SpreadPandas is a Python package to get the projected dimensions of a pandas data frame if it were to be transposed to a spreadsheet.
By creating a SpreadsheetMap object, understand which cells of a spreadsheet the data frame would occupy, with detail for its header, index and body.
The goal is for this package to serve as a basis to perform more complex operations, like Excel customization or Google Sheet exporting, that require to establish a precise mapping between the data frame content and the target cells.
You can install EasyPred via pip
pip install spreadpandas
Alternatively, you can install EasyPred by cloning the project to your local directory
git clone https://github.com/FilippoPisello/SpreadPandas
And then run setup.py
python setup.py install
Take an example pandas data frame:
>>> import pandas as pd
>>> df = pd.DataFrame({"COL1" : [1, 2, 3], "COL2" : [4, 5, 6]})
>>> df
COL1 COL2
0 1 4
1 2 5
2 3 6Use SpreadMap to get its spreadsheet mapping. Suppose the index should not be brought over to the spreadsheet:
>>> from spreadpandas import SpreadMap
>>> spreadmap = SpreadMap(df, keep_index=False)
>>> spreadmap.header.cells
('A1', 'B1')
>>> spreadmap.body.cells
('A2', 'B2', 'A3', 'B3', 'A4', 'B4')
>>> spreadmap.index
NoneIf the index should be kept instead:
>>> spreadmap = SpreadMap(df, keep_index=True)
>>> spreadmap.header.cells
('B1', 'C1')
>>> spreadmap.body.cells
('B2', 'C2', 'B3', 'C3', 'B4', 'C4')
>>> spreadmap.index.cells
('A2', 'A3', 'A4')The content can also be moved by skipping rows and/or columns:
>>> spreadmap = SpreadMap(df, keep_index=True, skip_rows=2, skip_columns=1)
>>> spreadmap.header.cells
('C3', 'D3')
>>> spreadmap.body.cells
('C4', 'D4', 'C5', 'D5', 'C6', 'D6')
>>> spreadmap.index.cells
('B4', 'B5', 'B6')EasyPred depends only on pandas.
For the moment, this is the only documentation available.