Prerequisite: Basic programming knowledge in Python.

Here is the link to the notebook: Practical Notebook

Data Set: https://github.com/Barde-S/Tax-Trip/blob/main/taxi_trip_pricing.csv

Session Outline

Overview of what to learn

• [x] Exploring Patterns.
• [x] Data Cleaning.
• [ ] Data Transformation

Classical CS Quote:

"Garbage in, garbage out" – emphases on the impact of the quality of data.

• Exploratory Data Analysis (EDA)
• Data Preprocessing

Hands-on Learning

Requirement:

1. Jupyter Notebook or other Environments (Google Colab, Kaggle) [Anaconda]
2. Pandas: For data manipulation.