Set Date Axis Intervals

Charts tick intervals are automatically sized by the relevant axis’ start and end values and calculating a reasonable number of ticks. However, many visualizations might be presented better with specific tick interavls given the use case. In these situations a tick_interval can be specified as an axis argument.

• The tick_interval for an axis_type=="date" should be of type dateutil.relativedelta.relativedelta

• For example, the x-axis is a date type, and the tick interval is set as 14 days

• Ticks will then be placed on the x-axis according to that interval

/home/runner/work/visualization_toolkit/visualization_toolkit/visualization_toolkit/helpers/plotly/charts/core/chart.py:651: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

import pandas as pd
from datetime import date
from dateutil.relativedelta import relativedelta

from visualization_toolkit.helpers.plotly import chart, axis, series


fig = chart(
    pdf,
    x_axis=axis(
        column_name="day",
        axis_type="date",
        label="Week Ending",
        tick_interval=relativedelta(days=14),
        axis_min=date(2024, 6, 30),
        axis_max=date(2024, 10, 20),
    ),
    chart_series=[
        series(
            column_name="abnb_gbv_share",
            label="ABNB GBV Share",
            color="dark-blue",
            mode="lines+markers",
        ),
    ],
    y1_axis=axis(
        axis_type="percent",
        axis_min=0,
        axis_max=1,
        tick_format="0.0%",
    ),
)

fig