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function clean_for_json_v14

Recursively sanitizes Python objects to make them JSON-serializable by converting NumPy types to native Python types and handling NaN/Inf values.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/42b81361-ba7e-4d79-9598-3090af68384b/analysis_2.py | Lines: 612-629

json serialization numpy data-conversion type-conversion

function clean_for_json_v13

Recursively sanitizes Python objects to make them JSON-serializable by converting NumPy types to native Python types and handling NaN/Inf values.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/d48d7789-9627-4e96-9f48-f90b687cd07d/analysis_1.py | Lines: 356-371

json serialization numpy data-cleaning type-conversion

function clean_for_json_v11

Recursively sanitizes Python objects (dicts, lists, floats) to make them JSON-serializable by replacing NaN and infinity float values with None.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/f5da873e-41e6-4f34-b3e4-f7443d4d213b/analysis_4.py | Lines: 403-412

json serialization data-cleaning nan-handling infinity-handling

function clean_for_json_v10

Recursively converts Python objects containing NumPy and Pandas data types into JSON-serializable native Python types.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/c385e1f5-fbf6-4832-8fd4-78ef8b72fc53/project_1/analysis.py | Lines: 630-651

json serialization data-conversion numpy pandas

function clean_for_json_v9

Recursively sanitizes Python objects (dicts, lists, floats) to ensure they are JSON-serializable by converting NaN and infinity values to None and ensuring all dictionary keys are strings.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/c385e1f5-fbf6-4832-8fd4-78ef8b72fc53/project_2/analysis.py | Lines: 107-116

json serialization data-cleaning sanitization nan-handling

function detect_outliers_zscore

Detects outliers in numerical data using the Z-score statistical method, identifying data points that deviate significantly from the mean.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/328d2f87-3367-495e-89f7-e633ff8c5b3d/analysis_2.py | Lines: 86-93

outlier-detection statistics data-cleaning anomaly-detection z-score

function detect_outliers_iqr_v1

Detects outliers in a dataset using the Interquartile Range (IQR) method, returning boolean indices of outliers and the calculated bounds.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/328d2f87-3367-495e-89f7-e633ff8c5b3d/analysis_2.py | Lines: 72-83

outlier-detection IQR interquartile-range statistics data-cleaning

function export_results

Exports correlation analysis results to multiple CSV files, including overall correlations, grouped correlations, and significant findings.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/5a059cb7-3903-4020-8519-14198d1f39c9/analysis_1.py | Lines: 464-483

data-export csv file-io correlation-analysis results-persistence

Generates and prints comprehensive statistical conclusions from correlation analysis between Eimeria infection variables and broiler performance measures, including overall and group-specific findings.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/5a059cb7-3903-4020-8519-14198d1f39c9/analysis_1.py | Lines: 356-458

statistical-analysis correlation reporting data-analysis veterinary-research

function create_grouped_correlation_plot

Creates and saves a dual-panel heatmap visualization showing correlation matrices grouped by treatment and challenge regimen variables.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/5a059cb7-3903-4020-8519-14198d1f39c9/analysis_1.py | Lines: 304-350

visualization correlation heatmap grouped-analysis data-visualization

function create_scatter_plots

Creates scatter plots with linear regression lines showing relationships between Eimeria variables and performance variables, grouped by categorical variables, and saves them as PNG files.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/5a059cb7-3903-4020-8519-14198d1f39c9/analysis_1.py | Lines: 254-302

data-visualization scatter-plot regression-analysis correlation pearson-correlation

function create_correlation_heatmap

Generates and saves a correlation heatmap visualizing the relationships between Eimeria infection indicators and performance measures from a pandas DataFrame.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/5a059cb7-3903-4020-8519-14198d1f39c9/analysis_1.py | Lines: 233-252

visualization correlation heatmap data-analysis statistics

function grouped_correlation_analysis

Performs Pearson correlation analysis between Eimeria-related variables and performance variables, grouped by specified categorical variables (e.g., treatment, challenge groups).

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/5a059cb7-3903-4020-8519-14198d1f39c9/analysis_1.py | Lines: 187-227

correlation-analysis grouped-analysis statistical-analysis pearson-correlation eimeria

function calculate_correlations

Calculates both Pearson and Spearman correlation coefficients between Eimeria variables and performance variables, filtering out missing values and identifying statistically significant relationships.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/5a059cb7-3903-4020-8519-14198d1f39c9/analysis_1.py | Lines: 147-185

correlation statistics data-analysis pearson spearman

function identify_variables

Categorizes DataFrame columns into Eimeria infection variables, performance measure variables, and grouping variables based on keyword matching in column names.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/5a059cb7-3903-4020-8519-14198d1f39c9/analysis_1.py | Lines: 103-141

data-preprocessing variable-classification keyword-matching veterinary-research eimeria

function explore_data

Performs comprehensive exploratory data analysis on a pandas DataFrame, printing dataset overview, data types, missing values, descriptive statistics, and identifying categorical and numerical variables.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/5a059cb7-3903-4020-8519-14198d1f39c9/analysis_1.py | Lines: 72-97

data-exploration EDA exploratory-data-analysis data-profiling pandas

function load_data

Loads a CSV dataset from a specified filepath using pandas, with fallback to creating sample data if the file is not found.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/5a059cb7-3903-4020-8519-14198d1f39c9/analysis_1.py | Lines: 24-34

data-loading csv pandas file-io error-handling

function detect_outliers_iqr

Detects extreme outliers in a pandas Series using the Interquartile Range (IQR) method with a configurable multiplier (default 3.0).

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/5021ab2a-8cdd-44cb-81ad-201598352e39/analysis_1.py | Lines: 68-84

outlier-detection IQR interquartile-range data-cleaning anomaly-detection

function clean_for_json_v2

Recursively traverses nested data structures (dicts, lists) and sanitizes numeric values by converting NaN and Inf to None, and numpy types to native Python types for JSON serialization.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/e9b7c942-87b5-4a6f-865e-e7a0d62fb0a1/analysis_2.py | Lines: 404-420

json serialization data-cleaning numpy nan-handling

function clean_for_json_v8

Recursively traverses and converts a nested data structure (dicts, lists, numpy types, pandas NaN) into JSON-serializable Python primitives.

File: /tf/active/vicechatdev/vice_ai/smartstat_scripts/d1e252f5-950c-4ad7-b425-86b4b02c3c62/analysis_5.py | Lines: 384-400

json serialization data-cleaning numpy pandas

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