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I will do statistical data analysis in python and sql
Data Analyst
I am a Data Analyst and Statistics student with a strong foundation in transforming complex data into clear, actionable insights. Currently in my 4th semester, I bridge the gap between statistical the...
About this Gig
Are you looking to turn raw data into actionable insights? I can help!
Data is only valuable if you can interpret it. I specialize in professional data cleaning, statistical analysis, and visualization using Python and SQL. Whether it's business data or research, I provide accurate and clear results.
What I offer:
- Data Cleaning: Removing duplicates and handling missing values using Python (Pandas).
- Statistical Analysis: Hypothesis testing (T-tests, Z-tests), Correlation, and ANOVA.
- Regression Modeling: Linear and Logistic regression to identify trends.
- SQL Queries: Efficient data extraction and management from databases.
- Data Visualization: High-quality charts and graphs (Matplotlib/Seaborn).
Tools & Skills:
- Programming: Python, SQL (MySQL/PostgreSQL).
- Environment: Jupyter Notebook, Excel.
- Focus: Accuracy, clean code, and meaningful interpretations.
Why hire me?
- Reliable communication and on-time delivery.
- Well-documented Python scripts and source code provided.
- Focus on providing "Why" behind the numbers.
Note: Please message me before placing an order to discuss your project requirements!
FAQ
Q: What file formats can you work with?
Ans: I can work with CSV, Excel, SQL databases, and JSON files. If you have data in another format, just let me know!
Question: Will you provide the source code?
Answer: Yes! Depending on the project, I will provide the Jupyter Notebook (.ipynb), Python script (.py), or SQL queries used for the analysis.
Question: Can you explain the statistical results to me?
Answer: Absolutely. I provide a summary of findings with every project to ensure you understand the "Why" behind the numbers.
Question: Do you handle large datasets?
Answer: Yes, using Python and optimized SQL queries, I can efficiently process and analyze large volumes of data.
