Asif Iqbal wrote:
> 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
Can you post a self-contained example, i. e. a small script that also
creates a -- hopefully small -- DataFrame and then triggers the ValueError?
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