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expressions.evaluate(_compare, str_rep, self, other) |
_compare_frame(self, other, func, str_rep) |
self._indexed_same(other) |
self._compare_frame_evaluate(other, func, str_rep) |
_flex_compare_frame(self, other, func, str_rep, level) |
self._indexed_same(other) |
self.align(other, 'outer', level=level, copy=False) |
self._compare_frame_evaluate(other, func, str_rep) |
combine(self, other, func, fill_value=None, overwrite=True) |
a
(column, time) |
value (which might be NaN as well) |
len(other.index) |
self.align(other, copy=False) |
len(new_index) |
len(self.index) |
self.copy() |
len(other) |
other.copy() |
this.columns.union(other.columns) |
isnull(series) |
isnull(otherSeries) |
other_mask.all() |
copy() |
series.copy() |
otherSeries.copy() |
com._lcd_dtypes(this_dtype, other_dtype) |
series.astype(new_dtype) |
otherSeries.astype(new_dtype) |
i8 (datetimelike) |
com.needs_i8_conversion(new_dtype) |
func(series, otherSeries, True) |
func(series, otherSeries) |
com.ensure_float(arr) |
com._possibly_cast_to_datetime(arr, this_dtype) |
com._possibly_downcast_to_dtype(arr, this_dtype) |
combine_first(self, other) |
a.combine_first(b) |
combiner(x, y, needs_i8_conversion=False) |
hasattr(x, 'values') |
hasattr(y, 'values') |
isnull(x) |
x_values.view('i8') |
y_values.view('i8') |
isnull(x_values) |
self.combine(other, combiner, overwrite=False) |
callable(1d-array) |
NotImplementedError("Only left join is supported") |
isinstance(other, DataFrame) |
DataFrame(other) |
other.reindex_like(self) |
filter_func(this) |
isnull(that) |
notnull(that) |
notnull(this) |
any(mask_this & mask_that) |
ValueError("Data overlaps.") |
isnull(that) |
mask.all() |
notnull(this) |
first_valid_index(self) |
self.count(1) |
last_valid_index(self) |
self.count(1) |
pivot(self, index=None, columns=None, values=None) |
data (produce a "pivot" table) |
column (DataFrame) |
columns (Panel) |
df.pivot('foo', 'bar', 'baz') |
df.pivot('foo', 'bar') |
pivot(self, index=index, columns=columns, values=values) |
stack(self, level=-1, dropna=True) |
the (possibly hierarchical) |
Level(s) |
s.stack() |
isinstance(level, (tuple, list) |
stack_multiple(self, level, dropna=dropna) |
stack(self, level, dropna=dropna) |
unstack(self, level=-1) |
the (necessarily hierarchical) |
Level(s) |
pd.MultiIndex.from_tuples([('one', 'a') |
pd.Series(np.arange(1.0, 5.0) |
s.unstack(level=-1) |
s.unstack(level=0) |
s.unstack(level=0) |
df.unstack() |
unstack(self, level) |
diff(self, periods=1) |
self._data.diff(n=periods) |
self._constructor(new_data) |
index (axis=0) |
columns (axis=1) |
None (the default) |
df.apply(numpy.sqrt) |
df.apply(numpy.sum, axis=0) |
df.sum(0) |
df.apply(numpy.sum, axis=1) |
df.sum(1) |
self._get_axis_number(axis) |
isinstance(func, np.ufunc) |
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