You will get Professional Data Cleaning and Python Automation Scripts
Project details
Stop wasting hours on manual data entry and cleaning!
I will transform your messy, raw data into a clean, organized, and analysis-ready format using Python (Pandas) and Excel. Whether you have missing values, duplicate rows, or inconsistent formatting, I can fix it with 100% accuracy.
What you get with this project:
Data Cleaning: Handling null values, removing duplicates, and fixing data types.
Data Standardization: Formatting dates, phone numbers, and addresses.
Data Merging: Combining multiple Excel/CSV files into one master file.
Automation Script: (Premium Only) A Python script you can run anytime to clean new data automatically.
Why choose me?
I use Python for accuracy (no manual errors).
I can handle large datasets (100,000+ rows).
Fast delivery and professional communication.
Send me a message with your file sample before ordering!
I will transform your messy, raw data into a clean, organized, and analysis-ready format using Python (Pandas) and Excel. Whether you have missing values, duplicate rows, or inconsistent formatting, I can fix it with 100% accuracy.
What you get with this project:
Data Cleaning: Handling null values, removing duplicates, and fixing data types.
Data Standardization: Formatting dates, phone numbers, and addresses.
Data Merging: Combining multiple Excel/CSV files into one master file.
Automation Script: (Premium Only) A Python script you can run anytime to clean new data automatically.
Why choose me?
I use Python for accuracy (no manual errors).
I can handle large datasets (100,000+ rows).
Fast delivery and professional communication.
Send me a message with your file sample before ordering!
Data Tool
PythonWhat's included
| Service Tiers |
Starter
$30
|
Standard
$60
|
Advanced
$100
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 4 days |
Number of Revisions | 1 | 2 | 5 |
About Azaz
Python Data Analyst | Data Cleaning & Automation | Excel to Pandas
Gujrat, Pakistan - 4:10 pm local time
I am a Python Data Analyst specializing in transforming raw, unstructured data into clean, actionable insights. Instead of manual data entry, I use advanced Python scripts (Pandas & NumPy) to automate data cleaning and processing, ensuring 100% accuracy and saving you hours of repetitive work.
I recently developed a Real Estate Price Prediction model (R² score: 0.75), where I cleaned a dataset of 21,000+ properties, performed exploratory data analysis (EDA), and built a regression model to forecast market trends.
🚀 How I Can Help You:
Data Cleaning & Wrangling: Removing duplicates, handling missing values (NaN), and fixing format inconsistencies using Pandas.
Excel Automation: Writing scripts to merge multiple Excel/CSV files into a single master dataset automatically.
Data Visualization: Creating professional charts and dashboards using Matplotlib & Seaborn to identify trends.
Exploratory Data Analysis (EDA): analyzing your data to answer specific business questions.
Machine Learning (Basic): Building linear regression models for predictive analysis using Scikit-Learn.
🛠 Technical Stack:
Languages: Python, SQL
Libraries: Pandas, NumPy, Scikit-Learn, Matplotlib, Seaborn
Tools: Jupyter Notebooks, MS Excel, Google Colab
I am detail-oriented and committed to delivering high-quality work within deadlines. Whether you have a small one-time task or need a long-term data partner, I am here to help.
Let's discuss your data needs! Send me a message, and I can start working on your file immediately.
Steps for completing your project
After purchasing the project, send requirements so Azaz can start the project.
Delivery time starts when Azaz receives requirements from you.
Azaz works on your project following the steps below.
Revisions may occur after the delivery date.
Data Assessment & Requirement Review
I will review your raw data file (Excel/CSV) and confirm your specific requirements to ensure I understand the goal perfectly.
Cleaning & Processing (Python Scripting)
I will write a Python script using Pandas to clean the data, remove duplicates, fix missing values, and standardize the format as per your needs.