Skip to main content

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

Project description

Author:

Rafael Oliveira <rafaelbco@gmail.com>

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


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rbco.msexcel-0.0.3.zip (6.9 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page