Lab4: R Basics

1 Generate Data frame

Suppose you are a data scientist, and you get a project at a start-up company, for instance Kopi Kenangan. Let’s say, you are asking to generate the collection of any possible data set from their daily sales. If I asking you: what kind of data set that you can generate?. Here, I assume you want to provide them the following data set:

• Id : there are 5000 transactions.
• Date: daily 5000 transactions, start from 2018/01/01.
• Name: create 20 random cashier names (you can use names of your classmate including your self) to cover all 5000 transactions at Kopi Kenangan.
  
• City: allocate this 5000 transactions to the biggest cities in Indonesia (with the same proportion). Here I assume,
  • Jakarta
  • Bogor
  • Depok
  • Tangerang
  • Bekasi
• Outlet: allocate this 5000 transactions in five outlets. Here I assume,
  • Outlet 1
  • Outlet 2
  • Outlet 3
  • Outlet 4
  • Outlet 5
• Menu: generate random sales of 5000 menu items at Kopi Kenangan every day. Here, I assume,
  • Cappucino
  • Es Kopi Susu
  • Hot Caramel Latte
  • Hot Chocolate
  • Hot Red Velvet Latte
  • Ice Americano
  • Ice Berry Coffe
  • Ice Cafe Latte
  • Ice Caramel Latte
  • Ice Coffee Avocado
  • Ice Coffee Lite
  • Ice Matcha Espresso
  • Ice Matcha Latte
  • Ice Red Velvet Latte
• Price: generate random prices (min=18000, and max=45000)
• Discount: generate random discounts (min=0.05, and max=0.12)

2 Extraction

In this section, you are expected be able to apply a very basic data frame manipulation called Extraction. Please cover the following tasks:

• Extract all data set or transactions at Kopi Kenangan, in the specific city for instance Jakarta.

• Extract all data set or transactions at Kopi Kenangan, in the specific menu for instance Hot Chocolate.

• Extract all data set or transactions at Kopi Kenangan, in the specific cashier names for instance Bakti Siregar.

• Extract all data set or transactions at Kopi Kenangan, in the specific price for instance >=40000.

• Add a new variable, call Total_Price to your data frame (data frame that you have done above)

• Add a new variable, call Category_Price to your data frame (data frame that you have done above), Here, I assume: “expensive”, “so-so”, and “cheap”.

3 Renames Data Frame

Please rename all variables of your data frame (data frame that you have done above) in your language.

4 Case Study

According to your data frame, please provide me the following tasks:

• Find out the frequency of sales of which menu items are best-selling at Kopi Kenangan Company!

• Find out which city got the most sales at Kopi Kenangan Company!

• Find out which city has the most discounted sales at Kopi Kenangan Company!

• Which year were the most sales at Kopi Kenangan Company?