backend.pql_queries.log_skeleton_queries

Queries that can be used to get log-skeleton related data from celonis.

Functions

get_always_before_relation(→ pandas.DataFrame)	Caculates which pairs of Activity always occurr before each other.
get_always_after_relation(→ pandas.DataFrame)	Caculates which pairs of Activity always occurr after each other.
get_equivalance_relation(→ pandas.DataFrame)	Caculates which pairs of Activity are equivalent.
get_exclusive_choice_relaion(→ pandas.DataFrame)	Caculates which pairs of Activity are exclusive choice.
get_never_together_relation(→ pandas.DataFrame)	Caculates which pairs of Activity never occurr together.
get_directly_follows_relation_and_count(→ pandas.DataFrame)	Gets the directly follows relation and count.
get_act_freq(→ pandas.DataFrame)	Gets the activity frequencies.

Module Contents

backend.pql_queries.log_skeleton_queries.get_always_before_relation(celonis: backend.celonis_connection.celonis_connection_manager.CelonisConnectionManager) → pandas.DataFrame

Caculates which pairs of Activity always occurr before each other.

Parameters:

celonis (CelonisConnectionManager) – the celonis connection

Returns:

A dataframe that contains for pairs of Activities whether they always occurr before each other.

backend.pql_queries.log_skeleton_queries.get_always_after_relation(celonis: backend.celonis_connection.celonis_connection_manager.CelonisConnectionManager) → pandas.DataFrame

Caculates which pairs of Activity always occurr after each other.

Parameters:

celonis (CelonisConnectionManager) – the celonis connection

Returns:

A dataframe that contains for pairs of Activities whether they always occurr after each other.

backend.pql_queries.log_skeleton_queries.get_equivalance_relation(celonis: backend.celonis_connection.celonis_connection_manager.CelonisConnectionManager) → pandas.DataFrame

Caculates which pairs of Activity are equivalent.

Parameters:

celonis (CelonisConnectionManager) – the celonis connection

Returns:

A dataframe that contains for pairs of Activities whether they are equivalent.

backend.pql_queries.log_skeleton_queries.get_exclusive_choice_relaion(celonis: backend.celonis_connection.celonis_connection_manager.CelonisConnectionManager) → pandas.DataFrame

Caculates which pairs of Activity are exclusive choice.

Parameters:

celonis (CelonisConnectionManager) – the celonis connection

Returns:

A dataframe that contains for pairs of Activities whether they are exclusive choice.

backend.pql_queries.log_skeleton_queries.get_never_together_relation(celonis: backend.celonis_connection.celonis_connection_manager.CelonisConnectionManager) → pandas.DataFrame

Caculates which pairs of Activity never occurr together.

Parameters:

celonis (CelonisConnectionManager) – the celonis connection

Returns:

A dataframe that contains for pairs of Activities whether they are never together in a trace

backend.pql_queries.log_skeleton_queries.get_directly_follows_relation_and_count(celonis: backend.celonis_connection.celonis_connection_manager.CelonisConnectionManager) → pandas.DataFrame

Gets the directly follows relation and count.

Parameters:

celonis (CelonisConnectionManager) – the celonis connection

Returns:

A pandas dataframe that contains a statement whether the dirctly follows relation is true and the count for each

backend.pql_queries.log_skeleton_queries.get_act_freq(celonis: backend.celonis_connection.celonis_connection_manager.CelonisConnectionManager) → pandas.DataFrame

Gets the activity frequencies.

Parameters:

celonis (CelonisConnectionManager) – the celonis connection

Returns:

A pandas dataframe that contains the activity frequencies