Welcome to the documentation for IQDM-Analytics!¶

IQDM-Analytics¶

What does it do?¶

IQDM Analytics is a desktop application that mines IMRT QA reports with IQDM-PDF and performs statistical analysis.

Executables¶

Single-file executables are available. See attachments in the latest release.

Other information¶

This library is part of the IMRT QA Data Mining (IQDM) project for the AAPM IMRT Working Group (WGIMRT).

Free software: MIT license
Documentation: Read the docs

IQDM Analytics screenshot

Dependencies¶

iqdmpdf - Mine IMRT QA PDF’s
wxPython Phoenix - Build a native GUI on Windows, Mac, or Unix systems
Bokeh - Interactive Web Plotting for Python
NumPy - The fundamental package for scientific computing with Python
selenium - A browser automation framework and ecosystem
PhantomJS - PhantomJS is a headless web browser scriptable with JavaScript
pypubsub - A Python publish-subscribe library

Install and Run¶

If you prefer to run from source:

$ git clone https://github.com/IQDM/IQDM-Analytics.git
$ cd IQDM-Analytics
$ python iqdma_app.py

Note you may have to use pythonw instead of python, depending on your version.

TODO¶

Ability to cancel PDF-Miner thread
Unit testing (non-GUI)
Setup continuous integration
Consolidate/Clean-up UserSettings Dialog code

Credits¶

Development Lead¶

Dan Cutright, University of Chicago Medicine

Contributors¶

Marc Chamberland, University of Vermont Health Network
Serpil Kucuker Dogan, Northwestern Medicine
Mahesh Gopalakrishnan, Northwestern Medicine
Aditya Panchal, AMITA Health
Michael Snyder, Beaumont Health

User Manual¶

This application is part of the IMRT QA Data Mining (IQDM) project for the AAPM IMRT Working Group (WGIMRT).

Introduction¶

IQDM Analytics is a desktop application designed to make IQDM-PDF more user friendly. IQDM-PDF is a python library used to mine data from IMRT QA PDF reports for the purpose of generating control charts, as recommended by AAPM TG-218.

Usage¶

The easiest way to use this application is to download an executable from the attachments in the latest release of IQDM Analytics.

Once you’ve launched the application, click on the PDF Miner icon in the toolbar. From there you can select a directory to scan and another to store a CSV file of mined data. Once this is complete (or if you already have an IQDM-PDF CSV file), click on Open in the toolbar of main window to import the CSV file.

The visuals are created with Bokeh and can be exported to HTML, SVG, or PNG files. Clicking the Save icon in the toolbar will open a window allowing you to apply temporary visual customizations prior to export. Alternatively, you can edit these visuals in Settings to store the changes permanently.

Supported Vendors¶

IQDM-PDF currently supports the following IMRT QA vendors / reports:

Sun Nuclear: SNC Patient
Scandidos: Delta4
PTW: Verisoft

Methods¶

PDF Mining¶

Generally speaking, the text from IMRT QA reports is extracted and sorted into boxes with coordinates, using pdfminer.six. Then IQDM-PDF searches for keywords to locate boxes containing data of interest. For more details, see the IQDM-PDF: How It Works page.

Although IQDM-PDF has very thorough testing, it is prudent for users to manually inspect the CSV file generated. If you find an error, please submit an issue with IQDM-PDF. If you provide an anonymized report reproducing the error, it can be included in the automated tests.

Data Parsing¶

Output from IQDM-PDF will be sorted in the following order:

Patient Name & ID ( & Plan ID/Name/SOPInstanceUID if available)
Analysis parameters (e.g., dose, distance, threshold, etc.)
Measurement date & time (or report date)

If multiple reports are found with this sorting, IQDM Analytics can be customized to select either the first or last report (by file creation timestamp), or be set to the min, mean, or max value (calculated per charting variable). See “Duplicate Value Policy” in Settings.

Control Charts¶

A control chart is simply a plot of chronological data with a center line and control limits (upper and lower). The center line is the mean value of all points. IQDM Analytics calculates a 2-point moving-range,

\[\overline { mR } = \frac { 1 }{ n-1 } \sum _{ i=2 }^{ n }{ \left| { x }_{ i }-{ x }_{ i-1 } \right| }.\]

Control limits (\(CL\)) are calculated with

\[CL=\overline { x } \pm 3\frac { \overline { mR } }{ 1.128 },\]

where \(3\) is the number of standard deviations, which can be customized in Settings. Since the chart is based on a 2-point moving-range, \(1.128\) is used (i.e., the value of \(d_2\)). Note that control limits are bounded if the population it describes also is bounded. For example, the UCL of a gamma pass-rate will not exceed 100%.

