Pandas Jobs

Job Title: Python Developer for Geophysical Data Analysis (K-Means Clustering & 3D Visualization) Project Overview: I am a Geophysics student working on a structural mapping project of the Red Sea Rift. I have a dataset of 50 years of earthquake records (USGS CSV format) and need a Python expert to build a machine learning workflow that clusters these events based on their seismic attributes to identify hidden fault structures. Scope of Work: Data Pre-processing: Clean a USGS earthquake catalog and perform feature scaling on four specific attributes: Latitude, Longitude, Depth, and Magnitude. Unsupervised Machine Learning: * Implement K-Means Clustering to group seismic events. Provide an Elbow Method plot to justify the optimal number of clusters (K). 3D Visualization: * Create ...

Project Overview: We are seeking an experienced Machine Learning Specialist to assist in the development and implementation of machine learning models for the controlled synthesis of carbon dots (CDs). This project involves data-driven prediction of optical properties of CDs based on key reaction parameters. The ideal candidate will have expertise in machine learning algorithms, data preprocessing, feature engineering, and model optimization. Knowledge of Python and relevant libraries (e.g., Pandas, Scikit-learn) is essential. Project Description: The project aims to apply machine learning techniques to predict and optimize the synthesis of carbon dots, focusing on properties like fluorescence intensity, emission wavelength, and stokes shift. The dataset comprises experimental data on 80 ...

We need Python Programmer for coding share market strategies. Please come back with your quotes.

I have a spreadsheet (~5,000 product rows) where each row contains a full HTML eBay listing template. Each row includes: ID SKU Description Short description The Description field contains a large block of HTML (decorative listing template), but the actual product description is embedded inside it. Your job is to extract the correct text. 1. Extract the Correct Description In every row, the real product description is located inside this HTML block: <div class="desc-rd desc-text"> Requirements: Extract only the content inside this div Ignore all other HTML content in the row (menus, images, headers, shipping info, footer, etc.) Do not use the rest of the HTML outside this block 2. Clean the Extracted Text The content inside the div typically contains HTML such as...

I have a numerical dataset that needs a careful scrub before any sense can be made of it. The main headache right now is outliers—they are skewing the story the numbers are trying to tell. I need you to detect, diagnose, and treat those extreme values using an approach you can justify statistically (Python / Pandas, R, or even advanced Excel are all fine as long as the method is transparent and reproducible). Once the data are healthy, I want straightforward descriptive statistics—think clear measures of central tendency, dispersion, and a concise written interpretation that highlights anything interesting the cleaned data reveals. No forecasting or trend-spotting models this time; just an honest summary of what the numbers say after the noise is removed. Deliverables: •...

I have a flow of numerical data arriving on a regular basis and I want the entire predictive-analysis cycle handled automatically in Python. The goal is a script or small pipeline that can pull the fresh data, clean and transform it, train or update a predictive model, and then return the forecasts (plus standard performance metrics) without manual intervention. I expect you to choose the appropriate Python libraries—think pandas for wrangling, scikit-learn or a comparable framework for modelling, and perhaps joblib or pickle for model persistence—and stitch them together in a way that lets me trigger everything with a single command or scheduled job. Clear, well-commented code and a short README that shows how to run the automation are part of the deliverable. If you can set ...

I need a Python expert to help automate data processing tasks. The data is primarily numeric. Key Tasks: - Write scripts to automate data processing. - Handle large datasets efficiently. - Ensure accuracy and reliability in automation. Ideal Skills and Experience: - Proficiency in Python, especially in scripting and automation. - Experience with libraries like Pandas, NumPy. - Strong problem-solving skills. - Ability to work with large numeric datasets. Looking forward to your bids!

I need a clean, modern portfolio site that presents me as a Machine-Learning Engineer and lets visitors quickly explore my work. The core of the site is a Project Showcase where each project has its own page with screenshots, a short problem–solution narrative, tech-stack tags, and links to the live demo or GitHub repo. Although a full blog section is not required for the initial release, the design should leave room for a future technology-focused blog so the navigation and folder structure remain extensible. Responsive behaviour, fast loading times, and solid SEO markup are priorities because most recruiters will be viewing the site on mobile first. Please build with a modern front-end framework you are comfortable with (React, , Vue, or a lightweight static-site generator are ...

I need a freelancer to perform exploratory data analysis on a large, structured dataset (CSV or Excel). The primary goal is to summarize the main characteristics of the data. Key requirements: - Summarize dataset characteristics - Work with large structured datasets - Deliver insights quickly Ideal skills: - Proficiency in data analysis tools (e.g., Python, R, Pandas) - Experience with large datasets - Strong statistical knowledge - Ability to meet tight deadlines Please provide examples of previous similar work.

I need a small-to-mid-size Python 3.x project entirely centred on data processing. The script (or self-contained package) should be able to ingest a raw dataset from a file path or stream, apply a clear transformation pipeline that I can modify later, and write the cleaned, structured results back out. The exact data format is still flexible—I’ll provide sample files once we start—so please write modular code that separates the I/O layer from the core transformation logic. Pandas, NumPy, or similar libraries are welcome as long as they are the right tool for the job and you keep external dependencies to a minimum. My priorities are: • Readable, well-commented code that follows PEP 8 • A concise README explaining setup, usage, and how to extend or swap ...

I already run this multi-layer intraday trend-and-momentum strategy live on TradingView, and it behaves exactly as intended there. Now I need the same logic translated to a Python algo that talks to Zerodha’s Kite API so it can place and manage real NSE/BSE orders automatically. All of the trading logic is ready in Pine Script: dual-timeframe directional scoring, twin SuperTrend confirmation, jump/flip pattern triggers, momentum state scoring, ATR-managed exits, dynamic stop-losses, a trend filter, and strict intraday time gating. The job here is to reproduce that behaviour faithfully in Python, keep it modular for easy parameter tweaks, and wire it for live execution. I want you to build on familiar tools—Pandas for data handling, TA-Lib for indicator parity, and Backtrader ...

I need a freelancer to perform exploratory data analysis on a large, structured dataset (CSV or Excel). The primary goal is to summarize the main characteristics of the data. Key requirements: - Summarize dataset characteristics - Work with large structured datasets - Deliver insights quickly Ideal skills: - Proficiency in data analysis tools (e.g., Python, R, Pandas) - Experience with large datasets - Strong statistical knowledge - Ability to meet tight deadlines Please provide examples of previous similar work.