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 behaviour 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 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")
It also provides some tools to validate and manipulate TfsDataFrames and their headers; or lazily manage a collection of TFS files.
With tfs.read_hdf() and tfs.write_hdf() the TfsDataFames can also be saved as hdf5 files, if the hdf5 extra-requirements are fullfilled.
License
This project is licensed under the MIT License - see the LICENSE file for details.
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