Read and write tfs files.
Project description
TFS-Pandas
This package provides reading and writing functionality for Table Format System (TFS) files.
Files are read into a TfsDataFrame, a class built on top of the famous pandas.DataFrame, which in addition to the normal behavior attaches an OrderedDict of headers to the DataFrame.
See the API documentation for details.
Installing
Installation is easily done via pip:
python -m pip install tfs-pandas
One can also install in a conda/mamba environment via the conda-forge channel with:
conda install -c conda-forge tfs-pandas
Example Usage
The package is imported as tfs, and exports top-level functions for reading and writing:
import tfs
# Loading a TFS file is simple
data_frame = tfs.read("path_to_input.tfs", index="index_column")
# You can access and modify the headers with the .headers attribute
useful_variable = data_frame.headers["SOME_KEY"]
data_frame.headers["NEW_KEY"] = some_variable
# Manipulate data as you do with pandas DataFrames
data_frame["NEWCOL"] = data_frame.COL_A * data_frame.COL_B
# You can check the validity of a TfsDataFrame, and choose the behavior in case of errors
tfs.frame.validate(data_frame, non_unique_behavior="raise") # or choose "warn"
# Writing out to disk is simple too
tfs.write("path_to_output.tfs", data_frame, save_index="index_column")
Reading and writing compressed files is also supported, and done automatically based on the provided file extension:
import tfs
# Reading a compressed file is simple, compression format is inferred
df = tfs.read("path_to_input.tfs.gz")
# When writing choose the compression format by providing the appropriate file extension
tfs.write("path_to_output.tfs.bz2", df)
tfs.write("path_to_output.tfs.zip", df)
License
This project is licensed under the MIT License - see the LICENSE file for details.
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