Misc

Misc

• Random Seed

  import random
  random.seed(12)
  
  random.sample([1,2,3,4,5], 2)
  #> [4,3]

Big Data

• {{datatable}}

  • Misc

    • Resources
      • An Overview of Python’s DataTable

  • fread  for fast loading of large datasets

    import datatable as dt  # pip install datatable
    tps_dt = dt.fread("data/tps_september_train.csv").to_pandas()

• For other options (e.g. Dask, Vaex, or cuDF) see this Kaggle notebook
• {{cuDF}}
  • Docs, Beginner’s tutorial
  • Useful for extreme data sizes (e.g. 100s of billions of rows)
  • similar to pandas syntax
• {{vaex}}
  • Docs
• {{dask}}
  • See MLOps >> Dask

Functions

• Suppress warnings

  import warnings
  warnings.filterwarnings("ignore")

• match/case

  • Similar to switch in R (See R, Base R >> Functions>> switch

  • Example (source)

    def show_options(options: dict|str, str|) -> None:
      for key, value in options.items():
        print(f"{key}: {value}")
      print()
    
    def main():
      options = {"1": "Add Item", "2": "Delete Item", "3": "View Item", "4": "Exit"}
      while True:
        show_options(options)
        selected_option = input("Choose an option: ")
    
        match selected_option:
          case "1":
            print("Add item logic here")
            # implement add item logic
          case "2":
            print("Delete item logic here")
            # implement view item logic
          case "3":
            print("View item logic here")
            # implement view item logic
          case "4":
            print("Goodbye!")
            break
          case _:
            print("Invalid option, please try again")
            continue