Pandas jobs

...and presenting the findings in an easy-to-digest format. The work will involve: • Securely pulling data from the sources I provide • Cleaning, normalising, and validating everything so it is analysis-ready • Running the agreed analytical models or exploratory techniques • Packaging the results in a concise summary report and, where useful, visual dashboards I generally rely on Python (pandas, NumPy, matplotlib, seaborn), SQL, and Excel for ad-hoc checks, but I’m open to the stack you prefer as long as the final output is transparent and reproducible. When you reply, please outline: – Your typical workflow for a project like this – The primary tools you plan to use – A recent example that shows you can move seamlessly ...

...insights. Your task is two-fold: 1) remove duplicates, fix inconsistencies, handle missing values and generally get the raw data into analysis-ready shape; 2) dig into the cleaned set to surface actionable findings—summary statistics, trends and any patterns you spot, with clear explanations and visuals where helpful. You are free to use the tools you are most comfortable with—Excel, Python (pandas, NumPy, SciPy), SQL, R, Power BI, Tableau or similar—as long as the final work is reproducible and can be handed over without licence restrictions. Deliverables • A clean, well-documented data file in the same original format • An insights report (PDF or slide deck) that explains methods, key findings and recommended next steps • Any scripts...

...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 synthesis conditions, with key parameters such as precursor types, solvent types, a...

...flow I have in mind starts with a clear overview, moves into the trend narrative, and culminates in a full SWOT analysis. Every slide should be self-explanatory—my VP should grasp the story without additional commentary. Strong data visualization, crisp wording, and a logical thread from finding to implication are essential. PowerPoint is fine, but feel free to use Tableau, Power BI, or Python (pandas, matplotlib, seaborn) behind the scenes if they sharpen the story; just embed or export final visuals so they remain editable. Deliverables • A polished slide deck (PPTX) following the overview-trend-SWOT structure • Source visual files or worksheets, clearly linked to the numbers in the Excel I provide • A short slide or note listing any assumptions or d...

...• Handle missing values intelligently (flag, fill, or remove). • Re-format text, with built-in spelling correction so names, addresses, and other fields come out consistent. Once the data is clean, the same application should let me design or pick a simple template and generate one PDF per record or a consolidated report in a single click. I’m flexible on language and framework—Python with pandas and ReportLab, C# with iText, or anything comparable—as long as the final deliverable is: 1. An installable or easily deployable application. 2. Source code with clear comments. 3. A brief user guide that shows how to load data, run the cleaning steps, and produce the PDFs. If this sounds like a tool you can build efficiently and reliably, I’d...

...that involves straightforward data entry from spreadsheets, deeper analytical summaries drawn from a database, or shaping web-scraped records into a narrative that can power a report, a machine-learning pipeline, or an interactive dashboard. Here’s what I need from you: • A brief outline of how you would tackle the job once you see the raw files. • Your preferred tools—Excel, SQL, Python (Pandas, NumPy), or any other stack you’re comfortable with. • A sample of comparable work, if available, so I can gauge fit and style. • An estimated turnaround time for an initial milestone, plus how you’d verify accuracy and completeness. Deliverables will ultimately include the cleaned dataset in its native format, a clearly documented des...

...dataset. The goal is to surface key trends, summary statistics, and clear visual insights that non-technical stakeholders can quickly grasp. I will supply the raw data once we agree on the engagement; it is already cleaned enough for immediate exploration, but I’m open to your recommendations if additional preprocessing will strengthen the final story the numbers tell. Typical tools such as Python (pandas, matplotlib, seaborn), R (dplyr, ggplot2), or even Power BI/Tableau are all acceptable—please work in whichever environment lets you deliver crisp, reproducible results fastest. Deliverables • Concise written report (PDF or Word) outlining findings, notable patterns, and any unexpected observations • Well-commented code or notebook so I can reproduce e...

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:...

...on-prem Ollama instance, allowing natural-language questions such as “What was EBITDA for 2023?” or “How did operating cash change quarter-over-quarter?” • Clear, offline-friendly documentation plus a brief demo confirming the system answers a supplied test set accurately. Environment details The server runs Linux with Python 3.11 and the latest Ollama build; libraries like pdfplumber, Camelot, pandas, LangChain, LlamaIndex, or similar are all acceptable as long as they install via and run fully offline. Deliverables 1. Complete, well-commented source code and 2. Setup guide and usage examples () 3. Recorded or live demo session showing ≥95 % extraction accuracy and correct answers on 20 validation questions drawn from the report If yo...

