53 lines
3 KiB
Python
53 lines
3 KiB
Python
import pandas as pd
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import numpy as np
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# import matplotlib.pyplot as plt
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timelog = pd.read_csv("timelog-titled.csv")
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# Dump bad data. The real solution here is to get rid of the damned 'Cancel'
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# button on the Pomodoro Prompt dialog, but i don't know how to do that, so we
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# need to drop the rows where the work task description is blank, which is
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# coming in as not a number for reasons i'm not entirely clear on. Maybe
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# because it's the last row of the spreadsheet? Anyway we cannot do anything
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# with no data in the description, so drop them at the outset.
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timelog = timelog.dropna()
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timelog = timelog.reset_index(drop=True)
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timelog["started"] = pd.to_datetime(timelog["started"]).dt.tz_convert("US/Eastern")
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timelog["recorded"] = pd.to_datetime(timelog["recorded"]).dt.tz_convert("US/Eastern")
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timelog["time"] = 30
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# A pomodoro started before 3am Eastern time is considered to be a continuation
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# of the day before, so we are, effectively, on West Coast time for determining
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# the day we want to associate a time entry with. PomodoroPrompt saves as UTC.
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timelog["date"] = timelog["started"].dt.tz_convert("US/Pacific").dt.date
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timelog["day_of_week"] = pd.to_datetime(timelog["date"]).dt.day_name()
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# For debugging, keep original description around.
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timelog["orig_desc"] = timelog["description"]
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# Clean up description before we go to work on it.
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timelog['description'] = timelog['description'].str.strip()
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# If a project has been specified (task prefixed with a colon), then put the
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# project in its own column.
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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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# Mid-work clean up of description.
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timelog['description'] = timelog['description'].str.strip()
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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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# Ensure we're splitting on the same asterisk we found: Use the end of string
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# signifier in the regular expression ($), and split from the right.
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timelog['tmp_multiplier'] = (np.where(timelog['description'].str.contains('\*\s*\d$'), timelog['description'].str.rsplit('*', 1).str[1].str.strip(), 1))
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timelog['description'] = (np.where(timelog['description'].str.contains('\*\s*\d$'), timelog['description'].str.rsplit('*', 1).str[0], timelog['description']))
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timelog["time"] = timelog["time"] * timelog['tmp_multiplier'].astype(int)
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timelog.drop(columns=['tmp_multiplier'], inplace=True)
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# Clean up description again, after it has been sliced and diced.
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timelog['description'] = timelog['description'].str.strip()
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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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tl = timelog.groupby(["date", "project", "description"]).agg({"time": 'sum', "started": 'min', "recorded": 'max'}).reset_index()
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