Read and write list of `pandas.DataFrame`s of tabular data from/to excel file.
Project description
xlsx2dfs
Easy loading from and writing to excel sheets to/from pandas DataFrames (and list of sheet_names).
Installation
pip install xlsx2dfs
Usage
from xlsx2dfs import xlsx2dfs, withNames, dfs2xlsx
# xlsx file path
fpath = "test.xlsx"
# read from it:
dfs, sheet_names = xlsx2dfs(fpath)
# write to it
out_fpath = "out_test.xlsx"
dfs2xlsx(dfs, sheet_names=["sheet1", "sheet2", "sheet3"], out_fpath=out_fpath)
# or using `withNames` which allows alternate input of sheet_name and corresponding df
# `withNames("sheet1", dfs[0], "sheet2" dfs[1], "sheet3", dfs[2])` returns
# ([dfs[0], dfs[1], dfs[2]], ["sheet1", "sheet2", "sheet3"])
# thus (dfs, sheet_names). Using asterisk we can integrate them into the argument list
# of `dfs2xlsx`.
dfs2xlsx(*withNames("sheet1", dfs[0], "sheet2" dfs[1], "sheet3", dfs[2]), out_fpath)
# This makes especially sense when you have different data frames as results in your script
# and you want to save few lines of code which would be needed to bind them
# together into a list and name them.
# Instead, you can do the naming and binding to a list using `*withNames().
# This also enhances readability and is intuitive.
# e.g.
dfs2xlsx(*withNames("Temperatures", temperatures_df,
"Prediction", prediction_df,
"Original Data", orig_df),
"/path/to/output/file.xlsx")
document the version:
- Linux:
$ pip freeze | grep xlsx2dfs
- Windows:
c:\> pip freeze | findstr xlsx2dfs
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