...dataset choices Deliverables • Clean and processed dataset • Skill extraction pipeline (with comparison results) • Salary prediction models + validation analysis • Demand forecasting models + evaluation • Streamlit dashboard for visualization • Research report including: • Methodology • Experiments • Evaluation metrics • Results and insights • Limitations Requirements • Strong Python (pandas, numpy) • NLP experience (regex, spaCy, embeddings) • Machine learning experience • Understanding of evaluation metrics (precision, recall, F1, RMSE, etc.) • Experience with research-style work (preferred) • GitHub usage with regular commits • Must speak Hindi or Gujarati • Must...

...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 up basic logging ...

I run the monthly roster for 17 staff in AmIOn and have accumulated 32 non-negotiable rules—everything from strict rotation patterns to honouring every approved leave request. ...walkthrough or video so I can tweak rules later without calling you every time. Acceptance criteria: the generated schedule must meet 100 % of the stated rotation patterns and leave requests, cover the full month in under five minutes of processing, and allow manual overrides without breaking the remaining logic. If you’ve built optimisation or scheduling engines before—whether in Python with pandas/OR-Tools, Google Sheets scripts, or similar—you’ll know exactly what to do. Let me know how you’d structure the rule logic and the kind of interface you’d deliver so I...

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...type) Task 3: Rule-Based Recommendation Logic Based on patterns identified: Create a rule-based system such as: If Hardware Change → Recommend Peak Test If DB + Software Change → Recommend Duration Test Deliverable: Documented rules Optional: Python or SQL-based implementation Expected Skills Strong experience in Data Analysis Good knowledge of SQL (grouping, aggregation) Experience with Python (Pandas preferred) Ability to identify patterns and build logic Experience with Excel / data comparison...

A reusable Python script is required to automate data scraping from a series of publicly accessible web pages. The script should accept a list of URLs, navigate through any paginated content, extract the specified fields, and save the results to CSV and JSON. The task suits someone with an intermediate grasp of Python who is comfortable working with libraries such as requests, BeautifulSoup, pandas, or, when a site relies on JavaScript, Selenium or Playwright. Clear, well-commented code and concise setup instructions are essential so the script can be dropped into an existing workflow without modification. Acceptance criteria and deliverables: • Fully functional .py script that runs from the command line. • Configuration section (or .env file) for URL list and fiel...

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!

...Python specialist to turn my methodology into clean, reproducible code. The core help I’m after is coding itself—covering the full pipeline from data preprocessing through model training to final evaluation and visualisation. I need datasets, well-documented Python scripts or notebooks that I can run end-to-end on my own machine (or a Colab instance). Expect to work with common libraries such as pandas, NumPy, PyTorch or TensorFlow, Hugging Face Transformers, plus Matplotlib or Seaborn for charts—use whichever combination best suits the objectives while keeping dependencies manageable. Deliverables
 • Data preprocessing module that loads the provided datasets, cleans them, applies any necessary tokenisation and splits them into train/validation/test sets....

...(Google Colab preferred) that takes raw user transaction data, cleans it, applies regression techniques, and then produces a short-term forecast I can cite in investor conversations. Because time is critical, I’m aiming to move quickly—ASAP means I will review work as soon as it comes in and provide immediate feedback. Here is what success looks like for me: • A well-commented Colab notebook using pandas, NumPy, scikit-learn or statsmodels for the regression and forecasting sections. Every major step—from missing-value handling to model evaluation—needs a clear markdown explanation that a non-technical stakeholder could follow. • Actionable insights tied directly to the product idea: for example, what spending behaviours you uncovered, how reg...

