Input/Output data

Shapelets supports a variety of data sources to create Dataframe-like structures to process data.

To load or save data, you need to create a sandbox on Shapelets first, you can do like:

>>> import shapelets as sh
>>> session = sh.sandbox()

Read Data

Read from csv files

You can read csv files using the from_csv() function. A basic example is:

>>> df = session.from_csv(path)

This reader function has automatic delimiter/separator detection, so you do not need to specify the delimiter!

This function has more params, like date_format to specify the date format on date columns, and even more. You can check it out on the API Reference in from_csv()

Read from parquet files

You can use the from_parquet() function to load parquet files. A basic example here:

>>> df = session.from_parquet(path)

This function has more params, which you can find in the API Reference in from_parquet().

Read from Pandas DataFrame

In the case that you have a Pandas DataFrame which you woud like to quickly load in Shapelets, you can do it so using from_pandas() function:

>>> pandas_df = pd.DataFrame(data)

>>> df = session.from_pandas(pandas_df)

Export/Save Data

Save to a csv file

To save the content of a Shapelets Dataframe into a csv file, you can use the to_csv() function.

>>> df.to_csv(filename, delimiter=",")

This function has more params, which you can find in the API Reference in to_csv().

Save to a parquet file

If you want save the contents of a Shapelets Dataframe into a parquet file, you can use the to_parquet() function.

>>> df.to_parquet(filename, delimiter=",")

This function has more params, which you can find in the API Reference in to_parquet().

Convert into Pandas DataFrame

You can load data into Shapelets, process it and convert the results directly to a Pandas Dataframe object to use it with Pandas functions or any other Python library. Here is an example:

>>> df.to_pandas()