🔍 Code Extractor

Search Components

Full-Text: Fast keyword matching | Semantic: AI-powered understanding of intent (finds similar concepts)

Search Results for "temporal"

Found 14 matching component(s)

  • function create_data_quality_dashboard

    Creates an interactive command-line dashboard for analyzing data quality issues in treatment timing data, specifically focusing on treatments administered outside of flock lifecycle dates.

    File: /tf/active/vicechatdev/data_quality_dashboard.py

    data-quality dashboard interactive menu-driven timing-analysis

  • function analyze_temporal_trends

    Analyzes and prints temporal trends in timing issues for treatments that occur before flock start dates or after flock end dates, breaking down occurrences by year and month.

    File: /tf/active/vicechatdev/data_quality_dashboard.py

    temporal-analysis data-quality time-series reporting data-validation

  • class OneCo_hybrid_RAG_v2

    A class named OneCo_hybrid_RAG

    File: /tf/active/vicechatdev/OneCo_hybrid_RAG.py

    class oneco_hybrid_rag

  • class OneCo_hybrid_RAG_v3

    A class named OneCo_hybrid_RAG

    File: /tf/active/vicechatdev/vice_ai/hybrid_rag_engine.py

    class oneco_hybrid_rag

  • class EnhancedSQLWorkflow

    Enhanced SQL workflow with iterative optimization

    File: /tf/active/vicechatdev/full_smartstat/enhanced_sql_workflow.py

    class enhancedsqlworkflow

  • function create_sample_data_v1

    Generates a synthetic dataset with 200 samples containing group-based measurements, quality scores, environmental data, and temporal information, then saves it to a CSV file.

    File: /tf/active/vicechatdev/full_smartstat/demo.py

    data-generation synthetic-data sample-data testing demonstration

  • class SQLQueryGenerator

    Generates SQL queries based on user requests and database schema

    File: /tf/active/vicechatdev/full_smartstat/sql_query_generator.py

    class sqlquerygenerator

  • function isnat

    Checks if a value is NaT (Not-a-Time), a special marker for missing or invalid datetime/timedelta values in NumPy and pandas.

    File: /tf/active/vicechatdev/patches/util.py

    datetime timedelta NaT missing-values temporal-data

  • function isdatetime

    Determines whether a given value (array or scalar) is a recognized datetime type, checking both NumPy datetime64 arrays and Python datetime objects.

    File: /tf/active/vicechatdev/patches/util.py

    datetime type-checking validation numpy temporal-data

  • function unique_array

    Returns an array of unique values from the input array while preserving the original order of first occurrence.

    File: /tf/active/vicechatdev/patches/util.py

    array-processing deduplication unique-values data-cleaning order-preserving

  • function dt64_to_dt

    Converts a NumPy datetime64 object to a Python datetime.datetime object by calculating seconds since Unix epoch.

    File: /tf/active/vicechatdev/patches/util.py

    datetime numpy conversion datetime64 time-conversion

  • function compute_density

    Computes the density (samples per unit) of a grid given start and end boundaries and the number of samples, with special handling for datetime/timedelta types.

    File: /tf/active/vicechatdev/patches/util.py

    density grid datetime timedelta sampling

  • function date_range

    Generates an evenly-spaced date range array with a specified number of samples between start and end dates, with dates centered in each interval.

    File: /tf/active/vicechatdev/patches/util.py

    datetime date-range time-series numpy pandas

  • function dt_to_int

    Converts various datetime types (pandas, numpy, cftime, Python datetime) to an integer timestamp with a specified time unit.

    File: /tf/active/vicechatdev/patches/util.py

    datetime timestamp conversion time-series pandas

Search Examples