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Import/Export

Exporting SpectraFrame objects works via convering them to pandas DataFrames from where you can export to any format available in pandas, such as CSV, pickle, feather, parquet, etc.

When converting to pandas DataFrame, various options are available to help with following exports/imports:

  • multiindex: If True, the DataFrame will have a MultiIndex with the metadata columns as levels. This is useful for quickly split spectra data and metadata.
  • string_names: If True, the metadata column names will be converted to strings. This is useful for some export formats that do not support non-string column names.
import pyspc

# Create sample data
wl = np.linspace(400, 800, 100)
spectra = np.random.randn(10, 100)
sf = pyspc.SpectraFrame(spectra, wl=wl)

# Some export examples
sf.to_pandas().to_csv('spectra.csv', index=False)  # Export to CSV
sf.to_pandas(multiindex=True).to_pickle('spectra.pkl')  # Export to pickle
sf.to_pandas(string_names=True).to_feather('spectra.feather')  # Export to Feather
sf.to_pandas(string_names=True).to_parquet('spectra.parquet')  # Export to Parquet

When exported directly from SpectraFrame, it is possible to import the data directly from that file:

sf = pyspc.SpectraFrame.fromfile('spectra.csv')
sf = pyspc.SpectraFrame.fromfile('spectra.pkl')
sf = pyspc.SpectraFrame.fromfile('spectra.feather')
sf = pyspc.SpectraFrame.fromfile('spectra.parquet')

Note

When taken from external sources, the data can be has to be converted to SpectraFrame explicitly.