The control chart in the main view uses the following acronyms:

IC: In Control
OOC: Out Of Control
UCL: Upper Control Limit
LCL: Lower Control Limit

CSV Parsing¶

If you are opening a CSV file generated by IQDM-PDF, its format will be automatically detected and loaded based on instructions from its matching JSON file found in ~/Apps/iqdm_analytics/csv_templates. If you develop your own data mining script, you can still use IQDM-Analytics if you create a CSV template (JSON formatted). Below is a simple example:

{
  "columns": [
    "patient",
    "plan",
    "field id",
    "image type",
    "date",
    "DD(%)",
    "DTA(mm)",
    "Threshold(%)",
    "Gamma Pass Rate(%)"
  ],
  "analysis_columns": {
    "uid": [0, 1, 2],
    "date": 4,
    "criteria": [5, 6, 7],
    "y": [
      {
        "index": 8,
        "ucl_limit": 100,
        "lcl_limit": 0
      }
    ]
  }
}

columns¶

This is a list of columns to be imported, their values must match EXACTLY with the column header in your CSV.

analysis_columns: uid¶

This is a list of column indices, that when combined, create an ID that is unique to an “observation” or “case”. This is used to catch duplicate reports being read. You may specify as column headers instead of indices.

analysis_columns: date¶

The assigned date for chronological sorting is based on this column index. You may specify as a column header name instead of a column index.

analysis_columns: criteria¶

These indices are used to “widen” the data (i.e., separate your reports by pass-rate criteria). Generally speaking, this is really a list of independent variables.

analysis_columns: y¶

This is a list of dependent variables available for charting. Each item in this list must be a dictionary with the keys index, ucl_limit, lcl_limit. If the charting variable has no bounded control limits, or you do not know them, set the limit values to null (e.g., "ucl_limit": null). The value for index may also be a column header instead of a column index.

Settings¶

The Settings window allows you to customize plot visualizations such as colors, widths/sizes, line styles, and transparency (alpha). Additionaly, there are the following options:

Control Limit standard deviations
- Set the number of standard deviations for UCL/LCL calculations
Duplicate Value Policy
- If multiple reports are found for a given patient/date/ID, use either ‘first’, ‘last’, ‘min’, ‘mean’, or ‘max’ value
- If “Enable Duplicate Detection” is unchecked, all reports will be considered unique observations / cases.
Multi-Threading Jobs
- IQDM-PDF supports multi-threading, set the number of jobs used for PDF parsing
Analyze .pdf only
- IQDM-PDF looks only at .pdf files by default, allow it to try parsing any file

Windows Users¶

The framework used to build this application (wxPython) leverages your operating system’s web viewer to render web pages (such as the Bokeh visuals in this application). Unfortunately, Windows still uses Internet Explorer (IE) emulation. This means there is no drag functionality (so no pan or zoom). These features can be recovered if you install Microsoft Edge Beta. If this is installed, you should be able to check “Enable Edge WebView Backend” in Settings. Note that it is much slower to initialize, but you can pan, zoom, and show/hide plot components when clicking on legend items.

Alternatively, you can export your chart as html or navigate to ~/Apps/iqdm_analytics/temp where the last chart you generated will live as an html file until you render a new one in IQDM Analytics. Then open the file in your browser of choice for full interactive functionality.

Local File Storage¶

IQDM Analytics will create the directory ~/Apps/iqdm_analytics. Your options are stored here as a hidden file .options. This directory also contains csv_templates, logs, and temp directories. The csv_templates contains instructions for CSV parsing - stored as JSON files. The logs contains a iqdma.log file if any python errors have been caught. This file will be helpful when reporting any issues. The temp directory is currently only used for html file storage on Windows.

PyInstaller¶

The executables for IQDM Analytics are generated with PyInstaller, which basically packages a full version of python and necessary libraries. When you run the executable, it unpacks into a temp directory with a location depending on your OS, but starts with _MEIxxxxxx where xxxxxx is a random number. If the application crashes or you kill the application, just note that this folder will not be automatically purged.

