Uses of Class
com.leumanuel.woozydata.model.DataFrame

Packages that use DataFrame

Package	Description
com.leumanuel.woozydata
com.leumanuel.woozydata.controller
com.leumanuel.woozydata.model
com.leumanuel.woozydata.repository
com.leumanuel.woozydata.service
com.leumanuel.woozydata.util

Uses of DataFrame in com.leumanuel.woozydata

Methods in com.leumanuel.woozydata that return DataFrame

Modifier and Type	Method	Description
DataFrame	Woozydata.analyze(String column)	Analyzes a specific column for statistical measures and patterns.
DataFrame	Woozydata.bin(String column, int bins)
DataFrame	Woozydata.clean()	Performs automatic data cleaning on the current DataFrame.
DataFrame	Woozydata.concat(DataFrame other, boolean axis)
DataFrame	Woozydata.convert(Map<String,Class<?>> typeMap)	Converts column data types according to the specified type map.
DataFrame	Woozydata.correlation(String... columns)
DataFrame	Woozydata.decompose(String timeCol, String valueCol)
DataFrame	Woozydata.detectOutliers(String timeCol, String valueCol)
DataFrame	Woozydata.dropDupes(String... columns)	Removes duplicate rows based on specified columns.
DataFrame	Woozydata.dropNa()	Removes rows containing null values from the DataFrame.
DataFrame	Woozydata.dummies(String... columns)
DataFrame	Woozydata.fillNa(Object value)	Fills null values in all columns with a specified value.
DataFrame	Woozydata.fillNaColumns(Object value, String... columns)
DataFrame	Woozydata.forecast(String timeCol, String valueCol, int periods)
DataFrame	Woozydata.fromCsv(String filePath)	Loads data from a CSV file into a DataFrame.
DataFrame	Woozydata.fromJson(String filePath)	Loads data from a JSON file into a DataFrame.
DataFrame	Woozydata.fromMongo(String connectionString, String dbName, String collection)	Connects to MongoDB and loads data from a collection into a DataFrame.
DataFrame	Woozydata.fromXlsx(String filePath)	Loads data from an Excel file into a DataFrame.
DataFrame	Woozydata.groupBy(String... columns)
DataFrame	Woozydata.interpolate(String method, String... columns)
DataFrame	Woozydata.logisticReg(String xCol, String yCol)
DataFrame	Woozydata.melt(String[] idVars, String[] valueVars)	Reshapes data from wide to long format.
DataFrame	Woozydata.merge(DataFrame other, String how, String... on)
DataFrame	Woozydata.missingAnalysis()
DataFrame	Woozydata.multipleReg(String[] xCols, String yCol)
DataFrame	Woozydata.normalize(String... columns)	Normalizes specified columns to range [0,1].
DataFrame	Woozydata.outlierAnalysis(String... columns)	Performs quick comprehensive analysis of specified columns.
DataFrame	Woozydata.pivot(String index, String columns, String values)	Creates a pivot table from the DataFrame.
DataFrame	Woozydata.polynomialReg(String xCol, String yCol, int degree)
DataFrame	Woozydata.quickAnalysis(String... columns)
DataFrame	Woozydata.reshape(int rows, int cols)
DataFrame	Woozydata.rollingWindow(String column, int window, String func)
DataFrame	Woozydata.sample(int n)
DataFrame	Woozydata.seasonalAdjust(String timeCol, String valueCol)
DataFrame	Woozydata.select(String... columns)
DataFrame	Woozydata.sort(String... columns)
DataFrame	Woozydata.standardize(String... columns)	Standardizes specified columns using z-score normalization.
DataFrame	Woozydata.timeAnalysis(String dateCol, String valueCol)

Methods in com.leumanuel.woozydata with parameters of type DataFrame

Modifier and Type	Method	Description
DataFrame	Woozydata.concat(DataFrame other, boolean axis)
DataFrame	Woozydata.merge(DataFrame other, String how, String... on)

