Not choosing the right data structure - Python Tutorial

Contents

• Introduction Introduction

  • Avoiding common Python mistakes

    39s
  • Getting the most from this course

    55s
• 1. Avoid Mistakes in Coding Practices 1. Avoid Mistakes in Coding Practices

  • Not writing comments

    3m 11s
  • Not organizing your directory

    3m 11s
  • Not testing

    2m 36s
  • Not sharing data referenced in code

    1m 10s
  • Hard coding inaccessible paths

    3m 10s
  • Name clashing with Python standard library

    2m 26s
  • Not importing relevant libraries and modules

    43s
  • Naming vaguely

    1m 51s
• 2. Avoid Mistakes in Structuring Code 2. Avoid Mistakes in Structuring Code

  • Modifying a list while iterating over it

    2m 14s
  • Using for loops instead of vectorized functions

    3m 48s
  • Using class variables vs. instance variables

    4m 2s
  • Calling functions before defining

    1m 40s
  • Creating circular dependencies

    1m 34s
• 3. Avoid Mistakes in Handling Data 3. Avoid Mistakes in Handling Data

  • Not choosing the right data structure

    2m 22s
  • Skimming data

    2m 1s
  • Not using the right visualization type

    1m 15s
  • Not addressing outliers

    1m 23s
  • Not updating your dataset

    1m 30s
  • Not cleaning data

    1m 20s
• 4. Avoid Mistakes in Machine Learning 4. Avoid Mistakes in Machine Learning

  • Using features that will be unavailable later

    1m 31s
  • Using redundant features

    1m 45s
• Conclusion Conclusion

  • Get started with Python

    1m 7s