2017-08-25 16:19:06 +00:00
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# -*- coding: utf-8 -*-
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from __future__ import unicode_literals
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2017-08-25 18:17:15 +00:00
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from collections import OrderedDict
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2017-08-25 16:19:06 +00:00
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from django.db.models import Count, Case, When
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from django.db.models.functions import TruncDate
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2017-08-25 21:32:46 +00:00
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from django.utils import timezone
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2017-08-25 16:19:06 +00:00
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import pandas as pd
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import plotly.offline as plotly
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import plotly.graph_objs as go
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from core.models import DiaperChange, Sleep
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2017-08-25 21:32:46 +00:00
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from core.utils import duration_string
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2017-08-25 16:19:06 +00:00
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from .utils import default_graph_layout_options, split_graph_output
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def diaperchange_types(child):
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changes = DiaperChange.objects.filter(child=child) \
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.annotate(date=TruncDate('time')) \
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.values('date') \
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.annotate(wet_count=Count(Case(When(wet=True, then=1)))) \
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.annotate(solid_count=Count(Case(When(solid=True, then=1)))) \
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.annotate(total=Count('id')) \
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.order_by('-date')
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solid_trace = go.Scatter(
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mode='markers',
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name='Solid changes',
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x=list(changes.values_list('date', flat=True)),
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y=list(changes.values_list('solid_count', flat=True)),
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)
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wet_trace = go.Scatter(
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mode='markers',
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name='Wet changes',
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x=list(changes.values_list('date', flat=True)),
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y=list(changes.values_list('wet_count', flat=True))
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)
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total_trace = go.Scatter(
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name='Total changes',
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x=list(changes.values_list('date', flat=True)),
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y=list(changes.values_list('total', flat=True))
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)
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layout_args = default_graph_layout_options()
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layout_args['barmode'] = 'stack'
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2017-09-13 15:20:28 +00:00
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layout_args['title'] = '<b>Diaper Change Types</b><br>{}'.format(child)
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2017-08-25 16:19:06 +00:00
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layout_args['xaxis']['title'] = 'Date'
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layout_args['yaxis']['title'] = 'Number of changes'
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fig = go.Figure({
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'data': [solid_trace, wet_trace, total_trace],
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'layout': go.Layout(**layout_args)
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})
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output = plotly.plot(fig, output_type='div', include_plotlyjs=False)
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return split_graph_output(output)
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2017-09-10 21:26:18 +00:00
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def sleep_amount(child):
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"""Create a graph showing total time sleeping for each day."""
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instances = Sleep.objects.filter(child=child).order_by('start')
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totals = {}
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for instance in instances:
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start_time = timezone.localtime(instance.start)
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start_date = start_time.date().isoformat()
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if start_date not in totals.keys():
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totals[start_date] = timezone.timedelta()
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totals[start_date] += instance.duration
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2017-08-25 16:19:06 +00:00
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def sleep_times(child):
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"""Create a graph showing blocked out periods of sleep during each day."""
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instances = Sleep.objects.filter(child=child).order_by('start')
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y_df = pd.DataFrame()
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text_df = pd.DataFrame()
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last_end_time = None
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adjustment = None
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df_index = 0
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for instance in instances:
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start_time = timezone.localtime(instance.start)
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end_time = timezone.localtime(instance.end)
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start_date = start_time.date().isoformat()
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duration = instance.duration
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# Check if the previous entry crossed midnight (see below).
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if adjustment:
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# Fake (0) entry to keep the color switching logic working.
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df_index = _add_sleep_entry(
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y_df, text_df, 0, adjustment['column'], 0)
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# Real adjustment entry.
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df_index = _add_sleep_entry(
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y_df,
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text_df,
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df_index,
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adjustment['column'],
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adjustment['duration'].seconds/60,
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'Asleep {} ({} to {})'.format(
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duration_string(adjustment['duration']),
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adjustment['start_time'].strftime('%I:%M %p'),
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adjustment['end_time'].strftime('%I:%M %p')
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)
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)
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last_end_time = timezone.localtime(adjustment['end_time'])
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adjustment = None
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# If the dates do not match, set up an adjustment for the next day.
