Metadata-Version: 2.1
Name: pycatcher
Version: 0.0.20
Summary: This package identifies outlier(s) for a given time-series dataset in simple steps. It supports day, week, month and quarter level time-series data.
Home-page: https://github.com/aseemanand/pycatcher/
License: MIT
Keywords: outlier-detection,python,timeseries
Author: Aseem Anand
Author-email: aseemanand@gmail.com
Maintainer: Jagadish Pamarthi
Maintainer-email: jagadish.vrsec@gmail.com
Requires-Python: >=3.9
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: pandas (==2.2.3)
Requires-Dist: pyod (==2.0.2)
Requires-Dist: pyspark (>=3.0.0,<4.0.0)
Requires-Dist: seaborn (==0.13.2)
Requires-Dist: statsmodels (==0.14.4)
Project-URL: Repository, https://github.com/aseemanand/pycatcher/
Description-Content-Type: text/markdown

## Outlier Detection for Time-series Data
This package identifies outlier(s) for a given time-series dataset in simple steps. It supports day, week, month and quarter level time-series data.

#### DataFrame Arguments:
First column in the dataframe must be a date column ('YYYY-MM-DD') and the last column a count column.
#### Package Functions:
* detect_outliers(df): Detect outliers in a time-series dataframe using seasonal trend decomposition when there is at least 2 years of data, otherwise we can use Interquartile Range (IQR) for smaller timeframe.
* detect_outliers_today(df) Detect outliers for the current date in a time-series dataframe.
* detect_outliers_latest(df): Detect latest outliers in a time-series dataframe.
* find_outliers_iqr(df): Detect outliers in a time-series dataframe when there's less than 2 years of data.

#### Diagnostic Plots:
* build_seasonal_plot(df): Build seasonal plot (additive or multiplicative) for a given dataframe.
* build_iqr_plot(df): Build IQR plot for a given dataframe (for less than 2 years of data).
* build_monthwise_plot(df): Build month-wise plot for a given dataframe.
* build_decomposition_results(df): Get seasonal decomposition results for a given dataframe.
* conduct_stationarity_check(df): Conduct stationarity check (trend only) for a feature (dataframe's count column).








