I will build an interactive streamlit data dashboard in python
AI and Data Science
About this Gig
Transform your raw dataset into actionable business intelligence with expert Data Analytics, Visualization, and Machine Learning services in Python.
Whether you need clean data processing, deep Exploratory Data Analysis (EDA), machine learning customer segmentation (K-Means), or an interactive web dashboard built with Streamlitthis gig delivers clear insights and clean, documented code to help you make smarter, data-driven decisions.
Key Deliverables:
- Cleaned & Processed Datasets (Handling missing values, outliers, and feature engineering).
- High-Resolution Custom Charts (Histograms, scatter plots, correlation heatmaps, and category breakdowns using Seaborn/Plotly).
- Machine Learning Segmentation (Customer profiling, clustering, and behavioral analysis).
- Interactive Web Dashboard (Built with Streamlit for real-time filtering, KPIs, and visual analytics).
- Complete Source Code (Fully commented Jupyter Notebooks .ipynb and Streamlit .app files).
My Portfolio
FAQ
Q1: What format should I provide my dataset in?
You can provide your data in CSV, Excel (.xlsx), TSV, JSON, or SQL format. If your data is in Google Sheets or a database, just grant access or provide an export.
Q2: Will I get the full Python source code?
Yes, absolutely! You will receive the fully commented Python Jupyter Notebook (.ipynb) and/or Streamlit app file (app.py), along with the cleaned CSV file.
What tools and libraries do you use for analysis and visualization?
I use Python, Pandas, and NumPy for data manipulation; Matplotlib, Seaborn, and Plotly for visual analytics; Scikit-Learn for Machine Learning; and Streamlit for web dashboards.
Can you host or deploy the Streamlit Dashboard live?
Yes! I can help you deploy your Streamlit app for free on Streamlit Community Cloud or guide you on how to host it on your own cloud server/system.
What if my dataset has missing values or outliers?
Cleaning raw data is part of every package. I will handle missing values (imputation), fix data types, and remove or treat extreme outliers before performing analysis.
Can you work with custom datasets not related to customer analysis?
Yes! While this gig highlights customer segmentation, I can analyze datasets from any industry including E-commerce, Healthcare, Finance, Marketing, and Sales.