Uses of DataFrame in com.leumanuel.woozydata.controller

Methods in com.leumanuel.woozydata.controller that return DataFrame

Modifier and Type	Method	Description
DataFrame	DataController.analyze(String column)	Performs basic analysis on a specified column.
DataFrame	DataController.bin(String column, int bins)	Bins continuous data into discrete intervals.
DataFrame	DataController.clean()	Performs general data cleaning operations.
DataFrame	DataController.concat(DataFrame other, boolean axis)	Concatenates current DataFrame with another DataFrame.
DataFrame	DataController.convert(Map<String,Class<?>> typeMap)	Converts column types according to the provided type map.
DataFrame	DataController.correlation(String... columns)	Calculates correlation matrix for specified columns.
DataFrame	DataController.decompose(String timeCol, String valueCol)	Decomposes time series into components.
DataFrame	DataController.detectOutliers(String timeCol, String valueCol)	Detects outliers in time series data.
DataFrame	DataController.dropDupes(String... columns)	Removes duplicate rows based on specified columns.
DataFrame	DataController.dropNa()	Removes rows with null values.
DataFrame	DataController.dummies(String... columns)	Creates dummy/indicator variables.
DataFrame	DataController.fillNa(Object value)	Fills null values with a specified value.
DataFrame	DataController.fillNaColumns(Object value, String... columns)	Fills null values in specified columns with a given value.
DataFrame	DataController.forecast(String timeCol, String valueCol, int periods)	Forecasts future values using time series analysis.
DataFrame	DataController.fromCsv(String filePath)	Reads data from a CSV file and creates a DataFrame.
DataFrame	DataController.fromJson(String filePath)	Reads data from a JSON file and creates a DataFrame.
DataFrame	DataController.fromMongo(String connectionString, String dbName, String collection)	Reads data from a MongoDB collection and creates a DataFrame.
DataFrame	DataController.fromXlsx(String filePath)	Reads data from an Excel (XLSX) file and creates a DataFrame.
DataFrame	DataController.groupBy(String... columns)	Groups DataFrame by specified columns.
DataFrame	DataController.interpolate(String method, String... columns)	Interpolates missing values using specified method.
DataFrame	DataController.logisticReg(String xCol, String yCol)	Performs logistic regression.
DataFrame	DataController.melt(String[] idVars, String[] valueVars)	Unpivots DataFrame from wide to long format.
DataFrame	DataController.merge(DataFrame other, String how, String... on)	Merges current DataFrame with another DataFrame.
DataFrame	DataController.missingAnalysis()	Analyzes missing values in the DataFrame.
DataFrame	DataController.multipleReg(String[] xCols, String yCol)	Performs multiple linear regression.
DataFrame	DataController.normalize(String... columns)	Normalizes specified columns to [0,1] range.
DataFrame	DataController.outlierAnalysis(String... columns)	Identifies and analyzes outliers in specified columns.
DataFrame	DataController.pivot(String index, String columns, String values)	Creates a pivot table from the DataFrame.
DataFrame	DataController.polynomialReg(String xCol, String yCol, int degree)	Performs polynomial regression.
DataFrame	DataController.quickAnalysis(String... columns)	Performs quick exploratory data analysis on specified columns.
DataFrame	DataController.reshape(int rows, int cols)	Reshapes the DataFrame to specified dimensions.
DataFrame	DataController.rollingWindow(String column, int window, String func)	Applies function over rolling window.
DataFrame	DataController.sample(int n)	Creates a random sample of rows from the DataFrame.
DataFrame	DataController.seasonalAdjust(String timeCol, String valueCol)	Performs seasonal adjustment on time series.
DataFrame	DataController.select(String... columns)	Selects specified columns from DataFrame.
DataFrame	DataController.sort(String... columns)	Sorts DataFrame by specified columns.
DataFrame	DataController.standardize(String... columns)	Standardizes specified columns (z-score normalization).
DataFrame	DataController.timeAnalysis(String dateCol, String valueCol)	Performs time-based analysis on a datetime column and corresponding value column.