IQDM Analytics¶

Data Table¶

A class to sync a data object and list_ctrl

class iqdma.data_table.DataTable(list_ctrl: wx.ListCtrl, data: Optional[dict] = None, columns: Optional[list] = None, widths: Optional[list] = None, formats: Optional[list] = None)[source]¶

Bases: object

Helper class for wx.ListCtrl

Init DataTable class

Parameters

list_ctrl (wx.ListCtrl) – the list_ctrl in the GUI to be updated with data in this class
data (dict) – data should be formatted in a dictionary with keys being the column names and values being lists
columns (list) – the keys of the data object to be visible in the list_ctrl
widths (list) – optionally specify the widths of the columns
formats (list) – optionally specify wx Format values (e.g., wx.LIST_FORMAT_LEFT)

append_row(row: list, layout_only: bool = False)[source]¶

Add a row of data

Parameters

row (list) – data ordered by self.columns
layout_only (bool) – If true, only add row to the GUI

append_row_to_data(row: list)[source]¶

Add a row of data to self.data

Parameters: row (list) – data ordered by self.columns

clear()[source]¶: Delete all data in self.data and clear the table view

property column_count: int¶

Number of columns

Returns: Length of columns
Return type: int

property data_for_csv: list¶

Iterate through data to get a list of csv rows

Returns: list of rows. Each row is a list of column data
Return type: list of lists

data_to_list_of_rows() → list[source]¶

Convert data into a list of rows as needed for list_ctrl

Returns: data in the format of list of rows
Return type: list

delete_all_rows(layout_only: bool = False, force_delete_data: bool = False)[source]¶

Clear all data from data and the layout view

Parameters

layout_only (bool) – If True, do not remove the row from self.data
force_delete_data (bool) – If true, force deletion even if layout is not set

get_csv_rows() → list[source]¶

Convert data to a list of strings for CSV writing

Returns: Each item is a str for a CSV file
Return type: list of str

get_data_in_original_order() → dict[source]¶

Get data in the order it was original set

Returns: keys are column names with voalues of row data
Return type: dict

get_row(row_index: int) → list[source]¶

Get a row of data from self.data with the given row index

Parameters: row_index (int) – retrieve all values from row with this index
Returns: values for the specified row
Return type: list

get_value(row_index: int, column_index: int)[source]¶

Get a specific table value with a column name and row index

Parameters

row_index (int) – retrieve value from row with this index
column_index (int) – retrieve value from column with this index

Returns

value corresponding to provided indices

Return type

any

property has_data: bool¶

Check if there are any rows of data

Returns: True if row_count > 0
Return type: bool

increment_index(evt: Optional[wx.Event] = None, increment: Optional[int] = None)[source]¶

Increment the ListCtrl selection with an event or fixed increment

Parameters

evt (wx.Event) – An event with a GetKeyCode method
increment (int) – If no event is passed, use a fixed index increment

property keys: list¶

Column names

Returns: A copy of columns
Return type: list

property row_count: int¶

Number of rows

Returns: Length of first column in data
Return type: int

property selected_row_data: list¶

Row data from the current selection in wx.ListCtrl

Returns: row data of the currently selected row in the GUI
Return type: list

property selected_row_index: list¶

Get the indices of selected rows in wx.ListCtrl

Returns: List of indices
Return type: list

set_column_width(index: int, width: int)[source]¶

Change the column width in the view

Parameters

index (int) – index of column
width (int) – the specified width

set_column_widths(auto: bool = False)[source]¶

Set all widths in layout based on widths

Parameters: auto (bool) – Use wx.LIST_AUTOSIZE_USEHEADER rather than widths

set_data(data: dict, columns: list, formats: Optional[list] = None, ignore_layout: bool = False)[source]¶

Set data and update layout

Parameters

data (dict) – data should be formatted in a dictionary with keys being the column names and values being lists
columns (list) – the keys of the data object to be visible in the list_ctrl
formats (list) – optionally specify wx Format values (e.g., wx.LIST_FORMAT_LEFT)
ignore_layout (bool) – If true, do not update layout

set_data_in_layout()[source]¶: Set data in layout from data

set_layout_columns()[source]¶: Clear layout and re-add columns

sort_table(evt: wx.EVT_LIST_COL_CLICK)[source]¶

Sort the data based on the clicked column header

Parameters: evt (wx.EVT_LIST_COL_CLICK) – Event from a ListCtrl column header click

