tslumen.profile.summary module¶

Summary indicators, both at frame and series levels.

tslumen.profile.summary.df_scaled(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame]) → Union[pandas.core.series.Series, pandas.core.frame.DataFrame][source]¶

Data scaled to be between 0 and 1.

Parameters: data (Union[pd.Series, pd.DataFrame]) – Time series.
Returns: Scaled data.
Return type: Union[pd.Series, pd.DataFrame]

tslumen.profile.summary.dt_end(data: pandas.core.frame.DataFrame) → Any[source]¶

Parameters: data (pd.DataFrame) – Time series.
Returns: End datetime.
Return type: datetime

tslumen.profile.summary.dt_start(data: pandas.core.frame.DataFrame) → Any[source]¶

Parameters: data (pd.DataFrame) – Time series.
Returns: Start datetime.
Return type: datetime

tslumen.profile.summary.freq(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame]) → Optional[str][source]¶

Parameters: data (Union[pd.Series, pd.DataFrame]) – Time series.
Returns: Data’s inferred frequency.
Return type: int

tslumen.profile.summary.infinite(data: pandas.core.series.Series) → int[source]¶

Count number of infinite values.

Parameters: data (pd.Series) – Time series.
Returns: Number of np.inf in data.
Return type: int

tslumen.profile.summary.length(data: pandas.core.frame.DataFrame) → int[source]¶

Parameters: data (pd.DataFrame) – Time series.
Returns: Length of the time series.
Return type: int

tslumen.profile.summary.missing(data: pandas.core.series.Series) → Any[source]¶

Count number of missing values.

Parameters: data (pd.Series) – Time series.
Returns: Number of np.nan in data.
Return type: int

tslumen.profile.summary.n_series(data: pandas.core.frame.DataFrame) → int[source]¶

Parameters: data (pd.DataFrame) – Time series.
Returns: Number of series in the DataFrame.
Return type: int

tslumen.profile.summary.period(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame]) → Optional[int][source]¶

Parameters: data (Union[pd.Series, pd.DataFrame]) – Time series.
Returns: Data’s periodicity.
Return type: int

tslumen.profile.summary.sample(data: pandas.core.series.Series, sample_size: int = 10) → pandas.core.series.Series[source]¶

Sample N records from the data.

Parameters

data (pd.Series) – Time series.
sample_size (int) – Size of the sample.

Returns

First and last sample_size/2 records in data.

Return type

pd.Series

tslumen.profile.summary.sz_total(data: pandas.core.frame.DataFrame, memory_deep: bool = True) → int[source]¶

Parameters

data (pd.DataFrame) – TimeSeries data.
memory_deep (bool) – deeper interrogation to obtain system-level memory consumption.

Returns

Memory usage in bytes.

Return type

int

tslumen.profile.summary.zeros(data: pandas.core.series.Series) → int[source]¶

Count number of zeros.

Parameters: data (pd.Series) – Time series.
Returns: Number of 0 in data.
Return type: int