read_csv fails with `TypeError: object cannot be converted to an IntegerDtype` yet succeeds when reading chunks

Code Sample, a copy-pastable example if possible

Download this file upload.txt

# Your code here
import pandas as pd
from enum import Enum, IntEnum, auto
import argparse

# I attached the file in the github issue
filename = "upload.txt"
# this field is coded on 64 bits so 'UInt64' looks perfect.
column = "tcp.options.mptcp.sendkey"

with open(filename) as fd:

    print("READ CHUNK BY CHUNK")

    res = pd.read_csv(
            fd,
            comment='#',
            sep='|',
            dtype={column: 'UInt64' },
            usecols=[column],
            chunksize=1
    )
    for chunk in (res):
        # print("chunk %d" % i)
        print(chunk)



    fd.seek(0) # rewind

    print("READ THE WHOLE FILE AT ONCE ")
    res = pd.read_csv(
            fd,
            comment='#',
            sep='|',
            usecols=[column],
            dtype={"tcp.options.mptcp.sendkey": 'UInt64' }
    )
    print(res)

If I read in chunks, read_csv succeeds, if I try to read the column at once, I get

Traceback (most recent call last):
  File "test2.py", line 34, in <module>
    dtype={"tcp.options.mptcp.sendkey": 'UInt64' }
  File "/nix/store/mhiszrb8cpicjkzgraq796asj2sxpjch-python3.7-pandas-0.24.1/lib/python3.7/site-packages/pandas/io/parsers.py", line 702, in parser_f
    return _read(filepath_or_buffer, kwds)
  File "/nix/store/mhiszrb8cpicjkzgraq796asj2sxpjch-python3.7-pandas-0.24.1/lib/python3.7/site-packages/pandas/io/parsers.py", line 435, in _read
    data = parser.read(nrows)
  File "/nix/store/mhiszrb8cpicjkzgraq796asj2sxpjch-python3.7-pandas-0.24.1/lib/python3.7/site-packages/pandas/io/parsers.py", line 1139, in read
    ret = self._engine.read(nrows)
  File "/nix/store/mhiszrb8cpicjkzgraq796asj2sxpjch-python3.7-pandas-0.24.1/lib/python3.7/site-packages/pandas/io/parsers.py", line 1995, in read
    data = self._reader.read(nrows)
  File "pandas/_libs/parsers.pyx", line 900, in pandas._libs.parsers.TextReader.read
  File "pandas/_libs/parsers.pyx", line 915, in pandas._libs.parsers.TextReader._read_low_memory
  File "pandas/_libs/parsers.pyx", line 992, in pandas._libs.parsers.TextReader._read_rows
  File "pandas/_libs/parsers.pyx", line 1124, in pandas._libs.parsers.TextReader._convert_column_data
  File "pandas/_libs/parsers.pyx", line 1155, in pandas._libs.parsers.TextReader._convert_tokens
  File "pandas/_libs/parsers.pyx", line 1235, in pandas._libs.parsers.TextReader._convert_with_dtype
  File "/nix/store/mhiszrb8cpicjkzgraq796asj2sxpjch-python3.7-pandas-0.24.1/lib/python3.7/site-packages/pandas/core/arrays/integer.py", line 308, in _from_sequence_of_strings
    return cls._from_sequence(scalars, dtype, copy)
  File "/nix/store/mhiszrb8cpicjkzgraq796asj2sxpjch-python3.7-pandas-0.24.1/lib/python3.7/site-packages/pandas/core/arrays/integer.py", line 303, in _from_sequence
    return integer_array(scalars, dtype=dtype, copy=copy)
  File "/nix/store/mhiszrb8cpicjkzgraq796asj2sxpjch-python3.7-pandas-0.24.1/lib/python3.7/site-packages/pandas/core/arrays/integer.py", line 111, in integer_array
    values, mask = coerce_to_array(values, dtype=dtype, copy=copy)
  File "/nix/store/mhiszrb8cpicjkzgraq796asj2sxpjch-python3.7-pandas-0.24.1/lib/python3.7/site-packages/pandas/core/arrays/integer.py", line 188, in coerce_to_array
    values.dtype))
TypeError: object cannot be converted to an IntegerDtype

Expected Output

I would like the call to read_csv to succeed without having to read in chunks (which seems to have other side effects as well).

Output of pd.show_versions()

I am using v0.23.4 with a patch from master to fix some other bug. [paste the output of ``pd.show_versions()`` here below this line] commit: None python: 3.7.2.final.0 python-bits: 64 OS: Linux OS-release: 4.19.0 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: fr_FR.UTF-8 LOCALE: fr_FR.UTF-8

pandas: 0+unknown pytest: None pip: 18.1 setuptools: 40.6.3 Cython: None numpy: 1.16.0 scipy: 1.2.0 pyarrow: None xarray: None IPython: None sphinx: None patsy: None dateutil: 2.7.5 pytz: 2018.7 blosc: None bottleneck: 1.2.1 tables: 3.4.4 numexpr: 2.6.9 feather: None matplotlib: 3.0.2 openpyxl: 2.5.12 xlrd: 1.1.0 xlwt: 1.3.0 xlsxwriter: None lxml.etree: 4.2.6 bs4: 4.6.3 html5lib: 1.0.1 sqlalchemy: 1.2.14 pymysql: None psycopg2: None jinja2: None s3fs: None fastparquet: None pandas_gbq: None pandas_datareader: None gcsfs: None

[NumesSanguis]

Sorry that I have no time to properly debug this, but I hope I can contribute a little bit of knowledge.

I’m running into the same problem as OP when I read 1 of the sheets of a .xlsl file (pandas 0.24.2). There are NaN values, but from pandas 0.24 that should work when doing .astype(pd.Int16Dtype()) right?

This gave the same problem as OP:

df_sheet.age = df_sheet.age.astype(pd.Int16Dtype())

However, ugly, but this seemed to have worked for me:

df_sheet.age = df_sheet.age.astype('float')  # first convert to float before int
df_sheet.age = df_sheet.age.astype(pd.Int16Dtype())

[jreback]

@alexreg you or anyone is welcome to submit a PR to patch and the core team can review