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Download Excel File with Dummy Data




If you are working on a project that involves data analysis, you may need to use some dummy data to test your formulas, functions, charts, or reports. Dummy data is mock data generated at random as a substitute for live data in testing environments. In this article, you will learn what dummy data is, why it is useful, how to create it in Excel, and how to download it from a website.


What is Dummy Data and Why Use It?




Dummy data is fake data that mimics the characteristics of real data. For example, if you want to test a sales report, you may need some dummy data that contains product names, prices, quantities, dates, and customer details. You can use dummy data to fill in the gaps in your real data, or to create a completely new data set for testing purposes.




download excel file with dummy data


Download File: https://www.google.com/url?q=https%3A%2F%2Ft.co%2FwTZ9jZ6Ysy&sa=D&sntz=1&usg=AOvVaw3-20Ajpg7JlK_zyXQy-CZy



Definition and Examples of Dummy Data




According to Analyst Answers, dummy data is mock data generated at random as a substitute for live data in testing environments. It acts as a placeholder for live data, which testers only introduce once they are sure that the trial program does not have any negative impact on the underlying data.


For example, suppose you have the following dataset and you want to use age and marital status to predict income:


NameAgeMarital StatusIncome


Alice25Single$40,000


Bob32Married$60,000


Charlie28Divorced$50,000


David35Single$70,000


Eve30Married$55,000


To use marital status as a predictor variable in a regression model, you need to convert it into a dummy variable. Since it is currently a categorical variable that can take on three different values (Single, Married, or Divorced), you need to create k-1 = 3-1 = 2 dummy variables. To create this dummy variable, you can let Single be your baseline value since it occurs most often. Heres how you would convert marital status into dummy variables:


NameAgeMarital StatusIncomeMarried (Dummy)Divorced (Dummy)


Alice25Single$40,00000


Bob32Married$60,00010


Charlie28Divorced$50,00001


David35Single$70,00000


Eve30Married$55,00010


Now you have two dummy variables that represent the marital status of each person. You can use these dummy variables in your regression model along with age to predict income.


Benefits of Using Dummy Data for Testing




Using dummy data for testing has several advantages, such as:


  • It allows you to test your formulas, functions, charts, or reports without affecting the real data.



  • It helps you identify any errors or bugs in your code or logic before applying it to the real data.



  • It enables you to simulate different scenarios and outcomes by changing the values or characteristics of the dummy data.



  • It saves you time and resources by avoiding the need to collect or generate real data for testing purposes.



How to Create Dummy Data in Excel




There are many ways to create dummy data in Excel, depending on the type and format of the data you need. Here are two common methods that you can use to create dummy data in Excel:


Using RANDBETWEEN Function




The RANDBETWEEN function returns a random integer between two specified values. You can use this function to create dummy data for numerical variables, such as prices, quantities, scores, etc. For example, if you want to create a dummy data set of 10 products with random prices between $10 and $100, you can use the following formula:


=RANDBETWEEN(10,100)


This formula will generate a random number between 10 and 100 in each cell where you enter it. You can copy and paste this formula to create as many rows or columns as you need. Here is an example of a dummy data set created using this formula:


How to download excel file with dummy data for testing


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Product NamePrice


Product A$54


Product B$23


Product C$87


Product D$45


Product E$76


Product F$12


Product G$34


Product H$98


Product I$67


Product J$41


Using VLOOKUP Function




The VLOOKUP function returns a value from a table based on a lookup value and a column index number. You can use this function to create dummy data for categorical variables, such as names, countries, colors, etc. For example, if you want to create a dummy data set of 10 customers with random names and countries, you can use the following steps:



  • Create a table with two columns: one for names and one for countries. You can use any source of names and countries that you like, such as online lists or databases. Here is an example of a table created using random names and countries from and :




NameCountry


Aaron SmithAustralia


Betty JonesBrazil


Charles LeeChina


Diana PerezMexico


Ethan BrownNew Zealand


Fiona TaylorCanada


Gregory WilsonGermany


Hannah MillerIndia


Ian ClarkJapan


Jennifer DavisUSA


  • Name this table as "Name_Country" by selecting the range of cells and typing the name in the Name Box on the left of the formula bar.



  • Create another table with two columns: one for customer ID and one for customer name. You can use any sequence of numbers for the customer ID, such as 1, 2, 3, etc. For the customer name, you can use the following formula:



=VLOOKUP(RANDBETWEEN(1,10),Name_Country,1,FALSE)


This formula will generate a random number between 1 and 10 and use it as a lookup value to find a matching name from the Name_Country table. The formula will return the name from the first column of the Name_Country table. You can copy and paste this formula to create as many rows as you need. Here is an example of a dummy data set created using this formula:



Customer IDCustomer Name


1Ethan Brown


2Betty Jones


3Aaron Smith


4Jennifer Davis


5Hannah Miller


6Diana Perez


7Ian Clark


8Fiona Taylor


9Charles Lee


10 Gregory Wilson


  • To create a dummy data set of 10 customers with random countries, you can use a similar formula, but change the column index number from 1 to 2. For example:



=VLOOKUP(RANDBETWEEN(1,10),Name_Country,2,FALSE)


This formula will return the country from the second column of the Name_Country table. Here is an example of a dummy data set created using this formula:



Customer IDCustomer Country


1 New Zealand


2 Brazil


3 Australia


4 USA


5 India


6 Mexico


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