Clean and transform messy data in Stata with reproducible workflows
Generates Python code to fetch images from AWS S3 using keys from a pandas DataFrame column and embeds them as visual images into an Excel file.
Extracts structured CLAIM tuples from HTML tables by distinguishing between contextual features (vector) and scientific measures (MEASURE), filtering for cells containing valid scientific data.
Generate Python code to iterate through S3 keys stored in a pandas DataFrame, fetch the images using boto3, and embed them as actual images into an Excel file.
Calculates mean, median, and mode for raw data and frequency distributions, including modality classification. Computes GPA using a specific 4.0 scale and applies user-defined rounding rules.
Generates a list of 15 words and 5 phrasal verbs appropriate for a specified CEFR level (e.g., B1, B2), strictly excluding any words or phrases provided in a user-defined exclusion list.
Generates a synthetic dataset of math problems in a Markdown table with specific columns, detailed derivations, and strict behavioral constraints regarding output completeness and tone.
Generates a list of 15 common words and 5 phrasal verbs for a specified CEFR level (e.g., B1, B2), strictly avoiding a user-provided list of excluded vocabulary.
Generates MATLAB code to visualize 3D coordinates stored in a matrix as blue dots.
Panel data analysis with Python using linearmodels and pandas.
Run IV, DiD, and RDD analyses in R with proper diagnostics
Run regression analyses in Stata with publication-ready output tables.
Generate publication-ready regression tables in LaTeX.
Create publication-quality charts and graphs for economics papers.
源泉徴収票の画像を読み取り構造化データを返す。 他のスキルから呼び出されるほか、直接ユーザーが呼び出すことも可能。
Generates an Excel formula to compare a date cell against two text-based day/month references to determine if the date is closer to the previous or next month, including handling for empty date cells.
Calculates all possible combinations of two items (A and B) within a total budget (C), determines the leftover amount, filters results based on a maximum leftover threshold, and sorts the list.
Interpolates GPS coordinate measurements with a grid density calculated as input count multiplied by 10, and exports the result to a CSV file with specific column headers.
Generates a structured analysis of historical battles focusing on participants, location, Canada's role, outcome, and significance, formatted in point form.
Analyzes provided lottery number series to generate optimized combinations based on frequency, supporting specific formats like '5 numbers + 2 stars'.
Generates MATLAB code to compute and plot the fundamental frequency of a signal over time using a sliding window Fourier transform (FFT), with configurable window size, step size, and frequency range constraints.
Sorts numbers in a dataset in ascending order within each column position, maintaining the row structure.
Builds a binary classification neural network for the Adult Census dataset using robust, dynamic preprocessing. Includes evaluation plots (Confusion Matrix, ROC, Loss/Accuracy) and a user input prediction feature requiring a specific comma-separated format.
Generates a comprehensive set of evaluation metrics and visualizations for classification models, including classification reports, confusion matrices, ROC curves (binary and multi-class One-vs-Rest), and density plots of predicted probabilities.
Calculate and list points with integer coordinates for a given mathematical function within specified x and y ranges to facilitate graphing.
Generates a one-row, eight-column table of random numbers where each value is less than 80 and the sum equals a user-provided target. The total is bolded at the left, and output is strictly the table data.
Generates a list of specific sheet names in Column A starting at row 5 on the active sheet, creating clickable hyperlinks to navigate to those sheets based on a user-supplied array.
Generates random math problems with 2 or 3 numbers and validates user answers by explicitly stating if they are correct or incorrect.
Implement MATLAB functions for numerical analysis, including curve fitting, regression, and integration, based on user-provided mathematical formulas and specific constraints.
Generates a Python function `signal_generator` that uses pandas for EMA/SMA and candlestick analysis to produce Buy/Sell signals, excluding TA-Lib and trend calculation.