Release v0.12.1

• Added: audformat.utils.hash()
• Added: audformat.utils.expand_file_path()
• Added: audformat.utils.replace_file_extension()
• Changed: use yaml.CLoader for faster header reading

Release v0.12.0

• Added: as_segmented, allow_nat, root, num_workers
  arguments to audformat.Table.get()
• Added: as_segmented, allow_nat, root, num_workers
  arguments to audformat.Column.get()
• Added: files_duration argument
  to audformat.utils.to_segmented_index()
• Added: audformat.Database.files_duration()
• Changed: changed default value of load_data argument
  in audformat.Database.load() to False
• Changed: speed up audformat.Database.files
  and audformat.Database.segments
• Fixed: re-add support for pandas>=1.3

Release v0.11.6

• Added: support for Python 3.9
• Fixed: speed up audformat.utils.union()
• Fixed: audformat.Column.set() with pd.Series
  and np.array for a scheme with fixed labels
  and containing NaN values

Release v0.11.5

• Removed: duration scheme and table
  from conventions
  and emodb example

Release v0.11.4

• Added: custom BadKeyError when key is not found
• Changed: limit to pandas <1.3
  until it works again for newer pandas versions
• Changed: remove the <1.0.0 limit for audiofile
  as a stable release is available and the API has not changed

Release v0.11.3

• Added: audformat.utils.duration
• Fixed: description of audformat.Database.is_portable
  in documentation

Release v0.11.2

• Added: audformat.utils.join_schemes

Release v0.11.1

• Added: Database.is_portable
• Added: copy_media argument to Database.update()
• Changed: remove root argument from testing.create_audio_files() and instead use Database.root
• Fixed: utils.concat() converts to nullable dtype
• Fixed: utils.concat() returns DataFrame if input contains at least one DataFrame

Release v0.11.0

• Added: Database.root
• Added: utils.join_labels()
• Added: Scheme.replace_labels()
• Changed: set dependency to pandas>=1.1.5
• Changed: do not compress pickled table files

Release v0.10.2

• Changed: allow_nat argument to utils.to_segmented_index()