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      CS39A0190代做、代寫Python,Java程序

      時間:2024-01-29  來源:合肥網hfw.cc  作者:hfw.cc 我要糾錯



      ASSIGNMENT 2 INSTRUCTIONS
      CS39A01** Data analytics basics
      ”DATASETS”-file has three sheets. First sheet ”DATASET1” is its own task and sheets two
      and three, ”DATASET2_1” and ”DATASET2_2” are another one.
      The datasets needs to be cleaned before they can be analysed. You can turn the data into
      table or keep as a range, whichever you find easier to work with.
      DATASET1 basic info
      The data is process data where Events go through a process from A to G.
      Process step colums A to G have dates as data. The date depicts when the process step began. Process
      step G means completion of the whole process.
      DATASET2 basic info
      The data is sales data for product range. SKU (stock keeping unit) is assigned to each unique product.
      Agency depicts a retailer. Volume is the amount sold during the time and average max temp describes
      the temperature at the retailer for the sales period.
      DATASETS
      Cleaning the data
      Remove empty rows.
      Remove incomplete Event records. Every process step must have a date.
      Remove duplicate Event records. Each Event ID is unique.
      If Excel does not recognize the process step data as dates, convert the cell contents into dates.
      Event IDs and Event types are numbers by format.
      Analysing the data
      Calculate the duration (in days) between each process step and the total duration for all Events.
      Calculate the average duration between each process step and the average total process duration for all
      Event types.
      Example for a single Event:
      DATASET1 – 3 POINTS
      First, use Text to Columns to get the comma separated data into separate columns.
      Cleaning the data
      Both DATASET2_1 and DATASET2_2 sheets have a column that uses dot as a decimal separator. If your
      Excel has comma as a decimal separator, convert the dots to commas.
      Check for duplicates, missing data, empty rows... and handle accordingly if found.
      Analysing the data
      Add the Avg_Max_Temp data from DATASET2_2 to DATASET_1. See example below.
      Calculate monthly total sales (all SKUs) for each Agency.
      Calculate annual total sales for each SKU.
      DATASET2 – 3 POINTS
      Data is from Eurostat, population data. Actual national population data from 2021 and
      projections for 2022-2100.
      Projections has multiple scenarios in separate sheets.
      Your task is to combine the data for EU countries + Iceland, Norway and Switzerland (30
      countries in total).
      Open a blank Excel spreadsheet and connect to both of the Excel files to get data.
      Clean the data, merge the datasets, and clean the merged data if necessary.
      You will return results only for the 30 countries.
      As a result, you will have for each country a 2021 actual population (total, males, and
      females) and projections for 2022-2100 (total, males, and females).
      From projections, use two scenarios. Baseline and a free choice for the second.
      POWER QUERY – 6 POINTS
      Find two datasets (from anywhere) that you can connect to and combine in Power Query.
      Use two different sources for the data.
      E.g., one from CSV and one from Web
      Clean the data using Power Query and combine them into one dataset.
      FIND AND MERGE – 3 POINTS
      Return three Excel-files.
      DATASETS
      POWER QUERY
      FIND AND MERGE
      All used functions and Queries must remain in the submitted files. Being able to see the
      data transformation process in the files is more important than the end result.
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