Force Altair chart to display years

Using a data frame of dates and values starting from 1 Jan 2022:

import datetime as dt
import altair as alt
import polars as pl
import numpy as np

alt.renderers.enable("browser")

dates = pl.date_range(dt.date(2022, 1, 1), dt.date(2025, 1, 22), "1d", eager = True)
values = np.random.uniform(size = len(dates))
df = pl.DataFrame({"dates": dates, "values": values})
alt.Chart(df).mark_point().encode(alt.X("dates:T"), alt.Y("values:Q")).show()

But if I start the data frame from 2020 and filter it for dates > 1 Jan 2022:

dates_b = pl.date_range(dt.date(2020, 1, 1), dt.date(2025, 1, 22), "1d", eager = True)
values_b = np.random.uniform(size = len(dates_b))
df_b = pl.DataFrame({"dates": dates, "values": values})
alt.Chart(df_b.filter(pl.col("dates") > dt.date(2022, 1, 1))).mark_point().encode(alt.X("dates:T"), alt.Y("values:Q")).show()

How can I specify that years must be shown?

Note that I do get the right result if I filter using >= to include 1 Jan 2022, but that's besides the point. I always need years.

You can use labelExpr to build your own logic for setting tick labels. For example, this gives the year if the month is January and the month otherwise.

dates_b = pl.date_range(dt.date(2020, 1, 1), dt.date(2025, 1, 22), "1d", eager=True)
values_b = np.random.uniform(size=len(dates_b))
df_b = pl.DataFrame({"dates": dates, "values": values})
alt.Chart(df_b.filter(pl.col("dates") > dt.date(2022, 1, 1))).mark_point().encode(
    alt.X("dates:T").axis(
        labelExpr="timeFormat(datum.value, '%m') == '01' ? timeFormat(datum.value, '%Y') : timeFormat(datum.value, '%b')",
    ),
    alt.Y("values:Q"),
)