data science cycle

The Data Science Cycle

Steps in order:

1. Problem Formulation

2. Getting Data

3. Exploring Data

4. Analysing Data

5. Communicating Results

Problem Formulation

Start with questions or explore data to find patterns

Getting Data

Import CSV (Comma-Separated Values) files and clean up messy/missing data

Exploring Data

Look for patterns and create basic plots to understand your data

Analyzing Data

Find connections between variables and test your questions

Communicating Results

Create clear visuals and explain findings for your audience

.read_csv()

Import CSV files into Python

.describe()

Get quick statistics about your data

.groupby()

Organize data by categories for comparison

catplot()

Create plots to compare different categories like box plots

displot()

Show how data is distributed using histograms

relplot()

Make plots showing relationships between feature