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if end_time.date() != start_time.date():
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adj_start_time = end_time.replace(hour=0, minute=0, second=0)
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adjustment = {
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'column': end_time.date().isoformat(),
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'start_time': adj_start_time,
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'end_time': end_time,
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'duration': end_time - adj_start_time
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}
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# Adjust end_time for the current entry.
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end_time = end_time.replace(
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day=start_time.day, hour=23, minute=59, second=0)
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duration = end_time - start_time
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2017-08-25 18:17:15 +00:00
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if start_date not in y_df:
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last_end_time = start_time.replace(hour=0, minute=0, second=0)
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# Awake time.
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df_index = _add_sleep_entry(
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y_df,
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text_df,
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df_index,
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start_date,
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(start_time - last_end_time).seconds/60
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)
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# Asleep time.
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df_index = _add_sleep_entry(
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y_df,
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text_df,
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df_index,
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start_date,
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duration.seconds/60,
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'Asleep {} ({} to {})'.format(
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duration_string(duration),
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start_time.strftime('%I:%M %p'),
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end_time.strftime('%I:%M %p')
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)
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)
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2017-08-25 21:32:46 +00:00
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2017-08-25 16:19:06 +00:00
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last_end_time = end_time
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2017-08-25 18:17:15 +00:00
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dates = list(y_df)
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traces = []
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color = 'rgba(255, 255, 255, 0)'
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for index, row in y_df.iterrows():
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traces.append(go.Bar(
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x=dates,
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y=row,
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text=text_df.ix[index],
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hoverinfo='text',
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marker={'color': color},
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showlegend=False,
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))
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if color == 'rgba(255, 255, 255, 0)':
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color = 'rgb(0, 0, 255)'
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else:
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color = 'rgba(255, 255, 255, 0)'
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layout_args = default_graph_layout_options()
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layout_args['margin']['b'] = 100
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layout_args['barmode'] = 'stack'
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layout_args['hovermode'] = 'closest'
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layout_args['title'] = '<b>Sleep Patterns</b><br>{}'.format(child)
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layout_args['height'] = 600
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layout_args['xaxis']['title'] = 'Date'
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layout_args['xaxis']['type'] = 'category'
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layout_args['xaxis']['tickangle'] = -65
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start = timezone.localtime().strptime('12:00 AM', '%I:%M %p')
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ticks = OrderedDict()
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ticks[0] = start.strftime('%I:%M %p')
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for i in range(30, 60*24, 30):
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ticks[i] = (start + timezone.timedelta(minutes=i)).strftime('%I:%M %p')
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layout_args['yaxis']['title'] = 'Time of day'
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layout_args['yaxis']['rangemode'] = 'tozero'
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layout_args['yaxis']['tickmode'] = 'array'
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layout_args['yaxis']['tickvals'] = list(ticks.keys())
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layout_args['yaxis']['ticktext'] = list(ticks.values())
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layout_args['yaxis']['tickfont'] = {'size': 10}
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fig = go.Figure({
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'data': traces,
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'layout': go.Layout(**layout_args)
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})
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output = plotly.plot(fig, output_type='div', include_plotlyjs=False)
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return split_graph_output(output)
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2017-08-25 21:32:46 +00:00
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def _add_sleep_entry(y_df, text_df, index, column, duration, text=''):
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"""Create a duration and text description entry in a DataFrame and return
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the next index on success."""
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if column not in y_df:
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y_df.assign(**{column: 0 in range(0, len(y_df.index))})
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text_df.assign(**{column: 0 in range(0, len(text_df.index))})
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index = 0
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y_df.set_value(index, column, duration)
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text_df.set_value(index, column, text)
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return index + 1
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