Methods in com.leumanuel.woozydata.controller with parameters of type DataFrame

Modifier and Type	Method	Description
DataFrame	DataController.concat(DataFrame other, boolean axis)	Concatenates current DataFrame with another DataFrame.
DataFrame	DataController.merge(DataFrame other, String how, String... on)	Merges current DataFrame with another DataFrame.

Uses of DataFrame in com.leumanuel.woozydata.model

Methods in com.leumanuel.woozydata.model that return DataFrame

Modifier and Type	Method	Description
DataFrame	DataFrame.clean()	Performs automatic data cleaning operations.
DataFrame	DataFrame.dropDupes()	Removes duplicate rows from the DataFrame.
DataFrame	DataFrame.dropNull()	Removes rows containing null values.
DataFrame	DataFrame.fill(Object value)	Fills null values with a specified value.
DataFrame	DataFrame.fillNa(Object value, String... columns)	Fills null values in specified columns.
DataFrame	DataFrame.fixTypes()	Automatically converts data types based on content.
DataFrame	DataFrame.rank(String... columns)	Ranks (sorts) the DataFrame based on specified columns.
DataFrame	DataFrame.select(String... columns)	Creates a new DataFrame containing only the specified columns.

Uses of DataFrame in com.leumanuel.woozydata.repository

Methods in com.leumanuel.woozydata.repository that return DataFrame

Modifier and Type	Method	Description
DataFrame	MongoDbConnector.readCollection(String collectionName)	Reads a MongoDB collection into a DataFrame.

