Learning XML Erik T. Ray 2003 39.95 Even read XML from AWS S3 buckets such as Python Software Foundation’s IRS 990 Form: In [335]: df = pd.read_xml( .....: "s3://irs-form-990/201923199349319487_public arraysetops.py:272, in␣ ˓→unique(ar, return_index, return_inverse, return_counts, axis) 270 ar = np.asanyarray(ar) 271 if axis is None: --> 272 ret = _unique1d(ar, return_index, return_inverse, return_counts) .py:330, in␣ ˓→_unique1d(ar, return_index, return_inverse, return_counts) 327 optional_indices = return_index or return_inverse 329 if optional_indices: --> 330 perm = ar.argsort(kind='mergesort' if

Learning XML Erik T. Ray 2003 39.95 Even read XML from AWS S3 buckets such as Python Software Foundation’s IRS 990 Form: In [331]: df = pd.read_xml( .....: "s3://irs-form-990/201923199349319487_public thousands separators to support other 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’ The apply() function takes an extra func argument and performs generic rolling computations. The func ar- gument should be a single function that produces a single value from an ndarray input. raw specifies

(GH13599) • Bug in cartesian_product and MultiIndex.from_product which may raise with empty input ar- rays (GH12258) • Bug in pd.read_csv() which may cause a segfault or corruption when iterating in (GH9322) • Index.get_indexer now supports method='pad' and method='backfill' even for any target ar- ray, not just monotonic targets. These methods also work for monotonic decreasing as well as monotonic unstacking. • set_names(), set_labels(), and set_levels() methods now take an optional level keyword ar- gument to all modification of specific level(s) of a MultiIndex. Additionally set_names() now accepts

(GH13599) • Bug in cartesian_product and MultiIndex.from_product which may raise with empty input ar- rays (GH12258) • Bug in pd.read_csv() which may cause a segfault or corruption when iterating in (GH9322) • Index.get_indexer now supports method='pad' and method='backfill' even for any target ar- ray, not just monotonic targets. These methods also work for monotonic decreasing as well as monotonic unstacking. • set_names(), set_labels(), and set_levels() methods now take an optional level keyword ar- gument to all modification of specific level(s) of a MultiIndex. Additionally set_names() now accepts

arraysetops.py:272, in␣ ˓→unique(ar, return_index, return_inverse, return_counts, axis) 270 ar = np.asanyarray(ar) 271 if axis is None: --> 272 ret = _unique1d(ar, return_index, return_inverse, return_counts) .py:330, in␣ ˓→_unique1d(ar, return_index, return_inverse, return_counts) 327 optional_indices = return_index or return_inverse 329 if optional_indices: --> 330 perm = ar.argsort(kind='mergesort' if if return_index else 'quicksort') 331 aux = ar[perm] 332 else: TypeError: '<' not supported between instances of 'float' and 'str' Note: If you just want to handle one column as a categorical variable

(GH13599) • Bug in cartesian_product and MultiIndex.from_product which may raise with empty input ar- rays (GH12258) • Bug in pd.read_csv() which may cause a segfault or corruption when iterating in (GH9322) • Index.get_indexer now supports method='pad' and method='backfill' even for any target ar- ray, not just monotonic targets. These methods also work for monotonic decreasing as well as monotonic unstacking. • set_names(), set_labels(), and set_levels() methods now take an optional level keyword ar- gument to all modification of specific level(s) of a MultiIndex. Additionally set_names() now accepts

setops.py:274, in␣ ˓→unique(ar, return_index, return_inverse, return_counts, axis, equal_nan) 272 ar = np.asanyarray(ar) 273 if axis is None: --> 274 ret = _unique1d(ar, return_index, return_inverse py:333, in␣ ˓→_unique1d(ar, return_index, return_inverse, return_counts, equal_nan) 330 optional_indices = return_index or return_inverse 332 if optional_indices: --> 333 perm = ar.argsort(kind='mergesort' ort' if return_index else 'quicksort') 334 aux = ar[perm] 335 else: TypeError: '<' not supported between instances of 'float' and 'str' Note: If you just want to handle one column as a categorical

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The apply() function takes an extra func argument and performs generic rolling computations. The func ar- gument should be a single function that produces a single value from an ndarray input. raw specifies names, returning names where the callable function evaluates to True. An example of a valid callable ar- gument would be lambda x: x.upper() in ['AAA', 'BBB', 'DDD']. Using this parameter results in much names, returning names where the callable function evaluates to True. An example of a valid callable ar- gument would be lambda x: x.upper() in ['AAA', 'BBB', 'DDD']. Using this parameter results in much