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GregW04
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Feb 13, 2026
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| df_events = df_events.copy() | ||
| df_events["location_filtered"] = df_events["location"].str.contains( | ||
| location_regex, case=False, regex=True, na=False |
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Check if regex = False would work (it is faster). If not - stay with current approach
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But the location_regex is a regex not a normal string, so as far as I'm concerned regex=True is mandatory here
GregW04
reviewed
Feb 13, 2026
| """Creates a boolean column "location_filtered" in the input dataframe df_events, | ||
| indicating whether the "location" column matches any of the specified regex patterns.""" | ||
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| df_events = df_events.copy() |
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as making copy is costly for Memory let's make it optional throught the functions -> add parameter: copy: bool = False
GregW04
reviewed
Feb 13, 2026
| r"strefa kultury studenckiej", | ||
| r"geocentrum" | ||
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for reapeated use try to compile patterns once e.g. location_pattern = re.compile(location_combined_regex, re.IGNORECASE
GregW04
reviewed
Feb 13, 2026
| df_events = filter_event_locations(df_events, location_regex) | ||
| df_events = filter_event_summaries(df_events, summary_regex) | ||
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| df_events["filter_events"] = (df_events["location_filtered"] | df_events["summary_filtered"]) |
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please change the name for the new column to sth like: is_event_filtered
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@DominikaStefaniak PR review rdy |
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Creates three functions that add new columns to the events DataFrame indicating whether an event takes place on the PWr campus. The determination is based on the event's location, summary, and a combined check.