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Reproducible Example

import pandas as pd

XML ='''
   <values>
       <guidedSaleKey>
           <code>9023000918982</code>
           <externalReference>0102350511</externalReference>
       </guidedSaleKey>
       <store>
           <code>02300</code>
           <externalReference>1543</externalReference>
           <currency>EUR</currency>
       </store>
   </values>
'''

df = pd.read_xml(XML,iterparse={"values":["code","code"]}, names=["guided_code","store_code"])
print(df)

Issue Description

dataframe will not be able to return value of both code elements from guidedSaleKey and store this will return this:

     guided_code     store_code
0  9023000918982  9023000918982

Expected Behavior

this should return a dataframe like this:

     guided_code     store_code
0  9023000918982  2300

Installed Versions

INSTALLED VERSIONS ------------------ commit : 87cfe4e38bafe7300a6003a1d18bd80f3f77c763 python : 3.10.4.final.0 python-bits : 64 OS : Linux OS-release : 5.4.0-137-generic Version : #154-Ubuntu SMP Thu Jan 5 17:03:22 UTC 2023 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.5.0 numpy : 1.23.4 pytz : 2022.5 dateutil : 2.8.2 setuptools : 58.1.0 pip : 22.0.4 Cython : None pytest : 7.1.3 hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : 4.9.2 html5lib : None pymysql : None psycopg2 : None jinja2 : None IPython : None pandas_datareader: None bs4 : None bottleneck : None brotli : None fastparquet : None fsspec : None gcsfs : None matplotlib : None numba : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : None pyreadstat : None pyxlsb : None s3fs : None scipy : None snappy : sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None xlwt : None zstandard : None tzdata : None

Comment From: bama-chi

there was quite same bug with attributes on this issue

Comment From: ParfaitG

I am not sure this is a bug. Per read_xml docs, the dictionary key in iterparse is intended to be the repeating element which serializes as rows in DataFrame.

Here you are using the root which never repeats in XML. Conceptually, guidedSaleKey and store are two different sets that can repeat in varying numbers. You can run read_xml separately then join DataFrames if their repetition matches.

Comment From: ParfaitG

However, your issue may relate to an iterparse issue regarding same-named elements which I recently observed on this SO post:

from io import BytesIO
import pandas as pd

xml = b'''\
<?xml version="1.0" encoding="UTF-8"?>
<histdata>
   <item>
    <datetime>20-1-2023 00:00:00</datetime>
    <value channel="Traffic Total" chid="-1">92 kbit/s</value>
    <value channel="Traffic In" chid="0">77 kbit/s</value>
    <value channel="Traffic Out" chid="1">16 kbit/s</value>
    <value channel="Downtime" chid="-4">0 %</value>
    <coverage>100 %</coverage>
   </item>
   <item>
    <datetime>20-1-2023 00:05:00</datetime>
    <value channel="Traffic Total" chid="-1">82 kbit/s</value>
    <value channel="Traffic In" chid="0">727 kbit/s</value>
    <value channel="Traffic Out" chid="1">18 kbit/s</value>
    <value channel="Downtime" chid="-4">0 %</value>
    <coverage>100 %</coverage>
   </item>
</histdata>
'''

with BytesIO(xml) as f:            # only latest pandas 2.0 dev supports file-like objects for iterparse
    items_df = pd.read_xml(
        f, 
        iterparse={"item": [
            "datetime", "value", "value", "value", "value", "coverage"
        ]},
        names = [
            "datetime", "value1", "value2",  "value3", "value4",  "coverage"
        ]
    )

items_df
#              datetime     value1     value2     value3     value4 coverage
# 0  20-1-2023 00:00:00  92 kbit/s  92 kbit/s  92 kbit/s  92 kbit/s    100 %
# 1  20-1-2023 00:05:00  82 kbit/s  82 kbit/s  82 kbit/s  82 kbit/s    100 %

As you can see the first <value> element text repeats for all other <value> instances. Interestingly, the repetitious result is not observed when only parsing the repeating attributes suggesting a bug:

with BytesIO(xml) as f:
    attribs_df = pd.read_xml(
        f, 
        iterparse={"item": [
            "datetime",  "channel", "chid", "channel", "chid",  "channel", "chid", "channel", "chid", "coverage"
        ]},
        names = [
            "datetime", "channe11", "chid1",  "channel2", "chid2", "channel3", "chid3", "channel4", "chid4", "coverage"
        ]
    )

attribs_df
#              datetime       channe11  chid1    channel2  chid2     channel3  chid3  channel4  chid4 coverage
# 0  20-1-2023 00:00:00  Traffic Total     -1  Traffic In      0  Traffic Out      1  Downtime     -4    100 %
# 1  20-1-2023 00:05:00  Traffic Total     -1  Traffic In      0  Traffic Out      1  Downtime     -4    100 %