code
stringlengths
3
6.57k
func(x, *args, **kwds)
len(self.columns)
len(self.index)
self._apply_empty_result(func, axis, reduce, *args, **kwds)
isinstance(f, np.ufunc)
f(self.values)
all(self.shape)
self._apply_raw(f, axis)
self._apply_standard(f, axis, reduce=reduce)
self._apply_broadcast(f, axis)
_apply_empty_result(self, func, axis, reduce, *args, **kwds)
isinstance(func(_EMPTY_SERIES, *args, **kwds)
Series(NA, index=self._get_agg_axis(axis)
self.copy()
_apply_raw(self, func, axis)
lib.reduce(self.values, func, axis=axis)
np.apply_along_axis(func, axis, self.values)
Series(result, index=self._get_agg_axis(axis)
_apply_standard(self, func, axis, ignore_failures=False, reduce=True)
first (by default)
Series(NA, index=self._get_axis(axis)
self._get_agg_axis(axis)
Series(result, index=labels)
self.icol(i)
range(len(self.columns)
Series.from_array(arr, index=res_columns, name=name, dtype=dtype)
enumerate(zip(values, res_index)
AssertionError('Axis must be 0 or 1, got %s' % str(axis)
enumerate(series_gen)
func(v)
keys.append(v.name)
successes.append(i)
len(successes)
len(res_index)
res_index.take(successes)
enumerate(series_gen)
func(v)
keys.append(v.name)
hasattr(e, 'args')
com.pprint_thing(k)
len(results)
is_sequence(results[0])
isinstance(results[0], Series)
self._constructor(data=results, index=index)
result.convert_objects(copy=False)
Series(results)
_apply_broadcast(self, func, axis)
AssertionError('Axis must be 0 or 1, got %s' % axis)
np.empty_like(target.values)
enumerate(columns)
func(target[col])
applymap(self, func)
map(func, series)
infer(x)
com.needs_i8_conversion(x)
com.i8_boxer(x)
lib.map_infer(_values_from_object(x)
lib.map_infer(_values_from_object(x)
self.apply(infer)
append(self, other, ignore_index=False, verify_integrity=False)
pd.DataFrame([[1, 2], [3, 4]], columns=list('AB')
pd.DataFrame([[5, 6], [7, 8]], columns=list('AB')
df.append(df2)
df.append(df2, ignore_index=True)
isinstance(other, (Series, dict)
isinstance(other, dict)
Series(other)
self.columns.tolist()
self.columns.union(other.index)
difference(self.columns)
tolist()
other.reindex(combined_columns, copy=False)
DataFrame(other.values.reshape((1, len(other)
convert_objects()
self.columns.equals(combined_columns)
self.reindex(columns=combined_columns)
isinstance(other, list)
isinstance(other[0], DataFrame)
DataFrame(other)
if (self.columns.get_indexer(other.columns)
all()
isinstance(other, (list, tuple)
Column(s)
calling (left)
isinstance(other, Series)
ValueError('Other Series must have a name')
DataFrame({other.name: other})
isinstance(other, DataFrame)
list(other)
all(df.index.is_unique for df in frames)
Substitution('')
Appender(_merge_doc, indents=2)
corr(self, method='pearson', min_periods=1)
self._get_numeric_data()
_algos.nancorr(com._ensure_float64(mat)
_algos.nancorr_spearman(com._ensure_float64(mat)
nanops.get_corr_func(method)
len(cols)
np.empty((K, K)
np.isfinite(mat)