Uses of DataFrame in com.leumanuel.woozydata.service

Methods in com.leumanuel.woozydata.service that return DataFrame

Modifier and Type	Method	Description
DataFrame	DataAnalysisService.analyze(DataFrame df, String column)	Analyzes a specified column in the DataFrame and calculates basic statistical measures.
DataFrame	DataStatisticsService.apply(DataFrame df, String column, Function<List<Object>,Object> func)	Applies a function to a column of the DataFrame.
DataFrame	DataCleaningService.astype(DataFrame df, Map<String,Class<?>> typeMap)	Converts columns to specified data types.
DataFrame	DataCleaningService.clean(DataFrame df)	Performs comprehensive data cleaning including removing nulls, duplicates, and filling remaining nulls.
DataFrame	MergeService.concat(DataFrame df1, DataFrame df2, boolean axis)	Concatenates two DataFrames either vertically or horizontally.
DataFrame	DataCleaningService.convert(DataFrame df, Map<String,Class<?>> typeMap)	Converts column data types according to the provided type map.
DataFrame	DataAnalysisService.correlation(DataFrame df)	Performs correlation analysis between numeric columns.
DataFrame	TimeSeriesAnalysisService.decompose(DataFrame df, String timeCol, String valueCol)	Decomposes time series into trend, seasonal, and residual components.
DataFrame	TimeSeriesAnalysisService.detectTimeSeriesOutliers(DataFrame df, String timeCol, String valueCol)	Detects outliers in time series data using IQR method.
DataFrame	DataCleaningService.dropDuplicates(DataFrame df, String... columns)	Removes duplicate rows from the DataFrame based on specified columns.
DataFrame	DataCleaningService.dropNa(DataFrame df)	Removes all rows containing missing values from the DataFrame.
DataFrame	DataCleaningService.fillNa(DataFrame df, Object value)	Replaces all missing values in the DataFrame with a specified value.
DataFrame	DataCleaningService.fillNaColumns(DataFrame df, Object value, String... columns)	Replaces missing values in specified columns with a given value.
DataFrame	TimeSeriesAnalysisService.forecast(DataFrame df, String timeCol, String valueCol, int periods)	Generates forecasts for future time periods.
DataFrame	DataStatisticsService.groupBy(DataFrame df, String... columns)	Groups DataFrame by specified columns and calculates aggregate statistics.
DataFrame	DataCleaningService.interpolate(DataFrame df, String method, String... columns)	Interpolates missing values in specified columns using various methods.
DataFrame	DataCleaningService.isna(DataFrame df)	Creates a boolean mask indicating missing values in the DataFrame.
DataFrame	DataStatisticsService.join(DataFrame left, DataFrame right, String[] leftCols, String[] rightCols)	Joins two DataFrames based on matching column values.
DataFrame	RegressionService.logisticRegression(DataFrame df, String xCol, String yCol)	Performs logistic regression analysis for binary classification.
DataFrame	DataStatisticsService.melt(DataFrame df, String[] idVars, String[] valueVars)	Unpivots DataFrame from wide to long format.
DataFrame	MergeService.merge(DataFrame df1, DataFrame df2, String how, String... on)	Merges two DataFrames based on matching columns.
DataFrame	AdvancedAnalysisService.missingAnalysis(DataFrame df)	Analyzes missing values in all columns of the DataFrame.
DataFrame	RegressionService.multipleRegression(DataFrame df, String[] xCols, String yCol)	Performs multiple linear regression analysis.
DataFrame	DataCleaningService.normalize(DataFrame df, String... columns)	Normalizes specified numeric columns to range [0,1].
DataFrame	DataCleaningService.notna(DataFrame df)	Creates a boolean mask indicating non-missing values in the DataFrame.
DataFrame	AdvancedAnalysisService.outlierAnalysis(DataFrame df, String... columns)	Analyzes outliers in specified numeric columns using both Z-score and IQR methods.
DataFrame	DataStatisticsService.pivot(DataFrame df, String index, String columns, String values, String aggFunc)	Creates a pivot table from the DataFrame data.
DataFrame	RegressionService.polynomialRegression(DataFrame df, String xCol, String yCol, int degree)	Performs polynomial regression analysis.
DataFrame	DataCleaningService.replace(DataFrame df, Object oldValue, Object newValue)	Replaces all occurrences of a specific value with a new value throughout the DataFrame.
DataFrame	MergeService.reshape(DataFrame df, int rows, int cols)	Reshapes DataFrame into specified dimensions.
DataFrame	StatisticalService.sample(DataFrame df, int n)	Creates a random sample of specified size from the DataFrame.
DataFrame	TimeSeriesAnalysisService.seasonalAdjustment(DataFrame df, String timeCol, String valueCol)	Removes seasonal component from time series.
DataFrame	StatisticalService.select(DataFrame df, String... columns)	Selects specified columns from the DataFrame.
DataFrame	DataStatisticsService.sort(DataFrame df, String... columns)	Sorts DataFrame by specified columns in ascending order.
DataFrame	DataStatisticsService.sort(DataFrame df, String[] columns, boolean[] ascending)	Sorts DataFrame by specified columns.
DataFrame	DataCleaningService.standardize(DataFrame df, String... columns)	Standardizes specified numeric columns using z-score normalization (x - mean) / std.
DataFrame	AdvancedAnalysisService.timeAnalysis(DataFrame df, String dateCol, String valueCol)	Performs time series analysis on a DataFrame with date and value columns.
DataFrame	DataAnalysisService.timeSeriesAnalysis(DataFrame df, String timeColumn, String valueColumn, int windowSize)	Performs time series analysis.
DataFrame	DataStatisticsService.transform(DataFrame df, String column, Function<Object,Object> func)	Transforms values in a specified column using a provided function.

Methods in com.leumanuel.woozydata.service that return types with arguments of type DataFrame

Modifier and Type	Method	Description
Map<String,DataFrame>	DataExportService.createAnalysisReport(DataFrame df)	Creates a standardized analysis report with multiple metrics.
Map<List<Object>,DataFrame>	DataCleaningService.groupBy(DataFrame df, String... columns)	Groups DataFrame by specified columns.