...A single consolidated Excel workbook containing every voter record with duplicates clearly paired and fully detailed. 2. Part-wise / assembly-wise Excel files regenerated from that master and stored in their respective folders. 3. No data loss: row counts in the split files must equal the counts in the original source plus any duplicate copy rows you have added. You are free to use Python (pandas), Power Query, VBA, or any equivalent tool, so long as every step above is achieved and the final output remains in standard Excel format (.xlsx). Very urgent project to be completed within 4 hours. Code is not required only the output required. Totally 65 lac records are roughly available. This is rough sample output

...checking so the script skips delisted or invalid symbols without crashing. • Save the results to a tab-delimited .txt file with clear column headers and date ordering. Essential skill set Web scraping or official API use, solid grasp of HTTP requests, and enough finance/data-analysis background to spot obvious anomalies in the feed. Acceptance criteria 1. The .txt file loads directly into pandas without extra cleaning. 2. Dates, numbers, and headers are accurate when cross-checked against the live site. 3. Script runs end-to-end on my machine (Windows) with a simple command and minimal setup. This is a quick task—many freelancers finish similar pulls in just a few hours—so please tell me how soon you can deliver along with a brief note on the librari...

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.

...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 in other data sources • At least one unit test demonstrating that ...

...records into forward-looking insights. The data is already well-structured in SQL tables; what I need now is a predictive layer that helps us forecast key metrics and identify the drivers behind them. You’ll have direct read-only access to the relevant tables along with a short data dictionary. From there, please choose the techniques and tools you’re most comfortable with—whether that’s Python (pandas, scikit-learn), R, or another established machine-learning framework—so long as the final model is reproducible and the code is clearly documented. The deliverable I expect is a concise notebook or script that: • cleans and preps the data, • trains and validates at least one predictive model, • outputs performance metrics and...

...over time • Build forecasting model • Evaluate reliability Dataset Requirement: You may use any dataset, but it must: • include job descriptions • include modern skills (Python, SQL, AWS, etc.) • be large (10k+ rows minimum) Deliverables: • Clean dataset • Skill extraction pipeline • Salary analysis • Demand forecasting • Streamlit dashboard • Research results Requirements: • Strong Python + pandas • NLP experience (regex / spaCy / embeddings) • Experience with ML models • GitHub usage with regular commits • Must speak Hindi or Gujarati • Must attend 2 meetings per week (30–45 min) Timeline: 2 to 3 weeks Important: • This is my research project • No ownership or reuse of t...

...The bot should open and close positions within the same session, respect configurable risk parameters, and support rapid position sizing, stop-loss, and take-profit logic. • Exchange connectivity: everything will run on Alpaca for now, but clean modular code will let me extend to Binance, Coinbase, Kraken, or any other REST/WebSocket venue later. I prefer Python, leveraging libraries such as pandas, NumPy, TA-Lib, backtrader (or similar) for strategy logic and backtesting, plus WebSocket streams for real-time ticks. If you can propose a more robust stack that still keeps hosting simple—FastAPI for a lightweight dashboard, Docker for deployment—that’s welcome. Deliverables • Well-structured, documented source code (Git-friendly). • Config...

...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 for back-testing. During development I will supply the original Pine code and walkthroughs of each module so you can mirror calculations line by line. Deliverables I expect • A well-documented Python package (or notebook set) that connects to Zerodha, streams intraday data, executes the strategy, and handle...

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.

A Python script is needed to pull text-only data from a website / mobile-app endpoint that returns XML and drop everything into a single Excel worksheet, with each category neatly separated into its own column. The source exposes only XML responses, so parsing must rely on built-in or an equivalent library such as lxml; once parsed, the data should be pushed to Excel via pandas or openpyxl. The script should: • Retrieve the full XML payload from the target URL or API, following any necessary headers or authentication I provide. • Map every relevant XML tag to a clearly named column in one worksheet, preserving order and encoding. • Export a clean .xlsx file in one run and overwrite or version files automatically (configurable). Deliverables: 1. Well-com...

...needs to be split into training, validation, and test sets, with any necessary feature engineering you judge appropriate. I have no fixed preference on the final algorithm—linear models, tree ensembles, or a small neural network are all acceptable as long as they deliver solid predictive accuracy and are easy to retrain when I add more data. Please build the solution in standard Python tooling (pandas, scikit-learn, TensorFlow or PyTorch only if the accuracy gains justify it) and present the work in a Jupyter Notebook. Your notebook should walk me through: • data import, preprocessing, and exploratory visuals • model selection and cross-validated performance metrics • prediction of W/L ratio on unseen inputs • a short optimisation routine that se...

