Exemplo n.º 1
0
def fig_contexts_use(df, months, level, **kwargs):
    col_count = 3
    row_count = math.ceil(len(month_range(months)) / col_count)
    figure = make_subplots(
        row_count,
        col_count,
        specs=[[{
            'type': 'domain'
        } for c in range(col_count)] for r in range(row_count)],
        subplot_titles=[MONTH_NAMES[m - 1] for m in month_range(months)])

    def take_month(months):
        for m in month_range(months):
            yield trace_context_use(df[df.index.month == m],
                                    level,
                                    name=MONTH_NAMES[m - 1])

    pie_factory = take_month(months)
    try:
        for r in range(row_count):
            for c in range(col_count):
                figure.add_trace(next(pie_factory), r + 1, c + 1)
    except StopIteration as stop:
        pass
    return figure
Exemplo n.º 2
0
 def test_month_range(self):
     d = datetime(2010, 4, 16, 23, 3)
     start, end = utils.month_range(d)
     self.assertEqual(datetime(2010, 4, 1), start)
     self.assertEqual(datetime(2010, 4, 30, 23, 59, 59, 999999), end)
     d = datetime(2012, 12, 27, 0, 0)
     start, end = utils.month_range(d)
     self.assertEqual(datetime(2012, 12, 1), start)
     self.assertEqual(datetime(2012, 12, 31, 23, 59, 59, 999999), end)
Exemplo n.º 3
0
def fig_total_capacity_2(df, month_caps, months):
    machine_list = df['Tipo Máquina'].unique()
    months = month_range(months)
    month_names = [MONTH_NAMES[m - 1] for m in months]
    figure = go.Figure()
    for machine in machine_list:
        texts = []
        caps = []
        for month in months:
            total_cap = cap_per_machine_per_month(month_caps, machine, month)
            hours = total_cap // 60
            used_cap = df[df.index.month == month].groupby(
                'Tipo Máquina')['Tiempo de uso en minutos'].sum().divide(
                    total_cap).multiply(100).round(2).get(machine, 0)
            caps.append(used_cap)
            texts.append(
                f'{used_cap}% utilizado de una capacidad total de {hours} horas.'
            )
        figure.add_trace(
            go.Bar(x=month_names, y=caps, name=machine, hovertext=texts))
    figure.update_layout(barmode='group',
                         yaxis=dict(type='linear',
                                    ticksuffix='%',
                                    title='Capacidad Utilizada'))
    return figure
Exemplo n.º 4
0
def fig_records(df, months=None, stacked=False):
    machine_list = df['Tipo Máquina'].unique()
    months = month_range(months)

    def create_frame(df, serie_name):
        count = df['Tipo Máquina'].value_counts()
        frame = pd.DataFrame({'Tipo de Máquina': machine_list})
        frame[serie_name] = [count.get(machine, 0) for machine in machine_list]
        return frame

    extras = {'barmode': 'relative' if stacked else 'group'}

    figure = go.Figure()
    for m in months:
        name = MONTH_NAMES[m - 1]
        frame = create_frame(df[df.index.month == m], name)
        figure.add_trace(
            go.Bar(x=frame['Tipo de Máquina'],
                   y=frame[name],
                   name=name,
                   hoverinfo='name+y'))

    if stacked and months:
        frame = create_frame(df[df.index.month.isin(months)], 'Total')
        figure.add_trace(
            go.Scatter(x=frame['Tipo de Máquina'],
                       y=frame['Total'],
                       text=frame['Total'],
                       textposition='top center',
                       mode='text',
                       showlegend=False,
                       hoverinfo='skip'))
    figure.update_layout(yaxis={'title': 'Número de registros'}, **extras)

    return figure
Exemplo n.º 5
0
def total_ranges():
    return (
        ("prev_year", utils.prev_year_range()),
        ("this_year", utils.year_range()),
        ("prev_month", utils.prev_month_range()),
        ("this_month", utils.month_range()),
        ("prev_week", utils.prev_week_range()),
        ("this_week", utils.week_range()),
        ("this_day", utils.day_range()),
        ("prev_day", utils.prev_day_range()))
Exemplo n.º 6
0
def fig_hours(df, months=None, stacked=False):
    machine_list = df['Tipo Máquina'].unique()
    months = month_range(months)

    def create_frame(df, serie_name):
        count = df.groupby('Tipo Máquina').sum(
        )['Tiempo de uso en minutos'].divide(60).round(0)
        frame = pd.DataFrame({'Tipo de Máquina': machine_list})
        frame[serie_name] = [count.get(machine, 0) for machine in machine_list]
        return frame

    if months and type(months) == list:
        df = df[df.index.month.isin(months)]

    frame = create_frame(df, 'Total')

    figure = go.Figure()

    extras = {'barmode': 'relative' if stacked else 'group'}

    for m in months:
        name = MONTH_NAMES[m - 1]
        frame = create_frame(df[df.index.month == m], name)
        figure.add_trace(
            go.Bar(y=frame['Tipo de Máquina'],
                   x=frame[name],
                   name=name,
                   hoverinfo='name+x',
                   orientation='h'))

    if stacked and months:
        frame = create_frame(df[df.index.month.isin(months)], 'Total')
        figure.add_trace(
            go.Scatter(y=frame['Tipo de Máquina'],
                       x=frame['Total'],
                       text=frame['Total'],
                       textposition='middle right',
                       mode='text',
                       showlegend=False,
                       hoverinfo='skip'))

    figure.update_layout(
        xaxis={'title': f'Horas de uso {"total" if stacked else ""}'},
        **extras)
    return figure
Exemplo n.º 7
0
 def take_month(months):
     for m in month_range(months):
         yield trace_context_use(df[df.index.month == m],
                                 level,
                                 name=MONTH_NAMES[m - 1])