Importer¶

Import output from IQDM-PDF

class iqdma.importer.CSVParser(json_file_path: str)[source]¶

Bases: object

Import CSV Template from JSON

Initialization of CSVParser

Parameters: json_file_path (str) – file path to JSON file containing CSV template info

get_index(value: str) → int[source]¶

If value is a string, return its index of columns

Parameters: value (str, int) – any value
Returns: If value from analysis_columns is a string, return its index
Return type: int

set_values_to_index()[source]¶: If values are str, set to column index

class iqdma.importer.ReportImporter(report_file_path: str, parser: str, duplicate_detection: bool)[source]¶

Bases: object

Class to import IQDM-PDF CSV output

Initialize ReportImporter

Parameters

report_file_path (str) – File path to CSV output from IQDM-PDF
parser (str) – The parser used to generate the report. Either ‘SNCPatient2020’, ‘SNCPatientCustom’, ‘Delta4’, ‘Verisoft’, ‘VarianPortalDosimetry’
duplicate_detection (bool) – If true, apply a multi_value policy from options

property charting_options: list¶

Column names of y-axis options

Returns: Column names from analysis_columns['y']
Return type: list

property criteria_col: list¶

Column names of analysis criteria options

Returns: Column names from analysis_columns['criteria']
Return type: list

property lcl¶

Lower Control Limit minimums

Returns: keys are column names, values are minimum LCL values (or None)
Return type: dict

remove_non_numeric(val: str) → float[source]¶

Remove all non-numeric characters, convert to float, use to highjack dtype in widen_data

Parameters: val (str) – Any string
Returns: val converted into a float
Return type: float

property ucl: dict¶

Upper Control Limit caps

Returns: keys are column names, values are maximum UCL values (or None)
Return type: dict

property uid_col: list¶

Column names, when combined create a UID

Returns: Column names from analysis_columns['uid']
Return type: list

iqdma.importer.copy_default_csv_templates()[source]¶: Copy default JSON file form resources/csv_templates

iqdma.importer.create_csv_template(parser: IQDMPDF.parsers.generic.ParserBase)[source]¶

Write a CSV_TEMPLATE to JSON

Parameters: parser (ParserBase) – a parser from IQDMPDF

iqdma.importer.create_default_parsers()[source]¶: Generate CSV_TEMPLATE JSON files from IQDMPDF, if it doesn’t exist

iqdma.importer.import_csv_templates() → dict[source]¶

Import CSV Templates

Returns: keys are parser names and values are CSVParser objects. If a default parser is missing from CSV_TEMPLATES_DIR, load directly from IQDMPDF
Return type: dict

Stats¶

Modified DVHA-Stats for IQDM-PDF output

class iqdma.stats.ControlChart(y, std=3, ucl_limit=None, lcl_limit=None, x=None, range=None)[source]¶

Bases: object

Calculate control limits for a standard univariate Control Chart”

Parameters

y (list, np.ndarray) – Input data (1-D)
std (int, float, optional) – Number of standard deviations used to calculate if a y-value is out-of-control.
ucl_limit (float, optional) – Limit the upper control limit to this value
lcl_limit (float, optional) – Limit the lower control limit to this value
range (tuple, list, ndarray) – 2-item object containing start and end index of y

Initialization of a ControlChart

property avg_moving_range¶

Avg moving range based on 2 consecutive points

Returns: Average moving range. Returns NaN if arr is empty.
Return type: np.ndarray, np.nan

property center_line¶

Center line of charting data (i.e., mean value)

Returns: Mean value of y with np.mean() or np.nan if y is empty
Return type: np.ndarray, np.nan

property chart_data¶

JSON compatible dict for chart generation

Returns: Data used for Histogram visuals. Keys include ‘x’, ‘y’, ‘out_of_control’, ‘center_line’, ‘lcl’, ‘ucl’
Return type: dict

property control_limits¶

Calculate the lower and upper control limits

Returns

lcl (float) – Lower Control Limit (LCL)
ucl (float) – Upper Control Limit (UCL)

property out_of_control¶

Get the indices of out-of-control observations

Returns: An array of indices that are not between the lower and upper control limits
Return type: np.ndarray

property out_of_control_high¶

Get the indices of observations > ucl

Returns: An array of indices that are greater than the upper control limit
Return type: np.ndarray

property out_of_control_low¶

Get the indices of observations < lcl

Returns: An array of indices that are less than the lower control limit
Return type: np.ndarray

property sigma¶

UCL/LCL = center_line +/- sigma * std

Returns: sigma or np.nan if arr is empty
Return type: np.ndarray, np.nan

property x_ranged: list¶

Return x within range

Returns: x data from range[0] to range[1]
Return type: list

property y_ranged¶

Return y within range

Returns: y data from range[0] to range[1]
Return type: list

class iqdma.stats.IQDMStats(report_file_path: str, charting_column: str, multi_val_policy: str, duplicate_detection: bool, parser: str)[source]¶

