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# What’s new in 0.25.1 (August 21, 2019)

These are the changes in pandas 0.25.1. See Release notes for a full changelog including other versions of pandas.

## IO and LZMA

Some users may unknowingly have an incomplete Python installation lacking the `lzma` module from the standard library. In this case, `import pandas` failed due to an `ImportError` (GH 27575). pandas will now warn, rather than raising an `ImportError` if the `lzma` module is not present. Any subsequent attempt to use `lzma` methods will raise a `RuntimeError`. A possible fix for the lack of the `lzma` module is to ensure you have the necessary libraries and then re-install Python. For example, on MacOS installing Python with `pyenv` may lead to an incomplete Python installation due to unmet system dependencies at compilation time (like `xz`). Compilation will succeed, but Python might fail at run time. The issue can be solved by installing the necessary dependencies and then re-installing Python.

## Bug fixes

### Categorical

- Bug in `Categorical.fillna()` that would replace all values, not just those that are `NaN` (GH 26215)

### Datetimelike

- Bug in `to_datetime()` where passing a timezone-naive `DatetimeArray` or `DatetimeIndex` and `utc=True` would incorrectly return a timezone-naive result (GH 27733)

- Bug in `Period.to_timestamp()` where a `Period` outside the `Timestamp` implementation bounds (roughly 1677-09-21 to 2262-04-11) would return an incorrect `Timestamp` instead of raising `OutOfBoundsDatetime` (GH 19643)

- Bug in iterating over `DatetimeIndex` when the underlying data is read-only (GH 28055)

### Timezones

- Bug in `Index` where a numpy object array with a timezone aware `Timestamp` and `np.nan` would not return a `DatetimeIndex` (GH 27011)

### Numeric

- Bug in `Series.interpolate()` when using a timezone aware `DatetimeIndex` (GH 27548)

- Bug when printing negative floating point complex numbers would raise an `IndexError` (GH 27484)

- Bug where `DataFrame` arithmetic operators such as `DataFrame.mul()` with a `Series` with axis=1 would raise an `AttributeError` on `DataFrame` larger than the minimum threshold to invoke numexpr (GH 27636)

- Bug in `DataFrame` arithmetic where missing values in results were incorrectly masked with `NaN` instead of `Inf` (GH 27464)

### Conversion

- Improved the warnings for the deprecated methods `Series.real()` and `Series.imag()` (GH 27610)

### Interval

- Bug in `IntervalIndex` where `dir(obj)` would raise `ValueError` (GH 27571)

### Indexing

- Bug in partial-string indexing returning a NumPy array rather than a `Series` when indexing with a scalar like `.loc['2015']` (GH 27516)

- Break reference cycle involving `Index` and other index classes to allow garbage collection of index objects without running the GC. (GH 27585, GH 27840)

- Fix regression in assigning values to a single column of a DataFrame with a `MultiIndex` columns (GH 27841).

- Fix regression in `.ix` fallback with an `IntervalIndex` (GH 27865).

### Missing

- Bug in `pandas.isnull()` or `pandas.isna()` when the input is a type e.g. `type(pandas.Series())` (GH 27482)

### IO

- Avoid calling `S3File.s3` when reading parquet, as this was removed in s3fs version 0.3.0 (GH 27756)

- Better error message when a negative header is passed in `pandas.read_csv()` (GH 27779)

- Follow the `min_rows` display option (introduced in v0.25.0) correctly in the HTML repr in the notebook (GH 27991).

### Plotting

- Added a `pandas_plotting_backends` entrypoint group for registering plot backends. See Plotting backends for more (GH 26747).

- Fixed the re-instatement of Matplotlib datetime converters after calling `pandas.plotting.deregister_matplotlib_converters()` (GH 27481).

- Fix compatibility issue with matplotlib when passing a pandas `Index` to a plot call (GH 27775).

### GroupBy/resample/rolling

- Fixed regression in `pands.core.groupby.DataFrameGroupBy.quantile()` raising when multiple quantiles are given (GH 27526)

- Bug in `DataFrameGroupBy.transform()` where applying a timezone conversion lambda function would drop timezone information (GH 27496)

- Bug in `GroupBy.nth()` where `observed=False` was being ignored for Categorical groupers (GH 26385)

- Bug in windowing over read-only arrays (GH 27766)

- Fixed segfault in `.DataFrameGroupBy.quantile` when an invalid quantile was passed (GH 27470)

### Reshaping

- A `KeyError` is now raised if `.unstack()` is called on a `Series` or `DataFrame` with a flat `Index` passing a name which is not the correct one (GH 18303)

- Bug `merge_asof()` could not merge `Timedelta` objects when passing `tolerance` kwarg (GH 27642)

- Bug in `DataFrame.crosstab()` when `margins` set to `True` and `normalize` is not `False`, an error is raised. (GH 27500)

- `DataFrame.join()` now suppresses the `FutureWarning` when the sort parameter is specified (GH 21952)

- Bug in `DataFrame.join()` raising with readonly arrays (GH 27943)

### Sparse

- Bug in reductions for `Series` with Sparse dtypes (GH 27080)

### Other

- Bug in `Series.replace()` and `DataFrame.replace()` when replacing timezone-aware timestamps using a dict-like replacer (GH 27720)

- Bug in `Series.rename()` when using a custom type indexer. Now any value that isn’t callable or dict-like is treated as a scalar. (GH 27814)

## Contributors

For contributors, please see /usr/share/doc/contributors_list.txt or https://github.com/pandas-dev/pandas/graphs/contributors