You will get clean, analyze and visualize your dataset using Python
Project details
I will analyze your dataset using professional data science methodologies to extract reliable insights, identify patterns, and answer your business questions.
The analysis follows industry best practices based on the CRISP-DM framework (Cross Industry Standard Process for Data Mining), ensuring a structured and transparent workflow from data understanding to final insights.
What I can deliver:
• Data cleaning and preprocessing
• Exploratory data analysis (EDA)
• Statistical insights and visualizations
• Predictive modeling (if applicable)
• Interpretable results and clear explanations
Important:
The quality of the results depends on the quality and completeness of the dataset provided. If the dataset lacks relevant information, the analysis results may be limited.
If a dataset is not available, I can search for publicly available data sources (government data, research databases, or open datasets). However, these sources may not perfectly represent your specific business context.
My goal is to provide clear, honest, and actionable insights that help you make better data-driven decisions.
The analysis follows industry best practices based on the CRISP-DM framework (Cross Industry Standard Process for Data Mining), ensuring a structured and transparent workflow from data understanding to final insights.
What I can deliver:
• Data cleaning and preprocessing
• Exploratory data analysis (EDA)
• Statistical insights and visualizations
• Predictive modeling (if applicable)
• Interpretable results and clear explanations
Important:
The quality of the results depends on the quality and completeness of the dataset provided. If the dataset lacks relevant information, the analysis results may be limited.
If a dataset is not available, I can search for publicly available data sources (government data, research databases, or open datasets). However, these sources may not perfectly represent your specific business context.
My goal is to provide clear, honest, and actionable insights that help you make better data-driven decisions.
Data Tool
PythonWhat's included
| Service Tiers |
Starter
$20
|
Standard
$50
|
Advanced
$100
|
|---|---|---|---|
| Delivery Time | 2 days | 3 days | 5 days |
Number of Revisions | 1 | 2 | 3 |
Number of Pages Mined/Scraped | 1 | 2 | 3 |
Number of Sources Mined/Scraped | 1 | 2 | 3 |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$15 - $25
Additional Revision
+$5
Additional Page Mined/Scraped
+$5
Additional Source Mined/Scraped
+$5Frequently asked questions
About Jesse
Data Analyst | Python | Pandas | Data Visualization | Machine Learning
Sao Paulo, Brazil - 10:36 am local time
I specialize in data analysis and predictive modeling using Python. My work focuses on understanding datasets, identifying patterns and building interpretable machine learning models that help explain and predict real-world behavior.
I have experience working with real datasets, including aviation and telecom data.
Some of my recent projects include:
• Flight delay prediction using Brazilian ANAC aviation data
• Customer churn prediction using the IBM Telco dataset
My workflow typically includes:
• Data cleaning and preprocessing (Pandas)
• Exploratory Data Analysis (EDA)
• Feature engineering
• Model development and evaluation
I have experience with models such as:
• Logistic Regression
• Random Forest
• XGBoost
• Linear Regression
I also work with model interpretation techniques, including feature importance analysis and SHAP values to better understand model behavior.
Technologies:
Python • Pandas • Scikit-learn • Matplotlib • Jupyter Notebook • SQL
If you need help analyzing data, building predictive models or understanding what drives patterns in your dataset, I’d be happy to help.
Steps for completing your project
After purchasing the project, send requirements so Jesse can start the project.
Delivery time starts when Jesse receives requirements from you.
Jesse works on your project following the steps below.
Revisions may occur after the delivery date.
Project kickoff and requirements
The client provides the dataset and explains the business objective or question to be answered. I review the data and confirm that the project scope is clear before starting the analysis.
Data exploration and preprocessing
I analyze the dataset structure, clean inconsistencies, handle missing values, and explore variable relationships to understand the data before performing deeper analysis.