mdvtools.csv_to_static
======================

.. py:module:: mdvtools.csv_to_static


Attributes
----------

.. autoapisummary::

   mdvtools.csv_to_static.parser
   mdvtools.csv_to_static.parse_multitext
   mdvtools.csv_to_static.args
   mdvtools.csv_to_static.separator
   mdvtools.csv_to_static.filename
   mdvtools.csv_to_static.filename
   mdvtools.csv_to_static.basename
   mdvtools.csv_to_static.outdir
   mdvtools.csv_to_static.outdir
   mdvtools.csv_to_static.indir
   mdvtools.csv_to_static.has_images
   mdvtools.csv_to_static.df
   mdvtools.csv_to_static.types
   mdvtools.csv_to_static.col_types


Functions
---------

.. autoapisummary::

   mdvtools.csv_to_static.rename_columns
   mdvtools.csv_to_static.get_column_type
   mdvtools.csv_to_static.get_quantiles
   mdvtools.csv_to_static.get_text_indices
   mdvtools.csv_to_static.get_column_groups
   mdvtools.csv_to_static.get_datasource
   mdvtools.csv_to_static.replace_text_values
   mdvtools.csv_to_static.get_views
   mdvtools.csv_to_static.get_state
   mdvtools.csv_to_static.convert_data_to_binary
   mdvtools.csv_to_static.main


Module Contents
---------------

.. py:data:: parser

.. py:data:: parse_multitext
   :value: True


.. py:data:: args

.. py:data:: separator

.. py:data:: filename

.. py:data:: filename

.. py:data:: basename

.. py:data:: outdir

.. py:data:: outdir

.. py:data:: indir

.. py:data:: has_images
   :value: False


.. py:data:: df

.. py:data:: types

.. py:data:: col_types

.. py:function:: rename_columns()

.. py:function:: get_column_type(name)

.. py:function:: get_quantiles(col)

.. py:function:: get_text_indices(col)

.. py:function:: get_column_groups()

.. py:function:: get_datasource()

   Has some side effects on the dataframe:
   if args.discard_redundant:
       - removes columns that are redundant (all the same value)
   text columns are converted to indices.

   Outputs a descriptor like this:
   {
       "name": "metric_table",
       "size": number of rows,
       "images": {
           "images": {
               "base_url": "./images/",
               "type": "png",
               "key_column": "image_id"
           }
       }
       "columns": [
           {
               "datatype": "float" | "integer" | "text" | "unique",
               "name": "column_name",
               "field": "column_name",
               "minMax"?: [min, max],
               "quantiles"?: ...,
               "values"?: ['a', 'b', 'c'],
           }
       ]
   }


.. py:function:: replace_text_values(col, values)

.. py:function:: get_views()

.. py:function:: get_state()

.. py:function:: convert_data_to_binary(df)

   Converts the dataframe to binary format.


.. py:function:: main()