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Provide functions to read, parse and convert MS Excel spreadsheets into various data structures.

Project description

Overview

Provide functions to read, parse and convert MS Excel spreadsheets into various data structures.

Usage

To read a MS Excel file into memory call xls_to_excelerator_dict(filename). This will return a dict in the excelerator_dict format. Functions are provided to convert between this format and the following formats.

excelerator_dict

A list of tuples (sheet_name, dict). dict keys are (row_num, col_num) pairs:

[
    (
        sheet_name,
        {
            (row_num, col_num): value,
        }
    ),
]

rows_and_columns

Nested dicts which keys sheet name, row number and column number:

{
    sheet_name: {
        row_num: {
            col_num: value,
        }
    },
}

matrix

A dict mapping from sheet names to matrices, i.e, a lists of lists:

{
    sheet_name: [
        [v01, v02, v03, ...],
        [v11, v12, v13, ...],
    ]
}

structure

Perhaps the more user-friendly format: A dict mapping from sheet names to lists. These lists contains the rows. Each row is represented by a dict, mapping from column names to values. Column names are the values in the first row of the sheet:

{
    sheet_name: [
        {
            col_name: value,
        },
    ]
}

This format is only useful if the first row of each sheet is actually a header row

Project details


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0.0.4

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Filename, size & hash SHA256 hash help File type Python version Upload date
rbco.msexcel-0.0.4.zip (6.9 kB) Copy SHA256 hash SHA256 Source None Feb 12, 2014

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