...suitable for a general audience. The writing should follow standard article conventions—compelling introduction, logical flow, and a concise conclusion—while the analytical portion should highlight the numbers that matter, presented through easy-to-grasp commentary and, where helpful, simple visuals such as tables or charts created with familiar tools (Excel, Google Sheets, or Python libraries like pandas/matplotlib). Deliverables • 1,500–2,000-word health article in editable format (Word or Google Docs) • Supporting spreadsheet/notebook containing the cleaned data, calculations, and visual assets • Citations for every data source or study referenced I’m flexible on timing; quality and accuracy take priority over speed. Let me know ...

I have roughly 10,000 individual XLSX workbooks that must be consolidated into...generating overlap. The finished deliverable should be: • assembly wise excel sheet where duplicates are marked, one voter data may be duplicated multiple times, I need in which assembly, which part number, at which serial number with which epic id data is Duplicated • A separate tab where which data is Duplicated how many times, as a consolidated report Feel free to rely on Power Query, VBA, Python pandas, or any tool you trust, so long as the end result arrives back to me in standard Excel format and can be opened without additional dependencies. Accuracy is critical; I’ll spot-check both the consolidated sheet and the duplicate report before sign-off. This work is urgently require...

...rainfall totals (or means, if that is what the variable represents) appear month by month across the full record. Dates must be easy to filter or pivot against, so please place one complete time series per sheet or, if you prefer, one sheet that stacks every grid-cell or station vertically with a month column beside it—whichever keeps the file light and readable. Python with xarray/netCDF4 and pandas is fine, but any tool chain that preserves data fidelity works for me as long as you document it briefly so I can reproduce the workflow later. Deliverables: • One Excel file per original NetCDF (unless you can combine logically) containing monthly rainfall values, with units retained. • A short “read-me” outlining the conversion steps and libraries used...

I have a collection of raw text records that need to be processed so they are accurate, consistent, and ready for downstream use. The task is strictly data processing—specifically text-based data cleaning. You will work with a ...rows. Your job is to: • Remove duplicates without losing any unique information • Standardize capitalization and spacing • Correct obvious typos using context (English only) • Flag any ambiguous or incomplete lines for my review Please return a cleaned file in the same format plus a short change log summarizing what was fixed. I prefer work done in Excel or Google Sheets, but Python (pandas) scripts are welcome if you include the code for transparency. Accuracy matters more than speed, so take the time to double-check ...

Title: Data Analysis Project Using Python (NumPy & Pandas) – Soccer Dataset Description I am a motivated data analyst and engineering student with hands-on experience in Python-based data analysis. I recently completed a comprehensive data analysis project focused on a real-world soccer dataset, applying powerful libraries such as NumPy and Pandas. In this project, I performed: * Data cleaning and preprocessing (handling missing values, correcting data types) * Exploratory Data Analysis (EDA) to uncover patterns and trends * Statistical analysis to answer key business and performance questions * Data visualization to present insights clearly and effectively * Structured reporting following professional data analysis standards This project demonstrates my ability...

...experienced Python developer for long-term collaboration to support automation and data visualization tasks. The work will involve automating repetitive data processes, building Python scripts for analysis, and creating interactive and insightful visualizations to support business decision-making. The ideal freelancer should have strong experience in Python programming, working with libraries like Pandas, NumPy, Matplotlib, Seaborn, and optionally Plotly or Dash for interactive dashboards. Familiarity with handling large or messy datasets and delivering clean, reproducible code is essential. Scope of Work: Automate repetitive tasks and data workflows using Python Clean, process, and transform datasets Generate visualizations and summary reports for insights Maintain organized,...

I already have several Python trading strategies coded and tested in isolation. What I need now is a clean, production-ready pipeline that does three things seamlessly: lets me back-test those strategies on historical data, pushes selected ones live through Zerodha Kite, and keeps an eye on real-time performance. The stack is non-negotiable: Pandas and NumPy for data wrangling, Backtrader as the core engine, and Zerodha’s Kite Connect/WebSocket API for brokerage connectivity. Wherever latency can be shaved, I’d like to see Numba or Cython used for just-in-time speed-ups, especially inside tight loops. The live leg must subscribe to tick data over WebSockets, place/modify orders, and stream portfolio updates without choking. Deliverables • Unified codebase that plu...

