Categorical: - [x] #19513 Comparisons between Categorical, CategoricalIndex, and Series[category] are inconsistent - [x] #8995 API: comparisons of categorical data and (scalar or list-like)

Series-specific: - [x] #19252 Series has no __rdivmod__ (closed by #23271) - [x] #19322 Series division by zero does not get filled for some dtypes - [x] #13843 BUG/API Series/Index integer floordiv/mod inconsistency

DataFrame - [x] #15697 pd.DataFrame([pd.NaT]).eq(pd.NaT) returns NaN instead of bool. == is OK. (closed by #22163) - [x] #13128 DataFrame.__eq__ is raising instead of returning bool (closed by #22163) - [x] #12437 DataFrame.sub broadcasting problem (closed by (I think) #22163) - [x] #8554 DataFrame[datetime64] - datetime is returning DataFrame[datetime64] instead of DataFrame[timedelta64] (closed by #22163) - [x] #8932 pd.Timestamp('2000-01-01') > pd.DataFrame({'x': range(5)}) returns 5 Trues instead of raising (closed by #22163) - [ ] #9006 datetime64 comparisons raise incorrectly - [x] #17559 DataFrame[datetime64] != pd.Series([pd.NaT]) raises (closed by (I think) #22163) - [x] #20088 DataFrame[timedelta64] / timedeltalike (closed by #22163) - [x] #21610 dtype changed when DataFrame add DateOffset (closed by #22163) - [x] #22005 DataFrame(Timestamp) add Timedelta fails (closed by #22163) - [x] #18874 DataFrame[datetime64].sub non-nano datetime64 fails (closed by #22163) - [x] #22017 Timestamp comparison inconsistency (closed by #22163)

Bool/Bitwise Methods: - [x] #5035 BUG: bool methods are wrong with DataFrame and Series (or at least wrong error) - [ ] #16873 ERR: Remove bitwise operations on dtype=object? - [x] #13896 API: Series/DataFrame logical op NaN propagation

Unsorted: - [x] #19123 DatetimeIndex + ndarray[int] wrong, reverse op errors (TODO: track down what PR fixed it) - [x] #15552 BUG: tz-aware datetime with column-wise comparisions failing - [x] #9369 BUG: binary comparison of numpy.int/float and Series - [x] #4615 Inconsistent comparisons between Series and 2-D ndarray - [x] #19389 Series[Period] +/- NaT returns Series[datetime64] - [x] #21980 np.ndarray[object] - Timedelta raises (closed by #22054) - [x] #19804 DTI/TDI comparison ops with incompatible types - [x] #22042 BUG: Mismatched Comparisons Inconsistencies - [x] #22047 Breaking change multiplication bool and int (closed by #22163) - [x] #7830 Equality comparison raises exception (closed by #22074) - [x] #11565 Comparing Strings to Numbers: No ValueError - [x] #20876 Comparing DataFrame with columns with mixed types to a scalar should fail (closed by #22163) - [x] #13637 API: Index/Series/DataFrame op 1-d list-like coercion - [x] #5202 ENH: Period ops NaT & timedelta ops - [ ] #20442 BUG: None is not equal to None - [x] #21793 BUG: PeriodIndex comparisons break on listlike - [x] #12689 ERR: Invalid error reporting when comparing vs None - [x] #22537 BUG: incorrect casting in ndarray + DataFrame (closed by #22696) - [x] #5035 BUG: bool methods are wrong with DataFrame and Series (or at least wrong error) - [x] #5284 Binary operators between DataFrame and Series object doesn't seem to work - [x] #20090 Mixed-dtype dataframe comparison with array raises incorrectly (closed by #23132)

TimedeltaIndex vs Series[timedelta64] - [x] Series[timedelta64] // timedelta raises TypeError. See others in #18831. (Closed by #18831) - [x] Series[timedelta64] +/- TimedeltaIndex gets cast to int64 #17250. Update: This appears to affect 0.22.0 but no longer affect master as of 2018-01-02. Needs a test. (closed by #19044) - [x] pd.Timedelta('3 hours') / pd.Series([pd.Timedelta('1 day')]) returns 0 days, not 0.125 (closed by #18831) - [x] TimedeltaIndex * Series[int] returns TimedeltaIndex #19042 (closed by #19253) - [x] Series[timedelta64] + TimedeltaIndex inherits name from the latter. This does not occur in 0.22.0, occurs in master as of 2018-01-02. #19043 (closed by #19044) - [x] TimedeltaIndex + Series[timedelta64] raises ValueError (TODO: issue?) (Fixed by #18884 but needs test) No original issue, no longer re-producable. - [x] TimedeltaIndex + Series[offsets] gets transposed and returns Series of TimedeltaIndexes. Analogue to #18849 (closed by #18884 (I think)) - [x] TimedeltaIndex +/- zero-dimensional integer arrays #19012 (closed by #19013)

DatetimeIndex vs Series[datetime64] - [x] Series[offsets] + Series[datetime64] raises #19211 (closed sometime before 4ebdc50f250ab2fd4312f8) - [x] Series.__sub__ incorrect with non-nano datetime64 #7996 (closed by #18783) - [x] Series[datetime64] - pd.NaT returns datetime64-dtype, DatetimeIndex - pd.NaT returns timedelta64-dtype. #18808, #17837. (closed by #19024) - [x] Series +/- Series[offsets] applies element-wise. DatetimeIndex +/- box([offsets]) raises for box in [np.array, pd.Index] and for box == Series returns a Series of DatetimeIndex objects. (Closed by #18849) - [x] Series[datetime64tz] - DatetimeIndex[tz] (with same tz) raises, same with reverse op #19071. (Fixed by #18884 but needs test) (closed by #19072) - [x] DatetimeIndex[tz] + Series[timedelta64] returns DatetimeIndex (?). Example from #13905 but the behavior seems to have changed since then. As of late-Dec 2017 behavior is as in #18963. (Closed by #18884) - [x] Series is missing overflow checks #12534 (Note: this is not specific to datetime/timedelta. Even int64 is missing overflow checks) (closed by #19072 (but only for datetime dtypes) - [x] Series[datetime64] - PeriodIndex is allowed, DatetimeIndex - PeriodIndex is not. #18850. (closed by #19024) - [x] DatetimeIndex +/- zero-dimensional integer arrays #19012 (closed by #19013)

Timedelta (strictly speaking out of scope) - [x] pd.Timedelta(minutes=5, seconds=4) // np.timedelta64('NaT') --> -1 instead of NaN, also messes up for timedelta / Series([Timedelta, NaT]) (closed by #18961)

Comment From: nmusolino

I was asked to comment here about issue #20088.

Issue #20088 is closest in spirit to #8554, in the sense that both bugs involve arithmetic operations (subtraction and division, respectively) for dataframes containing timedelta values.

That said, the bugs are somewhat distinct... paraphrasing, #8554 is roughly this: DataFrame[date] - date should give timedeltas, whereas #20088 is roughly this: DataFrame[timedelta64] / timedelta64 should give float.

I suggest you re-open #20088 and add it to the list of "DataFrame" issues above.

Comment From: jreback

none of the issues here need to be reopened this is a master tracking issue and they are referenced

Comment From: jbrockmendel

Down to 3 checkboxes, none of which are actionable. Closing.