23 version of cython to avoid problems with character encodings (GH14699) • Switched the test framework to use pytest (GH13097) • Reorganization of tests directory layout (GH14854, GH15707). 1.3.4 Deprecations (GH13522) • Bug in matplotlib AutoDataFormatter; this restores the second scaled formatting and re-adds micro-second scaled formatting (GH13131) • Bug in selection from a HDFStore with a fixed format Going forward, we are moving to a more functional style using the pytest framework, which offers a richer testing framework that will facilitate testing and developing. Thus, instead of writing test

23 version of cython to avoid problems with character encodings (GH14699) • Switched the test framework to use pytest (GH13097) • Reorganization of tests directory layout (GH14854, GH15707). 1.2.4 Deprecations (GH13522) • Bug in matplotlib AutoDataFormatter; this restores the second scaled formatting and re-adds micro-second scaled formatting (GH13131) • Bug in selection from a HDFStore with a fixed format Going forward, we are moving to a more functional style using the pytest framework, which offers a richer testing framework that will facilitate testing and developing. Thus, instead of writing test

previous page) In [116]: np.maximum(ser, idx) Out[116]: 0 4 1 5 2 6 dtype: int64 NumPy ufuncs are safe to apply to Series backed by non-ndarray arrays, for example arrays.SparseArray (see Sparse calculation) supports writing Excel files to buffer-like objects such as StringIO or BytesIO using ExcelWriter. # Safe import for either Python 2.x or 3.x try: from io import BytesIO except ImportError: from cStringIO ewma(x**2) - ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . 672 Chapter 3. User Guide

previously evaluated the supplied function consistently twice on the first group to infer if it is safe to use a fast code path. Particularly for functions with side effects, this was an undesired behavior to_excel() where custom objects (i.e. PeriodIndex) inside merged cells were not being converted into types safe for the Excel writer (GH27006) • Bug in read_hdf() where reading a timezone aware DatetimeIndex would Index([4, 5, 6]) In [118]: np.maximum(ser, idx) Out[118]: 0 4 1 5 2 6 dtype: int64 NumPy ufuncs are safe to apply to Series backed by non-ndarray arrays, for example SparseArray (see Sparse calculation)

previously evaluated the supplied function consistently twice on the first group to infer if it is safe to use a fast code path. Particularly for functions with side effects, this was an undesired behavior to_excel() where custom objects (i.e. PeriodIndex) inside merged cells were not being converted into types safe for the Excel writer (GH27006) • Bug in read_hdf() where reading a timezone aware DatetimeIndex would Index([4, 5, 6]) In [118]: np.maximum(ser, idx) Out[118]: 0 4 1 5 2 6 dtype: int64 NumPy ufuncs are safe to apply to Series backed by non-ndarray arrays, for example SparseArray (see Sparse calculation)

23 version of cython to avoid problems with character encodings (GH14699) • Switched the test framework to use pytest (GH13097) • Reorganization of tests directory layout (GH14854, GH15707). 1.5.4 Deprecations (GH13522) • Bug in matplotlib AutoDataFormatter; this restores the second scaled formatting and re-adds micro-second scaled formatting (GH13131) • Bug in selection from a HDFStore with a fixed format Going forward, we are moving to a more functional style using the pytest framework, which offers a richer testing framework that will facilitate testing and developing. Thus, instead of writing test

Index([4, 5, 6]) In [119]: np.maximum(ser, idx) Out[119]: 0 4 1 5 2 6 dtype: int64 NumPy ufuncs are safe to apply to Series backed by non-ndarray arrays, for example arrays.SparseArray 188 Chapter 2. User locales, an na_rep argument to display missing data, and an escape ar- gument to help displaying safe-HTML or safe-LaTeX. The default formatter is configured to adopt pandas’ regular display.precision option ewma(x**2) - ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . (For ?? = 1, this reduces

Index([4, 5, 6]) In [119]: np.maximum(ser, idx) Out[119]: 0 4 1 5 2 6 dtype: int64 NumPy ufuncs are safe to apply to Series backed by non-ndarray arrays, for example arrays.SparseArray (see Sparse calculation) locales, an na_rep argument to display missing data, and an escape argument to help displaying safe-HTML or safe-LaTeX. The default formatter is configured to adopt pandas’ regular display. precision option ewma(x**2) - ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . (For ?? = 1, this reduces

Index([4, 5, 6]) In [119]: np.maximum(ser, idx) Out[119]: 0 4 1 5 2 6 dtype: int64 NumPy ufuncs are safe to apply to Series backed by non-ndarray arrays, for example arrays.SparseArray (see Sparse calculation) locales, an na_rep argument to display missing data, and an escape argument to help displaying safe-HTML or safe-LaTeX. The default formatter is configured to adopt pandas’ regular display. precision option ewma(x**2) - ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . (For ?? = 1, this reduces

Index([4, 5, 6]) In [119]: np.maximum(ser, idx) Out[119]: 0 4 1 5 2 6 dtype: int64 NumPy ufuncs are safe to apply to Series backed by non-ndarray arrays, for example arrays.SparseArray (see Sparse calculation) locales, an na_rep argument to display missing data, and an escape argument to help displaying safe-HTML or safe-LaTeX. The default formatter is configured to adopt pandas’ styler.format. precision option ewma(x**2) - ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . (For ?? = 1, this reduces