I need a clear picture of how two specific Instagram accounts have interacted through direct messages. Your task is to mine ...keywords or topics, and any spikes in activity worth highlighting. • Deliver a well-structured report—PDF or Google Doc is fine—plus a spreadsheet or database dump with the raw and cleaned data so I can run my own queries later. Visuals such as timelines or simple charts are a bonus if they help tell the story. Feel free to rely on Python, the Instagram Graph API, headless browser scraping, Pandas, NLP libraries, or any workflow you are comfortable with, provided you stay within Instagram’s terms of service and keep personal data secure. Let me know in your bid which approach you prefer and how long it will take to hand over the fin...

I have several raw text files in CSV format that need to be cleaned so they are ready for further analysis and reporting. The core of the job is to remove inconsistencies, fix or flag malformed rows, standardize headers and date / number formats, and generally make sure each file can be imported without errors into common analytics tools such as Excel, Power Query, or a Python pandas workflow. You are free to use the tools and methods you prefer, provided the final output remains in CSV and keeps the same column structure where possible. Please double-check that character encodings are consistent and that no data is silently dropped during the process. When you reply, highlight your experience with similar CSV or text-file data-cleanup projects—brief, concrete examples are e...

...task completed. (Task durations = 1-3 hours max) What You’ll Do Design and run A/B experiments and evaluate model behavior. Build/audit data workflows and pipelines (dbt, SQL). Analyze datasets and communicate findings for data-driven decisions. Work with LLM benchmarking and agentic coding workflows. What You Need 4+ years professional experience in DS, ML, or Data Engineering. Expert Python (pandas, NumPy, scikit-learn) and SQL. Proven ability to diagnose ML failure modes and improve model quality. Familiarity with cloud warehouses (Snowflake, BigQuery, or Redshift). Why this role? This is a flexible, remote engagement perfect for those looking to contribute to cutting-edge AI research and work with top-tier industry labs without the commitment of a full-time product r...

...Python 3 script (or Jupyter notebook) that loads the dataset, performs the requested exploratory analysis, applies any statistical tests or visualisations called for in the brief, and prints or plots clear results. • Inline comments that clarify the logic, plus a short README or markdown cell summarising how to run the code and interpret the outputs. • Use of standard data-science libraries—pandas, NumPy and Matplotlib/Seaborn are fine unless you suggest better alternatives that still install easily with pip. Acceptance criteria 1. Runs without modification on a fresh Python 3.10+ environment after a simple pip install -r requirements.txt. 2. Passes all stated rubric tests (I’ll share them up front). 3. Code is logically structured, PEP-8 compliant ...

...only: moving selected .xlsx/.xls files to the correct destination folders and deleting those that meet specific criteria I will provide (age, naming pattern, or both). All processing is limited to Excel files—no other formats are involved. Please write modular code that I can run from the command line on Windows and macOS. Native libraries such as os and shutil are fine; if you prefer pathlib or pandas for pattern checks, that’s acceptable too. Clear logging to console and/or a simple log file is essential so I can review exactly which files were moved or deleted after each run. Deliverables • A single .py file with inline comments explaining each function • A brief README outlining any required third-party modules and usage examples • Confirmat...

...and implement reinforcement learning algorithms, experiment quickly, tune hyperparameters, and evaluate against clear success metrics. • Integration with existing systems – wrap trained models behind REST/GraphQL endpoints, containerise (Docker/Kubernetes), and wire everything into my current Python micro-services stack on AWS. Everything is Python-first, so fluency with PyTorch or TensorFlow, pandas, NumPy, and popular RL libraries (Stable-Baselines3, Ray RLlib, or similar) is expected. Familiarity with CI/CD (GitHub Actions), infrastructure-as-code, and basic DevOps will make collaboration smoother. Deliverables I’m expecting: 1. Reproducible training pipeline with documented code. 2. Baseline RL model that reaches the agreed-upon performance benchmark. ...

I’m midway through an AI project and need an engineer who can take full ownership of the data-labeling pipeline while keeping our Machine Learning goals front and center. The model we a...work • Weekly progress snapshots (exported JSON/CSV plus brief summary) • A short report outlining any data quality issues uncovered during labeling and proposed fixes Acceptance criteria • ≥ 98 % agreement on a 10 % random audit sample • All files named and stored according to the repository’s existing structure • Final dataset loads without errors into our current Python pipeline (pandas + scikit-learn) If you’re comfortable shaping raw data into machine-ready gold and can keep an eye on downstream regression performance, let’s t...

