Expert in Data Analysis and Web Scraping for Real Estate Market Research in Bogotá

Hello.
I was interested to learn about your project. I am confident that I can do effective and quality work that meets your requirements and expectations. I have over 8 years of experience. I am ready to discuss the details and start working. I will be waiting for your response, feel free to write and we will discuss.

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Hello!
I am ready to conduct a comprehensive real estate market research with regular updates: data collection from key portals, cleaning/deduplication, normalization of prices/areas, calculation of price per m² by districts (including admin fee per m²), detection of outliers, and building an interactive dashboard.

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Hello!
I am ready to conduct a comprehensive real estate market research with regular updates: data collection from key portals, data cleaning/deduplication, price/area normalization, calculation of price per m² by districts (including admin fee per m²), detection of outliers, and building an interactive dashboard.

Technology stack

Backend:

*Python 3.12
*Scrapy + Playwright
… *Pandas
*PostgreSQL
*FastAPI

-Infrastructure / DevOps:

*Docker + Docker Compose
*VPS
*GitHub

I will be waiting for your message to discuss the stages of development and approaches to work.
Best regards, Andriy!

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Hello! I understand the task, I have extensive experience with web scraping, databases and Excel.
I understand algorithms and methods of visualization and filtering the necessary data. I will develop the necessary tool inexpensively, because I am still building a portfolio and am ready to start immediately! Contact me!

I can build a high-performance system to handle this study end-to-end:

Automated Scraping: Extracting real-time data from major portals using Python (Playwright), including "Estrato" and age.

Data Cleaning: Removing duplicates and normalizing prices/areas for 100% consistency.

Investment Analytics: Identifying "outliers" (undervalued properties) using statistical modeling.

Interactive Dashboard: Creating a Google Looker Studio or Power BI report for easy filtering.
…
I have a strong background in Data Science (ex-FOREO) and experience scraping complex platforms like Facebook. Ready to start immediately.

I can deliver the project in 3 days with 100% completion.
I have proven expertise in web scraping, data cleaning, statistical analysis, and dashboard visualization.
I will execute exactly as specified:
— extract all required fields;
— clean and normalize the dataset;
— calculate average price and admin fees per m² by district and identify outliers;
— build an interactive monitoring dashboard;
— deliver the final CSV/Excel file.

… Confirmed acceptance of the $500 payment.

Hello, I am a Python developer with over 5 years of experience. I have successfully completed projects involving parsing and competitor analysis, and I can parse a wide variety of websites without any problems collecting and structuring data. We need to discuss the websites that are sources of real estate listings, the number of listings, and the amount of parsing required to understand the full scope of the work. I will do everything with high quality, help with project deployment on the hosting, and provide support in identifying bugs. One of my projects is parsing system for car sale websites, data structure and preparing for ine telegram bot, more then 5 websites, telegram channels and all work fine. The project is interesting, and I will be happy to discuss the details and move on to cooperation. I will do everything with high quality and quickly!

Hello!

I have strong experience in web scraping, data cleaning, and real estate market analysis. I can collect and normalize property data, calculate price per m² and admin fees by area, identify undervalued listings, and deliver a clean CSV/Excel file plus an interactive dashboard (Power BI / Tableau / Looker Studio).

Ready to start and provide regular updates.

Hello! I have reviewed the project description — I have relevant experience in web scraping, data cleaning, and real estate market analytics, so I can fully handle this task "turnkey."

How I propose to implement the project:
1. Web scraping

Data collection from the main real estate portals in Bogotá

Regular updates (on schedule)

… Data fields collection:

price

administrative fees

location (city / district)

socio-economic stratification level

area

number of bedrooms / bathrooms

age of the property

date of posting

Technically: Python + Playwright / requests (depending on website protection).

2. Data cleaning and processing

removal of duplicates

normalization of price and currency formats

unification of measurement units

verification of data completeness and accuracy

3. Analytics

calculation of price per m² by districts

calculation of administrative fees per m²

identification of investment opportunities (properties with prices significantly lower than the average)

basic statistical indicators and comparisons

4. Visualization

interactive dashboard in Power BI

filters by districts, price, area, stratification

convenient tool for market analysis and decision-making

Result

CSV / Excel with a complete cleaned database

link to the interactive dashboard

readiness for regular data updates

👉 I can provide examples of similar projects in personal messages.

Timeline and cost

Initial implementation: 10–14 days

Cost: $400-500
(depends on the number of sources and the complexity of the dashboard)

I am ready to discuss sources, update frequency, and start working immediately.

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I am among the top 5 developers in the category of "Artificial Intelligence and Machine Learning" among ~2100 specialists on the platform.
I guarantee:
- Fast and quality execution of the task
- Strict adherence to deadlines
- Regular communication throughout the entire process
I would be happy to discuss the details of your project in private messages.

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Hi,
I would be happy to help with your real estate market study in Bogotá.

I have strong experience in real estate web scraping, data mining, and statistical analysis, using Python and R.
I have previously worked with large property datasets, extracting and cleaning data from major real estate portals and transforming it into reliable, analysis-ready databases.

What I can deliver:
• Automated web scraping of real estate portals with regular updates
• Clean and normalized datasets (CSV / Excel)
… • Calculation of price per square meter and administration fee per square meter by neighborhood
• Detection of underpriced properties and statistical outliers
• Interactive dashboards (Power BI, Tableau, or Looker Studio) for easy filtering and exploration

Tools & Skills:
• Python (Scrapy, BeautifulSoup, Selenium, Pandas, NumPy)
• R (tidyverse, data.table, visualization)
• SQL for data storage and updates
• Dashboard creation and data visualization

I focus on data accuracy, scalability, and reproducibility, ensuring the solution can be updated regularly as new listings appear.

I would be glad to discuss your target areas, preferred real estate portals, and update frequency.

Best regards,
Roman

I will provide you with everything clearly and qualitatively, any protections are not a problem, feel free to contact me.

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I am a data analysis and web scraping expert with a proven track record in the real estate sector. I recently completed a similar comprehensive market study for the Cyprus real estate market, where I automated the extraction and analysis of thousands of listings to identify high-yield investment opportunities.

I can build a robust pipeline for the Bogotá market using the following approach:
- Smart Scraping: I use Python-based tools (Scrapy/Selenium/Playwright) capable of bypassing anti-scraping measures on major portals to ensure consistent data flow for your regular updates.
- AI-Powered Processing (LLM): Unlike traditional methods, I integrate LLMs (Large Language Models) to:
--Normalize and categorize "messy" location data and neighborhood names.
- -Extract hidden insights from property descriptions (e.g., specific amenities or seller urgency).
- -Filter out duplicate or low-quality listings with high precision.
- Statistical Depth: I will calculate price/sqm and administration/sqm metrics, using statistical methods (Z-score/IQR) to highlight undervalued "outliers" that represent the best investment opportunities.
… - Interactive Visualization

I am ready to start in a week.

Looking forward to discussing how I can help you find the best deals in Bogotá!

I am ready to develop this project. I will write in Python with full data analysis and support. If you are interested in working - write to me.

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