README.md

Pandas2TensorBoard

Pandas2TensorBoard is a library for transforming the pandas DataFrame into the data fomrat of TensorBoard. Pandas2TensorBoard relies on torch utilities for the data transformation.

Installation

• Regular installation via pip:

  pip install pandas2tensorboard

• With modin backend for pandas

  pip install pandas2tensorboard[modin]

• With Dask and omnisci support for pandas

  pip install pandas2tensorboard[backend]

• With Dask and omnisci support for pandas and modin backend for pandas

  pip install pandas2tensorboard[all]

Usage

Currently the following types of export from pandas to tensorboard are supported:

• pd.DataFrame → scalars
• pd.DataFrame → scalars with timestamp
• pd.DataFrame → scatter via hyperparameters

For initializing the pandas2tensorboard library, the current syntax of Torch's tensorboard.SummaryWriter is used.

Examples

1. Exporting a regular pd.DataFrame to tensorboard by removing columns with str:

   import seaborn as sns
   
   from pandas2tensorboard import pandas2tensorboard as p2t
   
   pt = p2t.Pandas2TensorBoard()
   pt.regular_df(
       sns.load_dataset("planets"),
       label="planets",
       remove_nan=True,
       remove_str=True,
   )
   pt.close()

2. Exporting a pd.DataFrame with time column to tensorboard:

   import seaborn as sns
   
   from pandas2tensorboard import pandas2tensorboard as p2t
   
   pt = p2t.Pandas2TensorBoard()
   pt.timeseries_df(
       sns.load_dataset("attention"),
       time="score",
       label="attention",
       remove_nan=True,
       remove_str=True,
       time_convert=True,
   )
   pt.close()

   The time column with name score is transformed into float with timestamp.

3. Exporting a pd.DataFrame with hyperparameters to tensorboard:

   import seaborn as sns
   
   from pandas2tensorboard import pandas2tensorboard as p2t
   
   pt = p2t.Pandas2TensorBoard()
   pt.scatter_df(
       sns.load_dataset("anagrams"),
       x_axis="subidr",
       group="anagrams",
       remove_nan=True,
       remove_str=True,
   )
   pt.close()

   The x-axis corresponds to hparam_dict; the dataframe without column x_axis="subidr" corresponds to metric_dict.

Contributing

Please feel free to open an issue or create a pull request; see also contributing.

License

Check MIT