QST: DataFrame with freq of 2.5ms fails to plot
- [ X] I have searched the [[pandas] tag](https://stackoverflow.com/questions/tagged/pandas) on StackOverflow for similar questions.

- [X ] I have asked my usage related question on [StackOverflow](https://stackoverflow.com). Here: https://stackoverflow.com/questions/67183791/pandas-dataframe-with-time-index-and-freq-with-multiplier

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#### Question about pandas


I have a DataFrame with a time series as index.

    import pandas as pd
    from numpy.random import rand
    
    df = pd.DataFrame(rand(100000), index=None, columns=['a'])
    df['time'] = pd.date_range('2020-01-01 12:30:15',
                               periods=len(df['a']), freq='ms')
    df.set_index('time', inplace=True)
    df.plot()

When I put a multiplier on the frequency, it becomes extremely slow to plot `df2`, even if it has less elements than `df`. It actually crashed my Python kernel, and my laptop almost ran out of RAM

    df2 = pd.DataFrame(rand(50000), index=None, columns=['a'])
    df2['time'] = pd.date_range('2020-01-01 12:30:15',
                                periods=len(df2['a']), freq='2.5ms')
    df2.set_index('time', inplace=True)
    df2.plot()

Trying with `freq=2500U` does not make any difference

I was wondering if this behavior is normal. Haven't tried to run this on a code profiler. Or with any other algorithms, to see if has any effect.

Thanks

Python 3.9.3-1,
Pandas 1.2.3-1,
Numpy  1.20.1-1,
Matplotlib 3.4.1-2