Bases: object

Modified DVHAStats class for IQDM-PDF output

Initialize IQDMStats

Parameters

report_file_path (str) – File path to CSV output from IQDM-PDF
charting_column (str) – Column of y-axis data
multi_val_policy (str) – Duplicate value policy from options
duplicate_detection (bool) – If true, apply a multi_value policy from options
parser (str) – CSV format

get_index_by_var_name(var_name: str)[source]¶

Get the variable index by var_name

Parameters: var_name (int, str) – The name (str) or index (int) of the variable of interest
Returns: The column index for the given var_name
Return type: int

get_index_description() → tuple[source]¶

Get a dict of data and columns for DataTable

Returns

dict – Keys are column names with values being a list of values
list – Column names in order to be displayed

univariate_control_chart(var_name: str, std: float = 3, ucl_limit: Optional[float] = None, lcl_limit: Optional[float] = None, range: Optional[tuple] = None)[source]¶

Calculate control limits for a standard univariate Control Chart

Parameters

var_name (str, int) – The name (str) or index (int) of teh variable to plot
std (int, float, optional) – Number of standard deviations used to calculate if a y-value is out-of-control
ucl_limit (float, optional) – Limit the upper control limit to this value
lcl_limit (float, optional) – Limit the lower control limit to this value
range (tuple, list, ndarray) – 2-item object containing start and end index of data

Returns

stats.ControlChart class object

Return type

stats.ControlChart

univariate_control_charts(**kwargs)[source]¶

Calculate Control charts for all variables

Parameters: kwargs (any) – See univariate_control_chart for keyword parameters
Returns: ControlChart class objects stored in a dictionary with var_names and indices as keys (can use var_name or index)
Return type: dict

property variable_count¶

Number of variables in data

Returns: Number of columns in data
Return type: int

iqdma.stats.avg_moving_range(arr, nan_policy='omit')[source]¶

Calculate the average moving range (over 2-consecutive point1)

Parameters

arr (array-like (1-D)) – Input array. Must be positive 1-dimensional.
nan_policy (str, optional) – Value must be one of the following: {‘propagate’, ‘raise’, ‘omit’} Defines how to handle when input contains nan. The following options are available (default is ‘omit’): ‘propagate’: returns nan ‘raise’: throws an error ‘omit’: performs the calculations ignoring nan values

Returns

Average moving range. Returns NaN if arr is empty

Return type

np.ndarray, np.nan

iqdma.stats.process_nan_policy(arr, nan_policy)[source]¶

Calculate the average moving range (over 2-consecutive point1)

Parameters

arr (array-like (1-D)) – Input array. Must be positive 1-dimensional.
nan_policy (str) – Value must be one of the following: {‘propagate’, ‘raise’, ‘omit’} Defines how to handle when input contains nan. The following options are available (default is ‘omit’): ‘propagate’: returns nan ‘raise’: throws an error ‘omit’: performs the calculations ignoring nan values

Returns

Input array evaluated per nan_policy

Return type

np.ndarray, np.nan

iqdma.stats.remove_nan(arr)[source]¶

Remove indices from 1-D array with values of np.nan

Parameters: arr (np.ndarray (1-D)) – Input array. Must be positive 1-dimensional.
Returns: arr with NaN values deleted
Return type: np.ndarray

Utilities ported from DVHA-Stats¶

Common functions for DVHA-Stats. Copied to limit required libraries.

iqdma.utilities_dvha_stats.apply_dtype(value, dtype)[source]¶

Convert value with the provided data type

Parameters

value (any) – Value to be converted
dtype (function, None) – python reserved types, e.g., int, float, str, etc. However, dtype could be any callable that raises a ValueError on failure.