Methods in com.leumanuel.woozydata.service with parameters of type DataFrame

Modifier and Type	Method	Description
DataFrame	DataAnalysisService.analyze(DataFrame df, String column)	Analyzes a specified column in the DataFrame and calculates basic statistical measures.
Map<String,Double>	StatisticalService.anova(DataFrame df, String... columns)	Performs ANOVA test on multiple columns.
DataFrame	DataStatisticsService.apply(DataFrame df, String column, Function<List<Object>,Object> func)	Applies a function to a column of the DataFrame.
DataFrame	DataCleaningService.astype(DataFrame df, Map<String,Class<?>> typeMap)	Converts columns to specified data types.
double	DataAnalysisService.avg(DataFrame df, String column)	Calculates the arithmetic mean (average) of values in a specified column.
double	DataAnalysisService.calculateCoefficientOfVariation(DataFrame dataFrame, String column)	Calculates the coefficient of variation (CV) for a specified column.
double	DataStatisticsService.calculateCovariance(DataFrame df, String col1, String col2)	Calculates covariance between two numeric columns.
Map<Object,Long>	DataStatisticsService.calculateFrequency(DataFrame df, String column)	Calculates frequency distribution of values in a column.
double	DataStatisticsService.calculateIQR(DataFrame df, String column)	Calculates Interquartile Range (IQR) of a numeric column.
double	DataStatisticsService.calculateKurtosis(DataFrame df, String column)	Calculates kurtosis of a numeric column.
double	DataAnalysisService.calculateMean(DataFrame dataFrame, String column)	Calculates the arithmetic mean (average) of numeric values in a specified column.
double	DataAnalysisService.calculateMedian(DataFrame dataFrame, String column)	Calculates the median value of a specified column.
Object	DataAnalysisService.calculateMode(DataFrame dataFrame, String column)	Calculates the mode (most frequent value) of a specified column.
List<Object>	DataAnalysisService.calculateMultipleMode(DataFrame dataFrame, String column)	Calculates multiple modes if they exist in the specified column.
double	RegressionService.calculatePearsonCorrelation(DataFrame dataFrame, String column1, String column2)	Calculates Pearson correlation coefficient between two columns.
double	DataAnalysisService.calculatePopulationStandardDeviation(DataFrame dataFrame, String column)	Calculates the population standard deviation of a specified column.
double	DataStatisticsService.calculateQuantile(DataFrame df, String column, double q)	Calculates specified quantile of a numeric column.
double	RegressionService.calculateRSquared(DataFrame df, String xCol, String yCol)	Calculates R-squared (coefficient of determination) for linear regression.
double	DataStatisticsService.calculateSkewness(DataFrame df, String column)	Calculates skewness of a numeric column.
double	DataAnalysisService.calculateStandardDeviation(DataFrame dataFrame, String column)	Calculates the standard deviation of a specified column.
double	DataAnalysisService.calculateVariance(DataFrame dataFrame, String column)	Calculates the variance of a specified column.
Map<String,Double>	StatisticalService.chiSquareTest(DataFrame df, String col1, String col2)	Performs chi-square test for independence.
DataFrame	DataCleaningService.clean(DataFrame df)	Performs comprehensive data cleaning including removing nulls, duplicates, and filling remaining nulls.
DataFrame	MergeService.concat(DataFrame df1, DataFrame df2, boolean axis)	Concatenates two DataFrames either vertically or horizontally.
DataFrame	DataCleaningService.convert(DataFrame df, Map<String,Class<?>> typeMap)	Converts column data types according to the provided type map.
DataFrame	DataAnalysisService.correlation(DataFrame df)	Performs correlation analysis between numeric columns.
Map<String,DataFrame>	DataExportService.createAnalysisReport(DataFrame df)	Creates a standardized analysis report with multiple metrics.
void	DataExportService.customExport(DataFrame df, List<String> metrics, String filePath)	Custom export with user-selected metrics.
DataFrame	TimeSeriesAnalysisService.decompose(DataFrame df, String timeCol, String valueCol)	Decomposes time series into trend, seasonal, and residual components.
Map<String,Map<String,Double>>	DataStatisticsService.describe(DataFrame df)	Generates comprehensive descriptive statistics for numeric columns.
DataFrame	TimeSeriesAnalysisService.detectTimeSeriesOutliers(DataFrame df, String timeCol, String valueCol)	Detects outliers in time series data using IQR method.
DataFrame	DataCleaningService.dropDuplicates(DataFrame df, String... columns)	Removes duplicate rows from the DataFrame based on specified columns.
DataFrame	DataCleaningService.dropNa(DataFrame df)	Removes all rows containing missing values from the DataFrame.
void	DataExportService.exportToCSV(DataFrame df, String filePath)	Exports DataFrame content to a CSV (Comma-Separated Values) file.
void	DataExportService.exportToExcel(DataFrame df, String filePath)	Exports DataFrame content to a Excel file.
void	DataExportService.exportToHTML(DataFrame df, String filePath)	Exports DataFrame content to a HTML file.
void	DataExportService.exportToJSON(DataFrame df, String filePath)	Exports DataFrame content to a JSON (JavaScript Object Notation) file.
void	DataExportService.exportToLatex(DataFrame df, String filePath)	Exports DataFrame content to a Latex file.
DataFrame	DataCleaningService.fillNa(DataFrame df, Object value)	Replaces all missing values in the DataFrame with a specified value.
