Search Tools

Search for cumulative changes in data.

canomaly.searchtools.cumrexpy(df: DataFrame, target: str, group: str) → Series

Apply a cumulative extraction of regular expressions to the grouped values of the target column in a pandas dataframe.

Parameters:

dfpandas.DataFrame

A pandas DataFrame with columns target and group.

targetstr

The name of the column to group the values of.

groupstr

The name of the column to group the values by.

Returns:

pandas.Series

A new series containing the cumulative extraction of regular expressions applied to the values of the target column grouped by the corresponding values of the group column.

References

Examples

>>> import pandas as pd
>>> from canomaly.searchtools import cumrexpy
>>> data = {'target': ['apple', 'apple', 'banana', 'banana', 'orange'],
            'group': ['a', 'a', 'b', 'b', 'b']}
>>> df = pd.DataFrame(data)
>>> cumrexpy(df, 'target', 'group')
group
a         [^apple$]
b    [^[a-z]{5,6}$]
Name: target_grouped, dtype: object

canomaly.searchtools.df_seq_diff(df: DataFrame) → DataFrame

Return a dataframe with rows that have at least one changed value compared to the previous row.

Parameters:

dfpandas.DataFrame

A pandas DataFrame with columns to compare for changes.

Returns:

pandas.DataFrame

A new dataframe containing the rows of the original dataframe that have at least one changed value compared to the previous row.