Grouping OHLC data by day using groupby

I’m reading minute data from a sqlite db into a dataframe where the index is a datetime object:

                             open    high     low   close  volume  trade_count        vwap ticker
index                                                                                            
2022-09-13 04:26:00+00:00  163.50  163.50  163.50  163.50   298.0         12.0  163.503255   AAPL
2022-09-13 04:45:00+00:00  163.50  163.50  163.50  163.50   727.0          1.0  163.500000   AAPL
2022-09-13 05:16:00+00:00  163.43  163.43  163.43  163.43   202.0          4.0  163.430000   AAPL
2022-09-13 05:44:00+00:00  163.50  163.50  163.50  163.50   121.0          2.0  163.499587   AAPL
2022-09-13 05:45:00+00:00  163.46  163.46  163.46  163.46   200.0          2.0  163.460000   AAPL
...                           ...     ...     ...     ...     ...          ...         ...    ...
2022-09-14 19:57:00+00:00   99.73   99.73   99.69   99.69  1273.0         18.0   99.693425   ZROZ
2022-09-14 19:58:00+00:00   99.69   99.69   99.66   99.69  1114.0         11.0   99.686965   ZROZ
2022-09-14 19:59:00+00:00   99.69   99.82   99.69   99.76  9764.0         76.0   99.736332   ZROZ
2022-09-14 20:00:00+00:00   99.76   99.76   99.76   99.76  2168.0          1.0   99.760000   ZROZ
2022-09-14 20:33:00+00:00   99.96   99.96   99.96   99.96   150.0          4.0   99.968667   ZROZ

[317028 rows x 8 columns] df

I want to split this massive dataframe into bits, grouped by the ticker, and the day. When I try the following method:

table = df.groupby(pd.Grouper(key='index', freq='1D'))

I get the error:

    raise KeyError(f"The grouper name {key} is not found")
KeyError: 'The grouper name index is not found'

When I change the key to:

table = df.groupby(pd.Grouper(key=df.index, freq='1D'))

I get the error:

    if getattr(self._gpr_index, "name", None) == key and isinstance(
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

How can I group by ticker and by day?

>Solution :

Because key parameter is for column name you can omit it:

table = df.groupby(pd.Grouper(freq='1D'))

Or use level parameter:

table = df.groupby(pd.Grouper(level='index', freq='1D'))

Or convert index to column (in my opinion overcomplicated):

table = df.reset_index().groupby(pd.Grouper(key='index', freq='1D'))