datafort_utilities

DataFort Utilities Module

This module provides utility procedures for data frame operations including: - Data inspection: head, tail, shape, info, empty - Data manipulation: clear, sample, shuffle - Row operations: apply_to_row_real, apply_to_all_rows_real

All procedures are standalone functions prefixed with df_.

Uses

Abstract Interfaces

abstract interface

public function pipe_func(df_in) result(df_out)

Arguments

Type	Intent	Optional	Attributes		Name
type(data_frame),	intent(in)			::	df_in

Return Value type(data_frame)

abstract interface

public function row_func_real(row_values, num_cols) result(output)

Arguments

Type	Intent	Optional	Attributes		Name
real(kind=rk),	intent(in),		dimension(:)	::	row_values
integer,	intent(in)			::	num_cols

Return Value real(kind=rk)

Functions

public function df_apply_to_all_rows_real(df, func) result(outputs)

Apply a function to all rows

Arguments

Type	Intent	Optional	Attributes		Name
type(data_frame),	intent(in)			::	df
procedure(row_func_real)				::	func

Return Value real(kind=rk), dimension(:), allocatable

public function df_apply_to_row_real(df, row_idx, func) result(output)

Apply a function to a specific row

Arguments

Type	Intent		Name
type(data_frame),	intent(in)	::	df
integer,	intent(in)	::	row_idx
procedure(row_func_real)		::	func

Return Value real(kind=rk)

public pure function df_empty(df) result(is_empty)

Check if dataframe is empty (no rows or no columns)

Arguments

Type	Intent	Optional	Attributes		Name
type(data_frame),	intent(in)			::	df

Return Value logical

public function df_equals(df1, df2) result(is_equal)

Check if two dataframes are identical

Arguments

Type	Intent	Optional	Attributes		Name
type(data_frame),	intent(in)			::	df1
type(data_frame),	intent(in)			::	df2

Return Value logical

public function df_head(df, n) result(head_df)

Return first n rows as a new dataframe

Arguments

Type	Intent	Optional	Attributes		Name
type(data_frame),	intent(in)			::	df
integer,	intent(in),	optional		::	n

Return Value type(data_frame)

public function df_nlargest_integer(df, n, col_index) result(result_df)

Return dataframe with n largest values in an integer column

Arguments

Type	Intent		Name
type(data_frame),	intent(in)	::	df
integer,	intent(in)	::	n
integer,	intent(in)	::	col_index

Return Value type(data_frame)

public function df_nlargest_real(df, n, col_index) result(result_df)

Return dataframe with n largest values in a real column

Arguments

Type	Intent		Name
type(data_frame),	intent(in)	::	df
integer,	intent(in)	::	n
integer,	intent(in)	::	col_index

Return Value type(data_frame)

public function df_nsmallest_integer(df, n, col_index) result(result_df)

Return dataframe with n smallest values in an integer column

Arguments

Type	Intent		Name
type(data_frame),	intent(in)	::	df
integer,	intent(in)	::	n
integer,	intent(in)	::	col_index

Return Value type(data_frame)

public function df_nsmallest_real(df, n, col_index) result(result_df)

Return dataframe with n smallest values in a real column

Arguments

Type	Intent		Name
type(data_frame),	intent(in)	::	df
integer,	intent(in)	::	n
integer,	intent(in)	::	col_index

Return Value type(data_frame)

public function df_pipe(df, func) result(result_df)

Apply a custom function to a dataframe (for method chaining)

Arguments

Type	Intent	Optional	Attributes		Name
type(data_frame),	intent(in)			::	df
procedure(pipe_func)				::	func

Return Value type(data_frame)

public function df_sample(df, n, seed) result(sampled_df)

Get n random rows from the dataframe

Arguments

Type	Intent	Optional		Name
type(data_frame),	intent(in)		::	df
integer,	intent(in)		::	n
integer,	intent(in),	optional	::	seed

Return Value type(data_frame)

public function df_shape(df) result(dims)

Return shape as [nrows, ncols]

Arguments

Type	Intent	Optional	Attributes		Name
type(data_frame),	intent(in)			::	df

Return Value integer, dimension(2)

private function df_slice_rows(df, start_row, end_row) result(new_df)

