timeatlas.time_series_dataset.TimeSeriesDataset

class timeatlas.time_series_dataset.TimeSeriesDataset(data: List[timeatlas.time_series.time_series.TimeSeries] = None)

Defines a set of time series

A TimeSeriesDataset represent a set of TimeSeries objects.

__init__(data: List[timeatlas.time_series.time_series.TimeSeries] = None)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([data])	Initialize self.
append(item)	Append a TimeSeries to TimeSeriesDataset
apply(func[, tsd])	Apply function specialized for TimeSeriesDataset
boundaries()	Get the tuple with the TimeSeries first and last index for all components in the TimeSeriesDataset
clear()	Remove all items from list.
copy([deep])	Copy a TimeSeriesDataset
count(value, /)	Return number of occurrences of value.
create(length, start, end[, freq])	Create an empty TimeSeriesDataset object with a defined index and period
describe()	Describe a TimeSeriesDataset with the describe function from Pandas
duration()	Get the duration for all TimeSeries in a TimeSeriesDataset
empty()	Empty the values in each TimeSeries from a TimeSeriesDataset.
end()	Get the last Timestamp of a all components of a TimeSeriesDataset
extend(iterable, /)	Extend list by appending elements from the iterable.
fill(value)	Fill all values in each TimeSeries from a TimeSeriesDataset.
frequency()	Get the frequency of a each TimeSeries in a TimeSeriesDataset
group_by(freq[, method])	Groups values by a frequency for each TimeSeries in a TimeSeriesDataset.
index(value[, start, stop])	Return first index of value.
insert(index, object, /)	Insert object before index.
interpolate(*args, **kwargs)	Wrapper around the Pandas interpolate() method.
kurtosis()	Kurtosis of all TimeSeries in TimeSeriesDataset
max()	Maximum of all TimeSeries in TimeSeriesDataset
mean()	Means of all TimeSeries in TimeSeriesDataset
median()	Median of all TimeSeries in TimeSeriesDataset
merge(tsd)	Merge two TimeSeriesDataset by the index of the TimeSeries
merge_by_label(tsd)	Merge two TimeSeriesDatasets by the label of the TimeSeries in the TimeSeriesDatasets
min()	Minimum of all TimeSeries in TimeSeriesDataset
normalize(method)	Normalize the TimeSeries in a TimeSeriesDataset with a given method
pad(limit[, side, value])	Pad a TimeSeriesDataset until a given limit
plot(*args, **kwargs)	Plot a TimeSeriesDataset
pop([index])	Remove and return item at index (default last).
regularize([side, fill])	Regularize a TimeSeriesDataset so that all starting and ending timestamps are similar.
remove(value, /)	Remove first occurrence of value.
resample(freq[, method])	Convert the TimeSeries in a TimeSeriesDataset to a specified frequency.
reverse()	Reverse IN PLACE.
round(decimals)	Round the values of every TimeSeries in the TimeSeriesDataset with a defined number of digits
select_components_by_percentage(percent[, …])	Returns a subset of the TimeSeriesDataset with randomly chosen percentage elements without replacement.
select_components_randomly(n[, seed, indices])	Returns a subset of the TimeSeriesDataset with randomly chosen n elements without replacement.
shuffle([inplace])	Randomizing the order of the TS in the TSD
skewness()	Skewness of all TimeSeries in TimeSeriesDataset
sort(*args, **kwargs)	Sort the TimeSeries of a TimeSeriesDataset by time stamps
split_at(timestamp)	Split a TimeSeriesDataset at a defined point and include the splitting point in both as in [start,…,at] and [at,…,end].
split_in_chunks(n)	The TimeSeries in the TimeSeriesDataset are cut into chunks of length n
start()	Get the first Timestamp of a all components of a TimeSeriesDataset
time_detlas()	Compute the time difference between each timestamp for all TimeSeries
to_array()	TimeSeriesData to NumpyArray [n x len(tsd)], where n is number of
to_df()	Converts a TimeSeriesDataset to a Pandas DataFrame
to_pickle(path)	Creating a pickle out of the TimeSeriesDataset
to_text(path)	Export a TimeSeriesDataset to text format
trim([side])	Remove NaNs from a TimeSeries start, end or both

TimeSeriesDataset timeatlas.time_series_dataset.TimeSeriesDataset.create