timeatlas.time_series.TimeSeries

class timeatlas.time_series.TimeSeries(series: Union[pandas.core.series.Series, pandas.core.frame.DataFrame] = None, metadata: timeatlas.metadata.metadata.Metadata = None, class_label: str = None)

A TimeSeries object is a series of time indexed values.

__init__(series: Union[pandas.core.series.Series, pandas.core.frame.DataFrame] = None, metadata: timeatlas.metadata.metadata.Metadata = None, class_label: str = None)

Defines a time series

A TimeSeries object is a series of time indexed values.

Parameters

• series – Series or DataFrame containing the values and labels

• metadata – Metadata-object

• class_label – class label

Methods

__init__([series, metadata, class_label])	Defines a time series
apply(func[, ts])	Wrapper around the Pandas apply function
boundaries()	Get a tuple with the TimeSeries first and last index
copy([deep])	Copy a TimeSeries
create(start, end[, freq, metadata])	Creates an empty TimeSeries object with the period as index
describe([percentiles, include, exclude])	Describe a TimeSeries with the describe function from Pandas
duration()	Get the duration of the TimeSeries
empty()	Empty the TimeSeries (fill all values with NaNs)
end()	Get the last Timestamp of a TimeSeries
fill(value)	Fill a TimeSeries with values
frequency()	Get the frequency of a TimeSeries
group_by(freq[, method])	Groups values by a frequency.
interpolate(*args, **kwargs)	Wrapper around the Pandas interpolate() method.
kurtosis()	Get the kurtosis of a TimeSeries
max()	Get the maximum value of a TimeSeries
mean()	Get the mean value of a TimeSeries
median()	Get the median value of a TimeSeries
merge(ts)	Merge two time series and make sure all the given indexes are sorted.
min()	Get the minimum value of a TimeSeries
normalize(method)	Normalize a TimeSeries with a given method
pad(limit[, side, value])	Pad a TimeSeries until a given limit
plot(*args, **kwargs)	Plot a TimeSeries
resample(freq[, method])	Convert TimeSeries to specified frequency.
round(decimals)	Round the values in the series.values
skewness()	Get the skewness of a TimeSeries
sort(*args, **kwargs)	Sort a TimeSeries by time stamps
split_at(timestamp)	Split a TimeSeries at a defined point and include the splitting point in both as in [start,…,at] and [at,…,end].
split_in_chunks(n)	Split a TimeSeries into chunks of length n
start()	Get the first Timestamp of a TimeSeries
time_detlas()	Compute the time difference in seconds between each timestamp of a TimeSeries
to_array()	Convert a TimeSeries to Numpy Array
to_darts()	Convert a TimeSeries to Darts TimeSeries
to_df()	Converts a TimeSeries to a Pandas DataFrame
to_pickle(path)	Export a TimeSeries to Pickle
to_text(path)	Export a TimeSeries to text format
trim([side])	Remove NaNs from a TimeSeries start, end or both

Time Series timeatlas.time_series.TimeSeries.create