Internal: Slice rows to create a new data frame

Arguments

Type	Intent		Name
type(data_frame),	intent(in)	::	df
integer,	intent(in)	::	start_row
integer,	intent(in)	::	end_row

Return Value type(data_frame)

public function df_tail(df, n) result(tail_df)

Return last n rows as a new dataframe

Arguments

Type	Intent	Optional	Attributes		Name
type(data_frame),	intent(in)			::	df
integer,	intent(in),	optional		::	n

Return Value type(data_frame)

public function df_to_array_real(df) result(array)

Convert dataframe to 2D real array

Arguments

Type	Intent	Optional	Attributes		Name
type(data_frame),	intent(in)			::	df

Return Value real(kind=rk), dimension(:, :), allocatable

Subroutines

private subroutine copy_filtered_column(source_df, target_df, col_index, selected_rows)

Internal: Copy filtered column from source to target

Arguments

Type	Intent	Attributes		Name
type(data_frame),	intent(in)		::	source_df
type(data_frame),	intent(inout)		::	target_df
integer,	intent(in)		::	col_index
integer,	intent(in),	dimension(:)	::	selected_rows

public subroutine df_clear(df)

Clear the dataframe (destroy and re-initialize)

Arguments

Type	Intent	Optional	Attributes		Name
type(data_frame),	intent(inout)			::	df

public subroutine df_info(df, unit)

Print information about the dataframe

Arguments

Type	Intent	Optional	Attributes		Name
type(data_frame),	intent(in)			::	df
integer,	intent(in),	optional		::	unit

public subroutine df_shuffle(df, seed)

Shuffle all rows randomly in place

Arguments

Type	Intent	Optional	Attributes		Name
type(data_frame),	intent(inout)			::	df
integer,	intent(in),	optional		::	seed

private subroutine reorder_all_columns(df, indices)

Internal: Reorder all columns according to index array

Arguments

Type	Intent	Optional	Attributes		Name
type(data_frame),	intent(inout)			::	df
integer,	intent(in),		dimension(:)	::	indices

datafort_utilities Module

Contents

Abstract Interfaces

Functions

Subroutines

Uses

Abstract Interfaces

abstract interface

public function pipe_func(df_in) result(df_out)

Arguments

Return Value type(data_frame)

abstract interface

public function row_func_real(row_values, num_cols) result(output)

Arguments

Return Value real(kind=rk)

Functions

public function df_apply_to_all_rows_real(df, func) result(outputs)

Arguments

Return Value real(kind=rk), dimension(:), allocatable

public function df_apply_to_row_real(df, row_idx, func) result(output)

Arguments

Return Value real(kind=rk)

public pure function df_empty(df) result(is_empty)

Arguments

Return Value logical

public function df_equals(df1, df2) result(is_equal)

Arguments

Return Value logical

public function df_head(df, n) result(head_df)

Arguments

Return Value type(data_frame)

public function df_nlargest_integer(df, n, col_index) result(result_df)

Arguments

Return Value type(data_frame)

public function df_nlargest_real(df, n, col_index) result(result_df)

Arguments

Return Value type(data_frame)

public function df_nsmallest_integer(df, n, col_index) result(result_df)

Arguments

Return Value type(data_frame)

public function df_nsmallest_real(df, n, col_index) result(result_df)

Arguments

Return Value type(data_frame)

public function df_pipe(df, func) result(result_df)

Arguments

Return Value type(data_frame)

public function df_sample(df, n, seed) result(sampled_df)

Arguments

Return Value type(data_frame)

public function df_shape(df) result(dims)

Arguments

Return Value integer, dimension(2)

private function df_slice_rows(df, start_row, end_row) result(new_df)

Arguments

Return Value type(data_frame)

public function df_tail(df, n) result(tail_df)

Arguments

Return Value type(data_frame)

public function df_to_array_real(df) result(array)

Arguments

Return Value real(kind=rk), dimension(:, :), allocatable

Subroutines

private subroutine copy_filtered_column(source_df, target_df, col_index, selected_rows)

Arguments

public subroutine df_clear(df)

Arguments

public subroutine df_info(df, unit)

Arguments

public subroutine df_shuffle(df, seed)

Arguments

private subroutine reorder_all_columns(df, indices)

Arguments