Start to use our multiplier to have time be x times what we give
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@ -18,6 +18,10 @@ timelog["day_of_week"] = pd.to_datetime(timelog["date"]).dt.day_name()
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timelog['project'] = (np.where(timelog['description'].str.contains(': '), timelog['description'].str.split(': ', 1).str[0], None))
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timelog['project'] = (np.where(timelog['description'].str.contains(': '), timelog['description'].str.split(': ', 1).str[0], None))
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timelog['description'] = (np.where(timelog['description'].str.contains(': '), timelog['description'].str.split(': ', 1).str[1], timelog['description']))
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timelog['description'] = (np.where(timelog['description'].str.contains(': '), timelog['description'].str.split(': ', 1).str[1], timelog['description']))
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# If a multiplier has been provided (an asterisk and an integer at the end of a
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# task), then multiply the time by it and remove it from the description.
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timelog['tmp_multiplier'] = (np.where(timelog['description'].str.contains(pat='*', regex=False), timelog['description'].str.split('*', 1).str[1], None))
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timelog['description'] = (np.where(timelog['description'].str.contains(pat='*', regex=False), timelog['description'].str.split('*', 1).str[0], timelog['description']))
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# Condense duplicate entries by date, summing the minutes spent, and listing
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# Condense duplicate entries by date, summing the minutes spent, and listing
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# the first started and last recorded times for each task.
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# the first started and last recorded times for each task.
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