DataFrame	DataCleaningService.fillNaColumns(DataFrame df, Object value, String... columns)	Replaces missing values in specified columns with a given value.
DataFrame	TimeSeriesAnalysisService.forecast(DataFrame df, String timeCol, String valueCol, int periods)	Generates forecasts for future time periods.
Map<String,Object>	AdvancedAnalysisService.fullReport(DataFrame df, String... columns)	Generates a comprehensive statistical report for specified columns.
double[]	DataStatisticsService.getColumnValues(DataFrame df, String column)	Gets numeric values from a specified column.
Map<String,Double>	DataAnalysisService.getDispersionStatistics(DataFrame dataFrame, String column)	Generates a summary of dispersion statistics for a specified column.
Map<Object,Long>	DataAnalysisService.getFrequencyDistribution(DataFrame dataFrame, String column)	Gets the frequency distribution of values in a specified column.
Map<List<Object>,DataFrame>	DataCleaningService.groupBy(DataFrame df, String... columns)	Groups DataFrame by specified columns.
DataFrame	DataStatisticsService.groupBy(DataFrame df, String... columns)	Groups DataFrame by specified columns and calculates aggregate statistics.
DataFrame	DataCleaningService.interpolate(DataFrame df, String method, String... columns)	Interpolates missing values in specified columns using various methods.
DataFrame	DataCleaningService.isna(DataFrame df)	Creates a boolean mask indicating missing values in the DataFrame.
DataFrame	DataStatisticsService.join(DataFrame left, DataFrame right, String[] leftCols, String[] rightCols)	Joins two DataFrames based on matching column values.
DataFrame	RegressionService.logisticRegression(DataFrame df, String xCol, String yCol)	Performs logistic regression analysis for binary classification.
Map<String,Double>	DataStatisticsService.mannWhitney(DataFrame df, String col1, String col2)	Performs Mann-Whitney U test between two columns.
DataFrame	DataStatisticsService.melt(DataFrame df, String[] idVars, String[] valueVars)	Unpivots DataFrame from wide to long format.
DataFrame	MergeService.merge(DataFrame df1, DataFrame df2, String how, String... on)	Merges two DataFrames based on matching columns.
DataFrame	AdvancedAnalysisService.missingAnalysis(DataFrame df)	Analyzes missing values in all columns of the DataFrame.
DataFrame	RegressionService.multipleRegression(DataFrame df, String[] xCols, String yCol)	Performs multiple linear regression analysis.
DataFrame	DataCleaningService.normalize(DataFrame df, String... columns)	Normalizes specified numeric columns to range [0,1].
DataFrame	DataCleaningService.notna(DataFrame df)	Creates a boolean mask indicating non-missing values in the DataFrame.
DataFrame	AdvancedAnalysisService.outlierAnalysis(DataFrame df, String... columns)	Analyzes outliers in specified numeric columns using both Z-score and IQR methods.
DataFrame	DataStatisticsService.pivot(DataFrame df, String index, String columns, String values, String aggFunc)	Creates a pivot table from the DataFrame data.
DataFrame	RegressionService.polynomialRegression(DataFrame df, String xCol, String yCol, int degree)	Performs polynomial regression analysis.
DataFrame	DataCleaningService.replace(DataFrame df, Object oldValue, Object newValue)	Replaces all occurrences of a specific value with a new value throughout the DataFrame.
DataFrame	MergeService.reshape(DataFrame df, int rows, int cols)	Reshapes DataFrame into specified dimensions.
DataFrame	StatisticalService.sample(DataFrame df, int n)	Creates a random sample of specified size from the DataFrame.
DataFrame	TimeSeriesAnalysisService.seasonalAdjustment(DataFrame df, String timeCol, String valueCol)	Removes seasonal component from time series.
DataFrame	StatisticalService.select(DataFrame df, String... columns)	Selects specified columns from the DataFrame.
Map<String,Double>	StatisticalService.shapiroWilkTest(DataFrame df, String column)	Performs Shapiro-Wilk test for normality on a numeric column.
double[]	RegressionService.simpleLinearRegression(DataFrame dataFrame, String xColumn, String yColumn)	Performs simple linear regression between two columns.
DataFrame	DataStatisticsService.sort(DataFrame df, String... columns)	Sorts DataFrame by specified columns in ascending order.
DataFrame	DataStatisticsService.sort(DataFrame df, String[] columns, boolean[] ascending)	Sorts DataFrame by specified columns.
DataFrame	DataCleaningService.standardize(DataFrame df, String... columns)	Standardizes specified numeric columns using z-score normalization (x - mean) / std.
Map<String,Double>	DataAnalysisService.stats(DataFrame df, String column)	Calculates statistical measures for a specified column.
Map<String,Double>	DataCleaningService.stats(DataFrame df, String column)	Calculates basic statistics for a specified column.
double	DataAnalysisService.sum(DataFrame df, String column)	Calculates the sum of all values in a specified column.
DataFrame	AdvancedAnalysisService.timeAnalysis(DataFrame df, String dateCol, String valueCol)	Performs time series analysis on a DataFrame with date and value columns.
DataFrame	DataAnalysisService.timeSeriesAnalysis(DataFrame df, String timeColumn, String valueColumn, int windowSize)	Performs time series analysis.
DataFrame	DataStatisticsService.transform(DataFrame df, String column, Function<Object,Object> func)	Transforms values in a specified column using a provided function.
Map<String,Double>	StatisticalService.tTest(DataFrame df, String col1, String col2)	Performs t-test between two columns.

