre-process and visualize the data3. Replace the ‘?’ mark in the ‘bare’ column by np.nan and change the type to ‘float’4. Fill any missing data with the median of the column.5. Drop the ID column6. Using Pandas, Matplotlib, seaborn (you can use any or a mix) generate 3-5 plots and add themto your written response explaining what are the key insights and findings from the plots.7. Separate the features from the class.8. Split your data into train 80% train and 20% test, use the last two digits of your student numberfor the seed.Build Classification ModelsSupport vector machine classifier with…Load & check the data:1. Load the data into a pandas dataframe named data_firstname where first name is you name.2. Carryout some initial investigations:a. Check the names and types of columns.b. Check the missing values.c. Check the statistics of the numeric fields (mean, min, max, median, count..etc.)d. In you written response write a paragraph explaining your findings about each column.Pre-process and visualize the data3. Replace the ‘?’ mark in the ‘bare’ column by np.nan and change the type to ‘float’4. Fill any missing data with the median of the column.5. Drop the ID column6. Using Pandas, Matplotlib, seaborn (you can use any or a mix) generate 3-5 plots and add themto your written response explaining what are the key insights and findings from the plots.7. Separate the features from the class.8. Split your data into train 80% train and 20% test, use the last two digits of your student numberfor the seed.Build Classification ModelsSupport vector machine classifier with…
- Load & check the data:1. Load the data into a pandas dataframe named data_firstname where first name is you name.2. Carryout some initial investigations:a. Check the names and types of columns.b. Check the missing values.c. Check the statistics of the numeric fields (mean, min, max, median, count..etc.)d. In you written response write a paragraph explaining your findings about each column. Pre-process and visualize the data3. Replace the ‘?’ mark in the ‘bare’ column by np.nan and change the type to ‘float’4. Fill any missing data with the median of the column.5. Drop the ID column6. Using Pandas, Matplotlib, seaborn (you can use any or a mix) generate 3-5 plots and add them to your written response explaining what are the key insights and findings from the plots.7. Separate the features from the class.8. Split your data into train 80% train and 20% test, use the last two digits of your student number for the seed. Build Classification ModelsSupport vector machine classifier with…Load & check the data:1. Load the data into a pandas dataframe named data_firstname where first name is you name.2. Carryout some initial investigations:a. Check the names and types of columns.b. Check the missing values.c. Check the statistics of the numeric fields (mean, min, max, median, count..etc.)d. In you written response write a paragraph explaining your findings about each column.Pre-process and visualize the data3. Replace the ‘?’ mark in the ‘bare’ column by np.nan and change the type to ‘float’4. Fill any missing data with the median of the column.5. Drop the ID column6. Using Pandas, Matplotlib, seaborn (you can use any or a mix) generate 3-5 plots and add themto your written response explaining what are the key insights and findings from the plots.7. Separate the features from the class.8. Split your data into train 80% train and 20% test, use the last two digits of your student numberfor the seed.Build Classification ModelsSupport vector machine classifier with…As a university instructor, charts are very useful to show statistical analysis of test scores to students. Students are always interested in how they scored compared to the whole class or where their score landed in the overall scheme of things. Which type of statistics would be most useful for comparisons? Which type of chart would be best to show the comparison of grades? How do charts help protect the privacy of individual grades?
- Unique Answer only Based on the dataset information given above, please answer the following questions. You are required to perform the following tasks using R Studio. Please provide the script and screenshot of the output. Q. If you want to see the 1st Quartile, Median, and 3rd Quartile of DiabetesPedigreeFunction, which plot is suitable to visualize these three pieces of information? Visualize the plot with an appropriate header and label.1. Create table of excel and name it as sales.xlsx. 2. By using excel form entry function, add (3) new entry of any item(s) bought by Ali (1-1-1999), Abu (2-1-1999) and Ahmad (3-1-1999) individually. 3. Create a PivotTable, place it on the same worksheet and name it as Sales.I'm using MySQL workbench Is the questions I have done correct? 1-Display the addresses of all the departments. Show locationID, street address,city,state and country name in the-- output. (Use Locations table) SELECT l.ID, L.ADDRESS, L.CITY, L.STATE, L.COUNTRY FROM Locations L, DEPARTMENTS D WHERE L.ID= D.LOCATION_ID;-- 2-Display the last name, department number and deparment name for all employees.SELECT E.last_name, E.department, D.DEPARTMENT_NAMEFROM employees E,departments DWHERE E.DEPARTMENT_ID = D.DEPARTMENT_ID; -- 3-Display the last name, job, department number, and department name for all employees work in-- Toronto. (Employees,Departments,Locations)SELECT e.LAST_NAME, e.JOB_ID, e.DEPARTMENT_ID, d.DEPARTMENT_NAMEFROM EMPLOYEES e, DEPARTMENTS d, LOCATIONS lWHERE e.DEPARTMENT_ID = d.DEPARTMENT_IDAND d.LOCATION_ID = l.LOCATION_IDAND UPPER(l.CITY) = 'TORONTO';-- 4-Display employees' last name and employee number along with their manager's last name and manager number.-- Label the…
- which statement best describes data visualization? a. data visualization was created to help accessibility issues b. data visualization is one way we share the story c. data visualization helps users understand a UML diagram d. data visualization is the way we input data into tablesLook at the geospatial visualizations in the CDC COVID Data Tracker website. What types of geospatial visualizations (in light of the types introduced in the Week 4 Lecture) do you see there? Do you think if these are right types for the visualized content? There are several choropleth maps there. Can these maps be replaced by heatmaps? What are the advantages and disadvantages if a choropleth map is used versus a heatmap?Based on the ERD in the above case:1. Apply 1NF, 2NF, and 3NF Normalization. Then picturereset ERD after normalization. NOTE ***Please, this is just one question, please do it properly and correctly and please don't give wrong answers and copy and paste other expert answers if you give wrong answers and wrong copy answers from other experts I have to downvote and report***