I can help you conduct factor analysis using Python
- 4.4
- (10)
Project Details
Why Hire Me?
I specialize in factor analysis using Python for clients across domains like education, marketing, psychology, and business. With 7+ years of experience in statistical modeling and data preprocessing, I simplify complex datasets into clear, actionable insights using techniques like EFA and CFA.
What I Offer
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Expert command of Python libraries like
factor_analyzer
,scikit-learn
,pandas
, andmatplotlib
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Accurate handling of assumptions and diagnostics (KMO, Bartlett’s test)
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Comprehensive visual reports including scree plots, loading matrices, and explained variance
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Project-ready interpretation tailored for academic or commercial use
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Clear documentation and reproducible scripts if required
What I Need to Start Your Project
To deliver the best results using Python for your factor analysis task, I will require the following:
1) Project Objectives and Context
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What decision or insight are you aiming to support using factor analysis?
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Are you conducting exploratory (EFA), confirmatory (CFA), or PCA?
2) Data Access and Specifications
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Dataset in CSV/Excel/SQL format
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Description of each variable
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Details on any required preprocessing or cleaning
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Information on scale type (Likert, continuous, ordinal, etc.)
3) Technical Expectations
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Do you need only results, or also the Python code?
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Do you prefer specific libraries or coding standards?
4) Report Format Preferences
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Output preference: PDF, Word, Jupyter Notebook, or HTML
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Level of detail needed (research-style, business-focused, or both)
5) Visualization Needs
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Scree plots, factor loading plots, heatmaps
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Custom color coding or chart annotations if needed
6) Timeline and Deadlines
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Final submission date
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Any interim updates or review dates
7) Communication Setup
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Preferred method: Email, Zoom, WhatsApp
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How frequently should we share progress updates?
8) Security and Confidentiality
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Any special data handling requirements
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NDA or data-sharing agreement (if applicable)
9) Future Use or Training
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Will you reuse the process in-house later?
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Any expectation for walkthrough, documentation, or training?
Portfolio

Psychometric Scale Validation Using Exploratory Factor Analysis in Python
Conducted exploratory factor analysis (EFA) on survey data for a U.S.-based university psychology research group. Helped validate an emotional resilience scale by identifying its core latent constructs.

Brand Perception Analysis Using Factor Analysis for a U.S. Consumer Electronics Firm
Used factor analysis in Python to uncover latent themes behind customer brand perceptions collected via online surveys. Findings guided content strategy and product positioning for a U.S. electronics brand.

Employee Satisfaction Index Construction via Confirmatory Factor Analysis Using Python
Performed confirmatory factor analysis (CFA) using Python to test the construct validity of an internal employee engagement index. Enabled the U.S. HR team to track satisfaction dimensions with statistical rigor.
Process

Customer Reviews
10 reviews for this Gig ★★★★☆ 4.4
Clear process, smooth communication, and detailed Python-based analysis. The insights derived from the factor solution were valuable for our internal product design research.
This service helped me understand the latent structure of my marketing data. The factor loadings and scree plots were nicely visualized and all assumptions were properly tested.
He implemented both EFA and CFA in Python using factor_analyzer and statsmodels. Output was well-structured and helped me present my results confidently in a client meeting.
Great experience working with him. Used Python to extract meaningful factors and helped me reduce dimensionality in a complex survey dataset. Very professional and responsive.
The factor analysis was done exactly as I needed, with clean code and great explanations in Python. The report included helpful plots and clear interpretations—highly recommended.
this service helped me simplify my data and understand the major patterns, very professional with Python and delivered exactly what I asked
he used scikit-learn and factor_analyzer to run the analysis and explained everything in report, thanks for the clear visualizations and code
I sent a messy dataset and he not only cleaned it but also performed complete factor analysis and helped me understand the results step by step
great communication and timely delivery, he helped me do EFA with proper scree plot and factor loadings using Python, highly recommended
the way factor analysis was handled in Python was very smooth, all latent dimensions were clearly explained and visuals helped a lot, good job