date can not be serialized

I am getting an error while trying to save the dataframe as a file.

from fastparquet import write 
write('profile_dtl.parq', df)

The error is related to "date" and the error message looks like this...

ValueError: Can't infer object conversion type: 0    1990-01-01
1    1954-01-01
2    1981-11-15
3    1993-01-21
4    1948-01-01
5    1977-01-01
6    1968-04-28
7    1969-01-01
8    1989-01-01
9    1985-01-01
Name: dob, dtype: object

I have checked that the column is "object" just like any other column that can be serialized without any problem. If I remove the "dob" column from the dataframe, then this line will work. This will also work if there is date+time.

Only dates are not accepted by fast-parquet?

Solution

Try changing dob to datetime64 dtype:

import pandas as pd
dob = pd.Series(['1954-01-01', '1981-11-15', '1993-01-21', '1948-01-01',
                 '1977-01-01', '1968-04-28', '1969-01-01', '1989-01-01',
                 '1985-01-01'], name='dob')
Out:
0    1954-01-01
1    1981-11-15
2    1993-01-21
3    1948-01-01
4    1977-01-01
5    1968-04-28
6    1969-01-01
7    1989-01-01
8    1985-01-01
Name: dob, dtype: object

Note the dtype that results:

pd.to_datetime(dob)

Out:
0   1954-01-01
1   1981-11-15
2   1993-01-21
3   1948-01-01
4   1977-01-01
5   1968-04-28
6   1969-01-01
7   1989-01-01
8   1985-01-01
dtype: datetime64[ns]

Using this Series as an index in a DataFrame:

baz = list(range(9))
foo = pd.DataFrame(baz, index=pd.to_datetime(dob), columns=['dob'])

You should be able to save your Parquet file now.

from fastparquet import write

write('foo.parquet', foo)

$ls -l foo.parquet
-rw-r--r--  1 moi  admin  854 Oct 13 16:44 foo.parquet

Your dob Series has an object dtype and you left unchanged the object_encoding='infer' argument to fastparquet.write. So, from the docs:

"The special value 'infer' will cause the type to be guessed from the first ten non-null values."