Returns

The return of dtype(value) or numpy.nan on ValueError

Return type

any

iqdma.utilities_dvha_stats.csv_to_dict(csv_file_path, delimiter=',', dtype=None, header_row=True)[source]¶

Read in a csv file, return data as a dictionary

Parameters

csv_file_path (str) – File path to the CSV file to be processed.
delimiter (str) – Specify the delimiter used in the csv file (default = ‘,’)
dtype (callable, type, optional) – Optionally force values to a type (e.g., float, int, str, etc.).
header_row (bool, optional) – If True, the first row is interpreted as column keys, otherwise row indices will be used

Returns

CSV data as a dict, using the first row values as keys

Return type

dict

iqdma.utilities_dvha_stats.dict_to_array(data, key_order=None)[source]¶

Convert a dict of data to a numpy array

Parameters

data (dict) – Dictionary of data to be converted to np.array.
key_order (None, list of str) – Optionally the order of columns

Returns

A dictionary with keys of ‘data’ and ‘columns’, pointing to a numpy array and list of str, respectively

Return type

dict

iqdma.utilities_dvha_stats.get_sorted_indices(list_data)[source]¶

Get original indices of a list after sorting

Parameters: list_data (list) – Any python sortable list
Returns: list_data indices of sorted(list_data)
Return type: list

iqdma.utilities_dvha_stats.import_data(data, var_names=None)[source]¶

Generalized data importer for np.ndarray, dict, and csv file

Parameters

data (numpy.array, dict, str) – Input data (2-D) with N rows of observations and p columns of variables. The CSV file must have a header row for column names.
var_names (list of str, optional) – If data is a numpy array, optionally provide the column names.

Returns

A tuple: data as an array and variable names as a list

Return type

np.ndarray, list

iqdma.utilities_dvha_stats.is_numeric(val)[source]¶

Check if value is numeric (float or int)

Parameters: val (any) – Any value
Returns: Returns true if float(val) doesn’t raise a ValueError
Return type: bool

iqdma.utilities_dvha_stats.sort_2d_array(arr, index, mode='col')[source]¶

Sort a 2-D numpy array

Parameters

arr (np.ndarray) – Input 2-D array to be sorted
index (int, list) – Index of column or row to sort arr. If list, will sort by each index in the order provided.
mode (str) – Either ‘col’ or ‘row’

Credits¶

Development Lead¶

Dan Cutright, University of Chicago Medicine

Contributors¶

Marc Chamberland, University of Vermont Health Network
Serpil Kucuker Dogan, Northwestern Medicine
Mahesh Gopalakrishnan, Northwestern Medicine
Aditya Panchal, AMITA Health
Michael Snyder, Beaumont Health

Change Log for IQDM-Analytics¶

v0.1.9 (2021.05.17)¶

Clean charting values of non-numerical characters on import
Prevent crash if only one UID columns is defined in CSV Template
Added CSV template for IBA MyQA

v0.1.8 (2021.03.28)¶

Implement CSV parsing with JSON templates, allowing for customization
Option to disable duplicate report detection

v0.1.7 (2021.03.14)¶

Added Control Chart using all data
MS Edge Support for Windows
IQDM-PDF bump to v0.3.0

v0.1.6 (2021.03.13)¶

Improved date parsing (IQDM-PDF bump to v0.2.9)

v0.1.5 (2021.03.10)¶

Last release before Change Log implemented

Welcome to the documentation for IQDM-Analytics!¶

IQDM-Analytics¶

What does it do?¶

Executables¶

Other information¶

Dependencies¶

Install and Run¶

TODO¶

Credits¶

Development Lead¶

Contributors¶

User Manual¶

Introduction¶

Usage¶

Supported Vendors¶

Methods¶

PDF Mining¶

Data Parsing¶

Control Charts¶

CSV Parsing¶

columns¶

analysis_columns: uid¶

analysis_columns: date¶

analysis_columns: criteria¶

analysis_columns: y¶

Settings¶

Windows Users¶

Local File Storage¶

PyInstaller¶

IQDM Analytics¶

Data Table¶

Importer¶

Stats¶

Utilities ported from DVHA-Stats¶

Credits¶

Development Lead¶

Contributors¶

Change Log for IQDM-Analytics¶

v0.1.9 (2021.05.17)¶

v0.1.8 (2021.03.28)¶

v0.1.7 (2021.03.14)¶

v0.1.6 (2021.03.13)¶

v0.1.5 (2021.03.10)¶

Indices and tables¶