You will get data cleaning and exploratory analysis with Python
Project details
I offer accurate and well-documented data cleaning and analysis using Python. You’ll get a clean dataset, visual insights, and a clear final report that supports better business decisions — clear communication, and reproducible results.
Data Tool
PythonWhat's included
| Service Tiers |
Starter
$50
|
Standard
$100
|
Advanced
$150
|
|---|---|---|---|
| Delivery Time | 3 days | 6 days | 10 days |
Number of Revisions | 0 | 1 | 2 |
About Badr
Data Analyst
Minyat Sandub, Egypt - 8:03 am local time
Many businesses struggle with unclear reporting and scattered data — I help fix that by simplifying complexity with clean analysis and clear dashboards that deliver actionable results. My focus is always on creating real business value, not just reporting numbers.
I work with SQL, Excel, Power BI, and Python (NumPy, Pandas, Matplotlib) to explore, clean, and analyze data — transforming it into meaningful insights and visualizations.
Here’s how I can help you:
Data preparation & cleaning – fixing missing values, duplicates, and inconsistencies.
Exploratory analysis – identifying patterns, trends, and outliers.
Data visualization – creating dashboards in Excel & Power BI, with clear and engaging charts.
Reporting & KPIs – designing reports that highlight your most important metrics.
SQL querying – extracting and aggregating data from relational databases.
Automation – using Python to streamline repetitive tasks and speed up analysis.
If you need data that speaks and supports your strategy, let’s connect.
Send me a message, and let’s start turning your data into smarter business decisions!
Steps for completing your project
After purchasing the project, send requirements so Badr can start the project.
Delivery time starts when Badr receives requirements from you.
Badr works on your project following the steps below.
Revisions may occur after the delivery date.
Initial data review
I check data quality, missing values, duplicates, and data structure to plan the cleaning process.
Data cleaning
Fix missing values, remove duplicates, correct data types, and clean text fields where needed.