On Mon, May 21, 2018 at 9:28 AM, Peter Otten <__pete...@web.de> wrote:
> Asif Iqbal wrote: > > > Hi, > > > > I am trying to add a new row to a new date in the dataframe like below > > > > df.loc['2018-01-24'] = [0,1,2,3,4,5] > > > > And I am getting the following error > > > > ValueError: cannot set using a list-like indexer with a different > length > > than the value > > > > I do have the right number of columns and I can lookup a row by the date > > > > df.loc['2018-01-23'] > > > > df.shape > > (8034, 6) > > > > df.index > > DatetimeIndex(['2018-01-23', '2018-01-22', '2018-01-19', '2018-01-18', > > '2018-01-17', '2018-01-16', '2018-01-12', '2018-01-11', > > '2018-01-10', '2018-01-09', > > ... > > '1986-03-25', '1986-03-24', '1986-03-21', '1986-03-20', > > '1986-03-19', '1986-03-18', '1986-03-17', '1986-03-14', > > '1986-03-13', '2018-01-24'], > > dtype='datetime64[ns]', name='date', length=8034, > freq=None) > > > > Any idea how to add a new row to a new date? > > My experiments indicate that there may be multiple values with the same > key: > > > >>> import pandas as pd > >>> df = pd.DataFrame([[1,2], [3,4], [5,6], [7,8]], index=["a", "b", "a", > "a"]) > >>> df.loc["a"] > 0 1 > a 1 2 > a 5 6 > a 7 8 > > [3 rows x 2 columns] > >>> df.loc["a"] = [10, 20] > Traceback (most recent call last): > File "<stdin>", line 1, in <module> > File "/usr/lib/python3/dist-packages/pandas/core/indexing.py", line 98, > in > __setitem__ > self._setitem_with_indexer(indexer, value) > File "/usr/lib/python3/dist-packages/pandas/core/indexing.py", line > 422, > in _setitem_with_indexer > self.obj._data = self.obj._data.setitem(indexer, value) > File "/usr/lib/python3/dist-packages/pandas/core/internals.py", line > 2396, > in setitem > return self.apply('setitem', *args, **kwargs) > File "/usr/lib/python3/dist-packages/pandas/core/internals.py", line > 2376, > in apply > applied = getattr(blk, f)(*args, **kwargs) > File "/usr/lib/python3/dist-packages/pandas/core/internals.py", line > 615, > in setitem > raise ValueError("cannot set using a list-like indexer " > ValueError: cannot set using a list-like indexer with a different length > than the value > > If found two ways to resolve this, > > (1) the obvious, ensure that the lengths are the same: > > >>> df.loc["a"] = [[10, 20], [30, 40], [50, 60]] > >>> df > 0 1 > a 10 20 > b 3 4 > a 30 40 > a 50 60 > > (2) pass the key as a tuple: > > >>> df.loc["a",] = [1000, 2000] > >>> df > 0 1 > a 1000 2000 > b 3 4 > a 1000 2000 > a 1000 2000 > > [4 rows x 2 columns] > > I suspect that you want neither, and instead avoid duplicate keys. I want to overwrite the row print ( df.loc['2018-01-24'] ) 2018-01-24 0.0 1.0 2.0 3.0 4.0 NaN df.loc['2018-01-24'] = [0,1,2,3,4,5] ValueError: cannot set using a list-like indexer with a different length than the value > > _______________________________________________ > Tutor maillist - Tutor@python.org > To unsubscribe or change subscription options: > https://mail.python.org/mailman/listinfo/tutor > -- Asif Iqbal PGP Key: 0xE62693C5 KeyServer: pgp.mit.edu A: Because it messes up the order in which people normally read text. Q: Why is top-posting such a bad thing? _______________________________________________ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor