Using pyarrow how do you append to parquet file?

In your case the column name is not consistent, I made the column name consistent for three sample dataframes and the following code worked for me.

# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import pyarrow as pa
import pyarrow.parquet as pq


def append_to_parquet_table(dataframe, filepath=None, writer=None):
    """Method writes/append dataframes in parquet format.

    This method is used to write pandas DataFrame as pyarrow Table in parquet format. If the methods is invoked
    with writer, it appends dataframe to the already written pyarrow table.

    :param dataframe: pd.DataFrame to be written in parquet format.
    :param filepath: target file location for parquet file.
    :param writer: ParquetWriter object to write pyarrow tables in parquet format.
    :return: ParquetWriter object. This can be passed in the subsequenct method calls to append DataFrame
        in the pyarrow Table
    """
    table = pa.Table.from_pandas(dataframe)
    if writer is None:
        writer = pq.ParquetWriter(filepath, table.schema)
    writer.write_table(table=table)
    return writer


if __name__ == '__main__':

    table1 = pd.DataFrame({'one': [-1, np.nan, 2.5], 'two': ['foo', 'bar', 'baz'], 'three': [True, False, True]})
    table2 = pd.DataFrame({'one': [-1, np.nan, 2.5], 'two': ['foo', 'bar', 'baz'], 'three': [True, False, True]})
    table3 = pd.DataFrame({'one': [-1, np.nan, 2.5], 'two': ['foo', 'bar', 'baz'], 'three': [True, False, True]})
    writer = None
    filepath = '/tmp/verify_pyarrow_append.parquet'
    table_list = [table1, table2, table3]

    for table in table_list:
        writer = append_to_parquet_table(table, filepath, writer)

    if writer:
        writer.close()

    df = pd.read_parquet(filepath)
    print(df)

Output:

   one  three  two
0 -1.0   True  foo
1  NaN  False  bar
2  2.5   True  baz
0 -1.0   True  foo
1  NaN  False  bar
2  2.5   True  baz
0 -1.0   True  foo
1  NaN  False  bar
2  2.5   True  baz

I ran into the same issue and I think I was able to solve it using the following:

import pandas as pd
import pyarrow as pa
import pyarrow.parquet as pq


chunksize=10000 # this is the number of lines

pqwriter = None
for i, df in enumerate(pd.read_csv('sample.csv', chunksize=chunksize)):
    table = pa.Table.from_pandas(df)
    # for the first chunk of records
    if i == 0:
        # create a parquet write object giving it an output file
        pqwriter = pq.ParquetWriter('sample.parquet', table.schema)            
    pqwriter.write_table(table)

# close the parquet writer
if pqwriter:
    pqwriter.close()