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https://issues.apache.org/jira/browse/ARROW-7628?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17038455#comment-17038455
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Antoine Pitrou commented on ARROW-7628:
---------------------------------------

So I don't think there is an Arrow bug here. However, perhaps we can try to 
make these things easier to find out. cc [~npr]  any thoughts?

> [Python] read_csv problematic cases
> -----------------------------------
>
>                 Key: ARROW-7628
>                 URL: https://issues.apache.org/jira/browse/ARROW-7628
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: Python
>    Affects Versions: 0.15.1
>         Environment: Ubuntu bionic
>            Reporter: Athanassios Hatzis
>            Priority: Minor
>              Labels: csv, pyarrow
>         Attachments: spc_catalog.tsv
>
>
> Hi, I have found two problematic cases, possibly bugs, in pyarrow *read_csv* 
> module. I have written the following piece of code and run a test on the 
> attached CSV file. 
> The code compares pandas read_csv with pyarrow csv to show that the second is 
> not behaving correctly with the following set of parameters:
> 1. change parameter skip_rows = 10, 
> {code:python}
> Traceback (most recent call last):
>   File 
> "/home/athan/anaconda3/envs/TRIADB/lib/python3.7/site-packages/IPython/core/interactiveshell.py",
>  line 3326, in run_code
>     exec(code_obj, self.user_global_ns, self.user_ns)
>   File "<ipython-input-21-8c5c88b190c4>", line 4, in <module>
>     read_options=csv.ReadOptions(skip_rows=skip_rows, 
> autogenerate_column_names=False, use_threads=True, column_names=column_names)
>   File "pyarrow/_csv.pyx", line 541, in pyarrow._csv.read_csv
>   File "pyarrow/error.pxi", line 84, in pyarrow.lib.check_status
> pyarrow.lib.ArrowKeyError: Column 'catcost' in include_columns does not exist 
> in CSV file
> {code}
> 2. change parameters skip_rows = 12, columns = None
> In this case you don't get the error above, all columns are fetched, but 
> compare the two dataframes, the one from pyarrow with to_pandas() and the one 
> from the output of pandas read_csv(). You will notice that the first one has 
> not parsed correctly the null values ('\\N') in the last column catname. On 
> the contrary pandas read_csv managed to parse all the null values correctly.
> {code:python}
> Out[28]: 
>    1082  991   16.5    200 2014-09-10  1  bar
> 0  1082  997   0.55  100.0 2014-09-10  1  bar
> 1  1082  998   7.95  200.0 2014-03-03  0   \N
> 2  1083  998  12.50    NaN        NaT  0  bar
> 3  1083  999   1.00    NaN        NaT  0  foo
> 4  1084  994  57.30  100.0 2014-12-20  1   \N
> 5  1084  995  22.20    NaN        NaT  0  foo
> 6  1084  998  48.60  200.0 2014-12-20  1  foo
> {code}
> Python code to test the attached CSV file for the bugs reported above
> {code:python}
> from pyarrow import csv
> import pyarrow as pa
> import pandas as pd
> file_location = 'spc_catalog.tsv'
> sep = '\t'
> nulls=['\\N']
> columns = ['catcost', 'catqnt', 'catdate', 'catchk', 'catname']
> column_names = None
> column_types = None
> skip_rows = None
> nrecords = None
> csv.read_csv(file_location,
>     parse_options=csv.ParseOptions(delimiter=sep),
>     convert_options=csv.ConvertOptions(include_columns=columns, 
> column_types=column_types, null_values=nulls),
>     read_options=csv.ReadOptions(skip_rows=skip_rows, 
> autogenerate_column_names=False, use_threads=True, column_names=column_names)
> ).to_pandas()
> pd.read_csv(file_location, sep=sep, na_values='\\N', usecols=columns, 
> nrows=nrecords, names=column_names, dtype=column_types)
> {code}



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