When pandas.DataFrame.resample is used grouping by one or more integer columns and also resetting the index, an error arises because the integer columns already exist in the re-sampled dataframe before resetting the index.
What I Did
In [1]: import pandas as pd
In [2]: df = pd.DataFrame({
...: 'time': ['2010-01-01', '2010-01-02', '2010-01-03'],
...: 'str_id': ['a', 'b', 'c'],
...: 'int_id': [1, 2, 3],
...: 'value': [1, 2, 3]
...: })
In [3]: df['time'] = pd.to_datetime(df['time'])
In [4]: from mlblocks import MLBlock
In [5]: block = MLBlock('pandas.DataFrame.resample', rule='1D', on='time',
...: groupby=['str_id'], aggregation='mean', reset_index=True)
In [6]: block.produce(X=df)
Out[6]:
str time int value
0 a 2010-01-01 1 1
1 b 2010-01-02 2 2
2 c 2010-01-03 3 3
In [7]: block = MLBlock('pandas.DataFrame.resample', rule='1D', on='time',
...: groupby=['int_id'], aggregation='mean', reset_index=True)
In [8]: block.produce(X=df)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-8-2f66b517b674> in <module>
----> 1 block.produce(X=df)
...
1147 if not allow_duplicates and item in self.items:
1148 # Should this be a different kind of error??
-> 1149 raise ValueError('cannot insert {}, already exists'.format(item))
1150
1151 if not isinstance(loc, int):
ValueError: cannot insert int_id, already exists
Description
When
pandas.DataFrame.resampleis used grouping by one or more integer columns and also resetting the index, an error arises because the integer columns already exist in the re-sampled dataframe before resetting the index.What I Did