TST: add tests for DatetimeIndex.is_year_start/is_quarter_start on "BMS" frequency

[natmokval]

• closes BUG: DatetimeIndex.is_year_start breaks on BusinessMonthBegin frequency #58729
• Tests added and passed
• Added an entry in the latest `doc/source/whatsnew/v3.0.0.rst

[simonjayhawkins]

Thanks @natmokval for the PR.

Should the OP be an issue instead.? or is there already an open issue for this?

[natmokval]

Should the OP be an issue instead.? or is there already an open issue for this?

thanks @simonjayhawkins for the comment. No, there is no open issue for this.
It's my mistake; I should have opened an issue first. Now I've opened the issue for this PR.

[natmokval]

Fixed bug in DatetimeIndex.is_year_start and DatetimeIndex.is_quarter_start returning False instead of True when using BusinessMonthBegin frequency. @MarcoGorelli, could you please take a look at this PR?

[MarcoGorelli]

thanks for looking into this

not sure this fixes the issue to be honest:

In [2]: pd.DatetimeIndex(['1976-11-01', '1976-12-01', '1977-01-03'], freq='BMS') Out[2]: DatetimeIndex(['1976-11-01', '1976-12-01', '1977-01-03'], dtype='datetime64[s]', freq='BMS') In [3]: arr = pd.DatetimeIndex(['1976-11-01', '1976-12-01', '1977-01-03'], freq='BMS') In [4]: arr.is_year_start Out[4]: array([False, False, True]) In [5]: [x.is_year_start for x in arr] Out[5]: [False, False, False]

We'd expect Out[4] and Out[5] to be the same, right?

Here's a little hypothesis test I put together:

import pytest import hypothesis.strategies as st from hypothesis import given import pandas as pd from datetime import datetime @pytest.mark.parametrize('freq', [  'MS',  'BMS', ]) @given(dt = st.datetimes(min_value=datetime(1960, 1, 1), max_value=datetime(1980, 1, 1))) def test_me(freq, dt): d = pd.date_range(dt, periods=3, freq=freq) result = [x for x in d.is_year_start] expected = [x.is_year_start for x in d] assert result == expected

Granted, it looks like this is already super-broken on main anyway, but I think this requires a more general and a very careful and focused fix

[MarcoGorelli]

Sorry, as an addendum to my previous comment: Timestamp doesn't have freq, so the two results can't be expected to be the same

If I amend the hypothesis test to be:

@given(  dt = st.datetimes(min_value=datetime(1960, 1, 1), max_value=datetime(1980, 1, 1)),  n = st.integers(min_value=1, max_value=10),  freq = st.sampled_from(['BMS']) ) def test_me(freq, dt, n): freq = f'{n}{freq}' d = pd.date_range(dt, periods=3, freq=freq) result = [x for x in d.is_year_start] expected = [] for x in d: if x.is_year_start: expected.append(True) else: if x.day_of_week == 0 and (x - pd.Timedelta(days=1)).is_year_start: expected.append(True) elif x.day_of_week == 0 and (x - pd.Timedelta(days=2)).is_year_start: expected.append(True) else: expected.append(False) assert result == expected

then it does indeed pass

I think we should get #57494 in first though, as I think that that also fixes the issues "for free" (but then we keep the test from this one)

[natmokval]

I think we should get #57494 in first though, as I think that that also fixes the issues "for free" (but then we keep the test from this one)

thanks, I will update this PR after we get the #57494 in.

[natmokval]

@MarcoGorelli, I updated this PR, could you please take a look at my changes?

[MarcoGorelli]

thanks @natmokval !