Forshining opened a new issue, #44059:
URL: https://github.com/apache/arrow/issues/44059
### Describe the usage question you have. Please include as many useful
details as possible.
My question description is as follows:
I have a parquet file that has already contains the __index_level_0__
colomn. Now I try to delete some of the rows that are unmatched to some
criterion and turn the updated dataframe into another new parquet file. The
code is as follows:
```python
import pyarrow.parquet as pq
import pyarrow as pa
import pandas as pd
import os
## select the images with aesthetic score >= 5
for m in range(100,128):
# table_temp =
pq.ParquetFile('part-00000-4e217ab5-40f3-4738-ac05-c1cb9f75ef32-c000.snappy.parquet')
# column_names = table_temp.schema.names
# print("Column names:", column_names)
read_file =
f'part-00{m}-4e217ab5-40f3-4738-ac05-c1cb9f75ef32-c000.snappy.parquet'
table_temp_pandas = pq.read_table(read_file).to_pandas()
index_to_be_deleted = []
for i in range(table_temp_pandas.shape[0]):
if table_temp_pandas.loc[i, 'AESTHETIC_SCORE'] < 5:
index_to_be_deleted.append(i)
table_dropped =
table_temp_pandas.drop(table_temp_pandas.index[index_to_be_deleted])
split_string = read_file.split("-")
write_file = "new-part-" + split_string[1] + ".parquet"
table_dropped_p = pa.Table.from_pandas(table_dropped,
preserve_index=False)
print(f"Writing new table into parquet......:{m+1}/127")
pq.write_table(table_dropped_p, write_file)
print("Completed")
print(f"Staring to remove the former parquet file:
part-00{m}-4e217ab5-40f3-4738-ac05-c1cb9f75ef32-c000.snappy.parquet")
os.remove(f"part-00{m}-4e217ab5-40f3-4738-ac05-c1cb9f75ef32-c000.snappy.parquet")
print("File removed successfully!")
```
However, when I tried to read the new parquet files with the following codes:
```python
read_file = "./datasets--laion--aesthetics_v2_4.75/new-part-00000.parquet"
table_temp_pandas = pq.read_table(read_file).to_pandas()
```
here comes an error:
```bash
pyarrow.lib.ArrowInvalid: Multiple matches for
FieldRef.Name(__index_level_0__)
```
After I check the new dataframe, I found that there are two same colomns of
__index_level_0__, one from the original parquet file and another from
write_file() operations.
However, my situation is that I do not have so much storage to
simultaneously store the original and new parquet files. Therefore, is there
any solution to directly delete one of the __index_level_0__ colomns only based
on the new parquet files?
I would appreciate anyone's precious time and help!
### Component(s)
Parquet, Python
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