ARROW-2689: [Python] Remove parameter timestamps_to_ms

[xhochy]

This parameter is no longer existent. For the Parquet path it was replaced by coerce_timestamps, other cases should use Column.cast().

[codecov-io]

Codecov Report

Merging #2129 into master will decrease coverage by 0.02%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master    #2129      +/-   ##
==========================================
- Coverage   86.39%   86.37%   -0.03%     
==========================================
  Files         242      230      -12     
  Lines       41481    40589     -892     
==========================================
- Hits        35838    35059     -779     
+ Misses       5643     5530     -113

Impacted Files	Coverage Δ
rust/src/list.rs
rust/src/error.rs
rust/src/array.rs
rust/src/builder.rs
rust/src/memory.rs
rust/src/list_builder.rs
rust/src/datatypes.rs
rust/src/bitmap.rs
rust/src/record_batch.rs
rust/src/memory_pool.rs
... and 2 more

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[domoritz]

So we should run https://arrow.apache.org/docs/python/generated/pyarrow.Column.html#pyarrow.Column.cast after converting a data frame to arrow. 👍

[wesm]

@domoritz could you elaborate on your use case a bit more?

[wesm]

+1

[domoritz]

I'm trying to convert some data from pandas to arrow but pandas' timestamps are in ns. I want to reduce the data size and use lower precision.

My code looks roughly like this:

df = pd.read_csv('flights.csv', encoding='utf-8', dtype={'FL_DATE': 'str', 'ARR_TIME': 'str', 'DEP_TIME': 'str'})

arr_time = df.FL_DATE + df.ARR_TIME.replace('2400', '0000')
data['ARRIVAL'] = pd.to_datetime(arr_time, format='%Y%m%d%H%M')

dep_time = df.FL_DATE + df.DEP_TIME.replace('2400', '0000')
data['DEPARTURE'] = pd.to_datetime(dep_time, format='%Y%m%d%H%M')

df = df.astype({'DEP_DELAY': 'int16', 'ARR_DELAY': 'int16', 'AIR_TIME': 'int16', 'DISTANCE': 'int16'})

table = pa.Table.from_pandas(df)

table.column('ARRIVAL').cast(pa.TimestampValue, True)

writer = pa.RecordBatchFileWriter(f'{name}.arrow', table.schema)
writer.write(table)
writer.close()

[wesm]

Okay. In this line:

table.column('ARRIVAL').cast(pa.TimestampValue, True)

Are you trying to cast that column a different timestamp unit? This line of code leaves table unmodified (data structures from the pyarrow library are immutable). All timestamps use the same amount of space (8 bytes per value)

It would be a good idea to add a documentation section about type casting and how to change the column type of a table; I don't think we have that right now. We could also add some convenience APIs to help with common workflows (e.g. replacing a single column)

[domoritz]

Are you trying to cast that column a different timestamp unit?

Yes, I am trying to switch to ns to ms accuracy.

I guess I have to write something like table = table.column('ARRIVAL').cast(pa.TimestampValue, True) instead. Or does this return a column and so I need table.setColumn('ARRIVAL', table.column('ARRIVAL').cast(pa.TimestampValue, True))?

[wesm]

Okay, let's create a JIRA about this and discuss there.

Firstly, the statement cast(pa.TimestampValue, True) will not do what you want. You either want

column.cast(pa.timestamp('ms'))

or

column.cast(pa.timestamp('ms'), safe=False)

depending on whether you want to allow unsafe casts (see http://arrow.apache.org/docs/python/generated/pyarrow.lib.Array.html#pyarrow.lib.Array.cast). I think the docstring could be improved to make more clear that a DataType instance is expected rather than a class object.

Secondly, we don't have a convenient function for replacing a column in a table to create a new table. So I would want to write:

new_column = table.column(name).cast(pa.timestamp('ms'))
new_table = table.set_column(name, new_column)

I opened https://issues.apache.org/jira/browse/ARROW-2699

[wesm]

See also https://issues.apache.org/jira/browse/ARROW-2700

[domoritz]

Thank you @wesm! I hope my comments are helpful.