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I will perform exploratory data analysis, eda and visualization in python
ML Engineer
Hi! I’m Rimsha, a Data Analyst with 1.5+ years of professional experience in data analysis, dashboards, automation, and APIs. I work with Excel, Google Sheets, Python, Power BI, and Machine Learning t...
Über diesen Service
I will perform exploratory data analysis (EDA) on your dataset using Python.
If you have messy sales data, survey responses, or research data sitting in a
spreadsheet, I'll clean it, explore it, and show you exactly what it's telling
you through statistics, visualizations, and a clear written summary, not
just charts.
WHAT'S INCLUDED IN MY EXPLORATORY DATA ANALYSIS SERVICE:
Data cleaning (missing values, duplicates, formatting issues)
Exploratory data analysis (distributions, correlations, trends, outliers)
Visualizations with Matplotlib, Seaborn & Plotly
Statistical summaries with plain-English insights
A clean, commented Jupyter Notebook you can reuse or extend
WHO THIS IS FOR:
Business owners needing sales or customer insights
Students needing EDA for coursework, thesis, or research
Startups validating data before building ML models
TOOLS: Python, Pandas, NumPy, Matplotlib, Seaborn, Plotly, Jupyter Notebook
Send me your dataset and your goals before you order I'll tell you exactly
what insights are possible, free of charge.
Mein Portfolio
FAQ
What file formats do you accept?
CSV, Excel, JSON, or a database export.
Do you need my dataset before I order?
Not required, but sharing a sample first (even 10 rows) helps me scope accurately.
What will I actually receive?
A commented Jupyter Notebook with the full analysis, code, and visualizations, plus a written summary of key insights in plain English. Standard and Premium packages also include a correlation analysis and (Premium) a separate PDF report.
What tools do you use?
Python, Pandas, NumPy, Matplotlib, Seaborn, Plotly, and Jupyter Notebook.
Do you offer revisions?
Yes — the number of revisions depends on your package (see package details). I'm also happy to clarify or re-explain any part of the analysis after delivery.
