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I will do python data cleaning and data visualization
AI and Data Science
Professional Data Analyst with expertise in end-to-end data processing, data cleaning, and Exploratory Data Analysis (EDA). I turn raw, messy data into clean, actionable insights that drive smart busi...
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I am a Python Data Analyst specializing in Data Cleaning, Preprocessing, and Exploratory Data Analysis (EDA).
Using Pandas, NumPy, Matplotlib, and Seaborn, I will transform your messy datasets into clean, well-structured, and actionable insights.
What I offer in this Gig:
- Data Cleaning & Formatting: Fixing missing values, duplicates, wrong data types, and structural errors.
- Exploratory Data Analysis (EDA): Discovering hidden patterns, trends, outliers, and correlations.
- Data Visualization: Creating clear, insightful, and professional charts (bar plots, histograms, heatmaps, box plots).
- Source Code: Delivery of clean, well-commented Python code in Google colab ,Jupyter Notebook (.ipynb) and CSV/Excel formats.
Lenguaje de programación:
Python
•
SQL
Tecnología:
Google Analytics
•
Jupyter Notebook
•
MATLAB
•
Power BI
Experiencia:
Conocimientos comerciales
•
Algoritmos
•
Predicción
Herramientas:
Pandas
Mi porfolio
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FAQ
What file formats will I receive in the final delivery?
You will receive the fully cleaned dataset in CSV or Excel format along with the complete Python code in a Jupyter Notebook file (.ipynb).
What Python libraries do you use for data cleaning and EDA?
I primarily use Pandas and NumPy for data cleaning and preprocessing, and Matplotlib along with Seaborn for exploratory data analysis and visualization.
How do you handle missing or duplicate data?
Depending on your dataset and requirements, missing values are either imputed using mean, median, mode, or dropped, while duplicates are completely identified and removed to ensure data integrity.
Can you handle large datasets?
Yes, Python handles large datasets very efficiently. If your dataset is exceptionally large, please drop me a message beforehand so I can review it.