Method parameters in com.leumanuel.woozydata.service with type arguments of type DataFrame

Modifier and Type	Method	Description
void	DataExportService.exportToPowerBI(Map<String,DataFrame> results, String filePath)	Exports all analysis results to a single Excel file for PowerBI.

Uses of DataFrame in com.leumanuel.woozydata.util

Methods in com.leumanuel.woozydata.util that return DataFrame

Modifier and Type	Method	Description
static DataFrame	DataTransformUtil.createMetadata(DataFrame df)	Creates metadata DataFrame describing the structure of input DataFrame.
static DataFrame	DataTransformUtil.formatForPowerBI(DataFrame df)	Formats DataFrame data for PowerBI compatibility.
static DataFrame	DataCsvReader.readCSV(String filePath)	Reads a CSV file and converts it to a DataFrame.
static DataFrame	DataJsonReader.readJSON(String filePath)	Reads a JSON file and converts it to a DataFrame.
static DataFrame	DataXlsxReader.readXLSX(String filePath)	Reads an Excel file and converts it to a DataFrame.

Methods in com.leumanuel.woozydata.util with parameters of type DataFrame

Modifier and Type	Method	Description
static DataFrame	DataTransformUtil.createMetadata(DataFrame df)	Creates metadata DataFrame describing the structure of input DataFrame.
static void	DataExporter.exportToCSV(DataFrame dataFrame, String filePath)	Exports DataFrame data to a CSV file.
static void	DataExporter.exportToJSON(DataFrame dataFrame, String filePath)	Exports DataFrame data to a JSON file.
static DataFrame	DataTransformUtil.formatForPowerBI(DataFrame df)	Formats DataFrame data for PowerBI compatibility.