Python Data Analytics Portfolio

The repository demonstrates practical experience with data cleaning, exploratory analysis, visualization, customer segmentation, predictive analytics, and geospatial analysis using real-world datasets.

Tech Stack

• Python
• Pandas
• NumPy
• Plotly
• Jupyter Notebook

Topics Covered

• Data cleaning & preprocessing
• Exploratory Data Analysis (EDA)
• Interactive visualizations
• Time series analysis
• Customer segmentation (RFM)
• Cohort analysis
• A/B testing
• Linear & Logistic Regression
• K-Means Clustering
• Geospatial analysis

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How to Run

1. Clone this repository:

   git clone https://github.com/avetisyanna/python-analytics-portfolio.git

2. Extract the dataset:

import zipfile

with zipfile.ZipFile("../data/raw/Archive.zip", "r") as zip_ref:
    zip_ref.extractall("../data/raw")

3. Open the notebooks and explore the analyses.