Closed
Description
It appears that if a dataframe has column headers of type DatetimeIndex, calling reset_index() throws AttributeError: 'str' object has no attribute 'view'. I see this both in v0.12 and the master branch.
If column headers are strings or integers, reset_index() works fine.
I'm guessing it's treating the new column array as type DatetimeIndex whereas it now has a string in the 0th position ('index'). Maybe the reset_index should first cast the columns as object and convert the DatetimeIndex values to strings?
In [48]: df = pd.DataFrame(data=np.random.rand(2, 2), columns=pd.date_range('1/1/2013', '1/2/2013'), index=['A', 'B'])
In [49]: df.reset_index()
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-49-6983677cc901> in <module>()
----> 1 df.reset_index()
/home/user/environments/python3/src/pandas/pandas/core/frame.py in reset_index(self, level, drop, inplace, col_level, col_fill)
2447 else:
2448 values = _maybe_cast(self.index.values)
-> 2449 new_obj.insert(0, name, values)
2450
2451 new_obj.index = new_index
/home/user/environments/python3/src/pandas/pandas/core/frame.py in insert(self, loc, column, value, allow_duplicates)
1940 value = self._sanitize_column(column, value)
1941 self._data.insert(
-> 1942 loc, column, value, allow_duplicates=allow_duplicates)
1943
1944 def _sanitize_column(self, key, value):
/home/user/environments/python3/src/pandas/pandas/core/internals.py in insert(self, loc, item, value, allow_duplicates)
2899
2900 try:
-> 2901 new_items = self.items.insert(loc, item)
2902 self.set_items_norename(new_items)
2903
/home/user/environments/python3/src/pandas/pandas/tseries/index.py in insert(self, loc, item)
1539
1540 new_index = np.concatenate((self[:loc].asi8,
-> 1541 [item.view(np.int64)],
1542 self[loc:].asi8))
1543 return DatetimeIndex(new_index, freq='infer')
AttributeError: 'str' object has no attribute 'view'
In [50]: df = pd.DataFrame(data=np.random.rand(2, 2), columns=[1, 2], index=['A', 'B'])
In [51]: df.reset_index()
Out[51]:
index 1 2
0 A 0.947575 0.370406
1 B 0.664856 0.686524
[2 rows x 3 columns]
In [52]: df = pd.DataFrame(data=np.random.rand(2, 2), columns=['C', 'D'], index=['A', 'B'])
In [53]: df.reset_index()
Out[53]:
index C D
0 A 0.053455 0.599483
1 B 0.776364 0.680425
[2 rows x 3 columns]