Generating Mock Data with Python - NumPy, Pandas, and Datetime Libraries

Generating Mock Data with Python - NumPy, Pandas, and Datetime Libraries

Keith Galli via YouTube Direct link

- Intro & Background Info

1 of 13

1 of 13

- Intro & Background Info

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Generating Mock Data with Python - NumPy, Pandas, and Datetime Libraries

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  1. 1 - Intro & Background Info
  2. 2 - What we're creating in this video!
  3. 3 - Start writing code generating a simple dataframe & csv
  4. 4 - Task: Making our data more realistic, selecting some products with higher probability than others
  5. 5 - Task: Generate 12 months worth of data in 12 csvs calendar library, f-strings
  6. 6 - Make some months have more purchases than others
  7. 7 - Normal distributions in NumPy
  8. 8 - Improving speed of our code making testing easier
  9. 9 - Task: Generate random addresses for our data
  10. 10 - Task: Generate order times for purchases datetime library overview
  11. 11 - Using timedelta objects to add & subtract time from dates
  12. 12 - Generate a realistic quantity ordered for each product using numpy geometric distribution
  13. 13 - Add multiple items being more likely to be sold together and cleaning code a bit

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