[
https://issues.apache.org/jira/browse/ARROW-2429?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Dave Challis updated ARROW-2429:
--------------------------------
Description:
When creating an Arrow table from a Pandas DataFrame, the table schema contains
a field of type `timestamp[ns]`.
When serialising that table to a parquet file and then immediately reading it
back, the schema of the table read instead contains a field with type
`timestamp[us]`.
Minimal example:
{code:python}
#!/usr/bin/env python
import pyarrow as pa
import pyarrow.parquet as pq
import pandas as pd
# create DataFrame with a datetime column
df = pd.DataFrame({'created': ['2018-04-04T10:14:14Z']})
df['created'] = pd.to_datetime(df['created'])
# create Arrow table from DataFrame
table = pa.Table.from_pandas(df, preserve_index=False)
# write the table as a parquet file, then read it back again
pq.write_table(table, 'foo.parquet')
table2 = pq.read_table('foo.parquet')
print(table.schema[0]) # pyarrow.Field<created: timestamp[ns]> (nanosecond
units)
print(table2.schema[0]) # pyarrow.Field<created: timestamp[us]> (microsecond
units)
{code}
was:
When creating an Arrow table from a Pandas DataFrame, the table schema contains
a field of type `timestamp[ns]`.
When serialising that table to a parquet file and then immediately reading it
back, the schema of the table read instead contains a field with type
`timestamp[us]`.
{code:python}
#!/usr/bin/env python
import pyarrow as pa
import pyarrow.parquet as pq
import pandas as pd
# create DataFrame with a datetime column
df = pd.DataFrame({'created': ['2018-04-04T10:14:14Z']})
df['created'] = pd.to_datetime(df['created'])
# create Arrow table from DataFrame
table = pa.Table.from_pandas(df, preserve_index=False)
# write the table as a parquet file, then read it back again
pq.write_table(table, 'foo.parquet')
table2 = pq.read_table('foo.parquet')
print(table.schema[0]) # pyarrow.Field<created: timestamp[ns]> (nanosecond
units)
print(table2.schema[0]) # pyarrow.Field<created: timestamp[us]> (microsecond
units)
{code}
> [Python] Timestamp unit in schema changes when writing to Parquet file then
> reading back
> ----------------------------------------------------------------------------------------
>
> Key: ARROW-2429
> URL: https://issues.apache.org/jira/browse/ARROW-2429
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 0.9.0
> Environment: Mac OS High Sierra
> PyArrow 0.9.0 (py36_1)
> Python
> Reporter: Dave Challis
> Priority: Minor
>
> When creating an Arrow table from a Pandas DataFrame, the table schema
> contains a field of type `timestamp[ns]`.
> When serialising that table to a parquet file and then immediately reading it
> back, the schema of the table read instead contains a field with type
> `timestamp[us]`.
> Minimal example:
>
> {code:python}
> #!/usr/bin/env python
> import pyarrow as pa
> import pyarrow.parquet as pq
> import pandas as pd
> # create DataFrame with a datetime column
> df = pd.DataFrame({'created': ['2018-04-04T10:14:14Z']})
> df['created'] = pd.to_datetime(df['created'])
> # create Arrow table from DataFrame
> table = pa.Table.from_pandas(df, preserve_index=False)
> # write the table as a parquet file, then read it back again
> pq.write_table(table, 'foo.parquet')
> table2 = pq.read_table('foo.parquet')
> print(table.schema[0]) # pyarrow.Field<created: timestamp[ns]> (nanosecond
> units)
> print(table2.schema[0]) # pyarrow.Field<created: timestamp[us]> (microsecond
> units)
> {code}
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
