diff --git a/dios/dios.py b/dios/dios.py
index 4a31acc50a542a0ace4c54f15a02fb81dd44d99e..7a6638aa87fc3021c574c7cc2a5a10bdd2948d22 100644
--- a/dios/dios.py
+++ b/dios/dios.py
@@ -72,7 +72,7 @@ class DictOfSeries:
def __init__(self, data=None, columns=None, itype=MixedItype, downcast_policy='save'):
- self._data = pd.Series()
+ self._data = pd.Series(dtype='O')
# We need to keep track of the index-type (itype) of every new Series.
# If the itypes differ between different series, slicing will almost always fail
# (eg. a datetime-like slice cannot work on a numeric index and vice versa).
@@ -189,7 +189,7 @@ class DictOfSeries:
new = self._getitem_bool_listlike(key)
else:
# work on columns
- new = self.copy_empty()
+ new = self.copy_empty(columns=False)
new._data = self._data[key]
return new
@@ -198,7 +198,7 @@ class DictOfSeries:
if key == slice(None):
return self.copy()
- new = self.copy_empty()
+ new = self.copy_empty(columns=False)
for k in self.columns:
new._data.at[k] = self._data.at[k][key]
return new
@@ -210,7 +210,7 @@ class DictOfSeries:
if not is_bool_indexer(key[k]):
raise ValueError("Must pass DictOfSeries with boolean values only")
- new = self.copy_empty()
+ new = self.copy_empty(columns=True)
for k in keys:
ser = self._data.at[k]
boolser = key[k]
@@ -220,7 +220,7 @@ class DictOfSeries:
return new
def _getitem_bool_listlike(self, key):
- new = self.copy_empty()
+ new = self.copy_empty(columns=False)
for k in self.columns:
new._data.at[k] = self._data.at[k].loc[key]
return new
@@ -348,7 +348,7 @@ class DictOfSeries:
return self.copy(deep=True)
def copy(self, deep=True):
- new = self.copy_empty()
+ new = DictOfSeries(itype=self.itype)
# We use `_data` here, because all checks are already done.
# So this should be much faster, especially, because we use the underlying dict for
# getting and setting the values, instead of ``__setitem__`` and ``__getitem__``.
@@ -356,10 +356,8 @@ class DictOfSeries:
new._data.at[i] = self._data.at[i].copy(deep=deep)
return new
- def copy_empty(self):
- new = DictOfSeries()
- new._itype = self.itype
- return new
+ def copy_empty(self, columns=True):
+ return DictOfSeries(columns=self.columns if columns is True else None, itype=self.itype)
def to_df(self):
return self._data.apply(lambda s: s).transpose()
@@ -399,7 +397,7 @@ class DictOfSeries:
pass
if need_dios:
- dios = self.copy_empty()
+ dios = self.copy_empty(columns=False)
for i, c in enumerate(self.columns):
dios[c] = pd.Series(new[i])
new = dios
@@ -408,7 +406,7 @@ class DictOfSeries:
return new
def _op1(self, op):
- new = self.copy_empty()
+ new = self.copy_empty(columns=False)
try:
for k in self.columns:
new[k] = op(self[k])
@@ -448,7 +446,7 @@ class DictOfSeries:
else:
raise NotImplementedError
- new = self if inplace else self.copy_empty()
+ new = self if inplace else self.copy_empty(columns=True)
try:
for k, val in gen():
new[k] = val
@@ -479,7 +477,8 @@ class DictOfSeries:
def pprint(dios, max_rows=10, max_cols=2, delim=' '):
if dios.empty:
- return "Empty DictionaryOfSeries"
+ return f"Empty DictionaryOfSeries\n" \
+ f"Columns: {dios.columns.to_list()}"
sstr = []
cols = list(dios.columns)
diff --git a/dios/locator.py b/dios/locator.py
index e0eff837f4b8fca9d299121fd1ebfce4619f02e4..332c53093294892a4efc43aaed46fdd722866e1b 100644
--- a/dios/locator.py
+++ b/dios/locator.py
@@ -49,7 +49,7 @@ class _LocIndexer(_Indexer):
if is_hashable(rowkey):
new = data
else:
- new = self._dios.copy_empty()
+ new = self._dios.copy_empty(columns=False)
new._data = data
return new
@@ -100,7 +100,7 @@ class _iLocIndexer(_Indexer):
if is_integer(rowkey):
new = data
else:
- new = self._dios.copy_empty()
+ new = self._dios.copy_empty(columns=False)
new._data = data
return new
@@ -139,9 +139,57 @@ class _aLocIndexer(_Indexer):
raise NotImplementedError
def __getitem__(self, key):
- # todo
- raise NotImplementedError
+ if is_dios_like(key):
+ raise NotImplementedError
+ else:
+ rowkey, colkey = self._unpack_key(key)
+
+ # filter column key
+
+ # make column-slice from scalar
+ if is_hashable(colkey):
+ colkey = [colkey] if colkey in self._dios.columns else []
+
+ # pd.Series(a=True, b=False, x=True), columns:[a,b,c,d,] -> [a,]
+ elif is_bool_series(colkey):
+ colkey = self._dios.columns.intersection(colkey[colkey].index).to_list()
+ # filter only existing columns from list
+ elif is_list_like_not_nested(colkey):
+ colkey = [c for c in self._dios.columns if c in colkey]
+
+ else:
+ colkey = self._data.loc[colkey].index.to_list()
+
+ # filter row key
+
+ # make row-slice from scalar
+ if is_hashable(rowkey):
+ rowkey = [slice(rowkey, rowkey)] * len(colkey)
+
+ # pd.Series(1=True, 4=False, 12=True)
+ # align every series, in columns
+ elif is_bool_series(rowkey):
+ rowkey = rowkey[rowkey] # kill False
+ rkeys = []
+ for c in colkey:
+ rkeys += [self._data.at[c].index.intersection(rowkey.index)]
+ rowkey = rkeys
+
+ # filter only existing rows from list
+ elif is_list_like_not_nested(rowkey):
+ rkeys = []
+ for c in colkey:
+ rkeys += [self._data.at[c].index.intersection(rowkey)]
+ rowkey = rkeys
+
+ else:
+ rowkey = [rowkey] * len(colkey)
+
+ new = self._dios.copy_empty(columns=False)
+ for i, c in enumerate(colkey):
+ new._data.at[c] = self._dios.loc[rowkey[i], c]
+ return new
# #############################################################################
diff --git a/dios/options.py b/dios/options.py
index 89d24308c4947ac759a192891fd0897c28213fe4..7d202525dd2bdc0ac5d4bedd4a4fd592be3fb4b1 100644
--- a/dios/options.py
+++ b/dios/options.py
@@ -81,7 +81,7 @@ dios_options = {
def align_dioslikes(self, other, nan=np.nan, policy=None):
- new = self.copy_empty()
+ new = self.copy_empty(columns=False)
for k in self.columns:
left = self.at[k]
if k not in other: