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DOC: is confusing for ddof parameter of sem, var and std functions pandas-dev/pandas

https://github.com/pandas-dev/pandas/blob/7bb204a05fee20c3c825e7da39ccaf39fbeb8ca5/pandas/core/generic.py#L7160-L7161 It states that _ddof_ is for degrees of freedom with default value of 1. But...

Created - 3 comments - Docs Effort Low good first issue Numeric

DOC: improve docs for broadcasting behavior pandas-dev/pandas

The following result was quite surprising to me: ```python >>> df = pd.DataFrame({'a': np.arange(3), 'b': np.ones(3)}) >>> df + [np.ones(3), np.ones(3)] ...

Created - 4 comments - Docs Effort Low good first issue Indexing Numeric

ERR: pivot_table when number of levels larger than int32 range pandas-dev/pandas

#### Code Sample, a copy-pastable example if possible ``` import pandas as pd dat = pd.DataFrame({'ind1':list(range(1337600))*2,'ind2':list(range(3040))*2*440,'count':[1]*2*1337600}) dat.pivo...

Created - 6 comments - Algos Effort Low Error Reporting Numeric good first issue

BUG: int64 overflow/wrap around with sum() pandas-dev/pandas

#### Code Sample, a copy-pastable example if possible ```python In [1]: import pandas as pd In [2]: s = pd.Series([2**31]) In [3]: print(s.dtype, s.sum()) (dtype('int64'), -2147483648) ...

Created - 10 comments - Bug Difficulty Novice Effort Low good first issue HackIllinois 2017 Numeric

ENH: calculate average absolute difference by mean, median or mode pandas-dev/pandas

The generic function `.mad()` calculates the mean absolute difference of a set of data, but in some cases the median absolute difference is more appropriate. In `R`, the `mad()` function accepts a ...

Created - 11 comments - API Design Effort Low Numeric good first issue

DOC: Clarifiy fill_value behavior in arithmetic ops pandas-dev/pandas

When adding two DataFrames using `df1.add(df2)` one can use the `fill_value` parameter to fill in any NaNs that might come up. This parameter seems pretty broken: ```python a = pd.DataFrame(np....

Created - 11 comments - Docs Effort Low Missing-data Numeric Usage Question good first issue

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