%f — fractional seconds (milliseconds)

The new %f pattern formats the millisecond component of a datetime, zero-padded to 3 digits (e.g. 007, 123).

import pandas as pd
from lets_plot import *

LetsPlot.setup_html()

df = pd.DataFrame({
    't': pd.date_range('2025-06-01 12:00:00', periods=12, freq='117ms'),
})
df['value'] = range(len(df))
df

	t	value
0	2025-06-01 12:00:00.000	0
1	2025-06-01 12:00:00.117	1
2	2025-06-01 12:00:00.234	2
3	2025-06-01 12:00:00.351	3
4	2025-06-01 12:00:00.468	4
5	2025-06-01 12:00:00.585	5
6	2025-06-01 12:00:00.702	6
7	2025-06-01 12:00:00.819	7
8	2025-06-01 12:00:00.936	8
9	2025-06-01 12:00:01.053	9
10	2025-06-01 12:00:01.170	10
11	2025-06-01 12:00:01.287	11

On the axis

# Milliseconds only
ggplot(df, aes('t', 'value')) + geom_point() + ggsize(700, 250) \
    + scale_x_datetime(format='%f')

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# Seconds + milliseconds
ggplot(df, aes('t', 'value')) + geom_point() + ggsize(700, 250) \
    + scale_x_datetime(format='%S.%f')

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# Full ISO-like timestamp with milliseconds
ggplot(df, aes('t', 'value')) + geom_point() + ggsize(700, 250) \
    + scale_x_datetime(format='%Y-%m-%dT%H:%M:%S.%f')

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In tooltips

ggplot(df, aes('t', 'value')) + ggsize(700, 250) \
    + geom_point(tooltips=layer_tooltips()
                 .format('^x', '%H:%M:%S.%f')
                 .line('t|^x')
                 .line('value|^y')) \
    + scale_x_datetime(format='%S.%f')

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