I already have a fully-tested intraday strategy written in Pi...work completely online data source. My goal is to finish with a clean, well-documented Python module that: • replicates every signal from the Pine version, including the strict entry/exit windows • can be back-tested locally against supplied CSV/Parquet data sets • exposes a simple function or class I can later plug into a live-trading wrapper Please keep the code structured and readable—Pandas, NumPy and similar staples are welcome as long as dependencies remain mainstream. Once the translation matches the Pine results on my test set, the project is complete. If you are comfortable decoding Pine nuances and enjoy building robust, indicator-heavy intraday models, I’d love to hear how y...

...that needs to be explored for meaningful trends. My main objective is to understand how our numbers are moving over time—seasonality, spikes, dips, and any longer-term shifts that will guide strategy. Python is my preferred toolset, so I’m picturing a clean, well-commented Jupyter notebook that pulls the raw CSVs, handles any necessary cleansing, and then walks through the full trend analysis with pandas, NumPy, and visualization libraries such as Matplotlib or Seaborn. You’ll have full access to the data and can recommend additional libraries if they improve clarity or speed. At the end, I need both the notebook and an executive-friendly summary (PDF or slide deck) that highlights the key findings, annotated charts, and your interpretation of what the trends a...

...controls publicly. Deliverables 1. Complete, ready-to-run application (web package or Windows executable) with installation/launch instructions. 2. Source code and concise README so I can tweak branding later if needed. 3. Test data showing at least two successful draws and one automated re-draw scenario. If you have experience with randomisation libraries, data import modules (e.g., pandas, OleDB, or similar), and a knack for simple, show-ready UI, I’d love to see a quick demo or screenshot of previous raffle or contest projects when you send your proposal....

...defensible insights. I will provide read-only credentials and a brief on the business questions I’m trying to answer. You will be responsible for extracting the relevant tables, preparing the data, running the appropriate statistical tests, and translating the results into plain-language findings that management can act on. Please work in the analytical environment you are most comfortable with—Python (pandas, SciPy, statsmodels) or R are both fine—as long as the code is clean, reproducible, and thoroughly commented. Visual summaries such as charts or dashboards are welcome where they help communicate the story behind the numbers. Deliverables • SQL query scripts used to pull and clean the data • Well-documented analysis code (Jupyter notebook or...

...analytical work for correctness, statistical soundness, and practical relevance Engage through internal tooling, with contributions tracked to support transparency, feedback, and long-term reputation building Tools & Context Experts in this role routinely work with—or help AI agents reason about—the same tools and artifacts used in professional data science environments, including: Python (e.g., pandas, NumPy, scikit-learn) SQL Jupyter / notebook-based workflows Data warehouses and analytics platforms Dashboards, metrics definitions, and experiment readouts Research papers You May Be a Good Fit If You Are a subject-matter expert with meaningful experience in data science, experience with "how you would inspect data" Have 5+ years of professiona...

I have direct access to a ...steering-angle and yaw-rate channels. • Generating descriptive measures (min/max, mean, standard deviation, range) and overlay plots that clearly illustrate vehicle path behaviour. • Translating those findings into a short, courtroom-ready narrative that highlights the physical impossibility of the claimed path. Any common forensic or data-science toolkit—i.e., Bosch CDR, Tesla PyEDR, MATLAB, Python/pandas/matplotlib—is acceptable, provided the final deliverables include: 1. The raw CSV or JSON export. 2. Reproducible analysis scripts. 3. A brief written report (PDF) with charts suitable for legal submission. If additional context (GPS logs, speed, or timestamp alignment) strengthens the argument, please flag it so I c...

...automatically—pull rent comps, calculate projected NOI, cap rate, cash-on-cash and simple IRR, then package the results in both a downloadable spreadsheet and a JSON payload so I can drop the file straight into my CRM. Editable assumption cells for vacancy, expense ratio, financing terms and exit cap are essential so I can fine-tune scenarios on the fly. I am language-agnostic, though Python (Pandas, Requests, BeautifulSoup or Selenium for scraping, plus Jupyter for quick tweaks) or JavaScript with Node and relevant SDKs would be easiest for me to maintain. If an official API is required I will provide keys; otherwise build a scraper that respects rate limits and captcha challenges. Deliverables: • Full source code with clear in-line comments • Setup guide and...