Parse XML with Python lxml

I am trying to parse a XML using the python library lxml, and would like the resulting output to be in a dataframe. I am relatively new to python and parsing so please bear with me as I outline the problem. The original xml that I am trying to parse is available here

I am interested in obtaining some relevant tags founds in "invstOrSec". Below is a snapshot of one instance of "invstOrSec" where the text accompanying the tag "curCd" is USD.

<?xml version="1.0" encoding="UTF-8"?>
    <invstOrSec>
        <name>NIPPON LIFE INSURANCE</name>
        <lei>549300Y0HHMFW3EVWY08</lei>
        <curCd>USD</curCd>
    <invstOrSec>

This is relatively straightforward, and my current approach involves first defining the relevant tags in a dictionary and then coarse them into a dataframe in a loop.

    import pandas as pd
    from lxml import etree

    # Declare directory
    os.chdir('C:/Users/A1610222/Desktop/Form NPORT/pkg/sec-edgar-filings/0001548717/NPORT-P/0001752724- 
    20-040624')

    # Set root
    xmlfile = "filing-details.xml"
    tree = etree.parse(xmlfile)
    root = tree.getroot()

    # Remove namespace prefixes
    for elem in root.getiterator():
        elem.tag = etree.QName(elem).localname
   
    # Remove unused namespace declarations
    etree.cleanup_namespaces(root)

    # Set path
    invstOrSec = root.xpath('//invstOrSec')

    # Define tags to extract
    vars = {'invstOrSec' : {'name', 'lei', 'curCd'}

    # Extract holdings data
    sec_info =  pd.DataFrame()
    temp = pd.DataFrame()

    for one in invstOrSec:
        for two in one:
            if two.tag in vars['invstOrSec']:
                temp[two.tag] = [two.text]
        sec_info = sec_info.append(temp)  

Here are the top three rows of sec_info

However, the xml follows a slightly different structure when the currency is not USD. See the below example.

<?xml version="1.0" encoding="UTF-8"?>
    <invstOrSec>
        <name>ACHMEA BV</name>
        <lei>7245007QUMI1FHIQV531</lei>
        <currencyConditional curCd="EUR" exchangeRt="0.89150400"/>
    <invstOrSec>

This time curCd is replaced with a different tag currencyConditional and it contains attributes as opposed to the text. I am having a hard time trying to account for these cases while keeping my code as general as possible. I hope I have managed to illustrate the problem. Again, please excuse me if this is too elementary. Any help would be much appreciated.

This is one case where you shouldn't try to reinvent the wheel; use tools developed by others...

import pandas as pd
import pandas_read_xml as pdx

url = 'https://www.sec.gov/Archives/edgar/data/1548717/000175272420040624/primary_doc.xml'

df = pdx.read_xml(url,['edgarSubmission', 'formData', 'invstOrSecs','invstOrSec'])

#because of the non-US currency column, you have to apply one more contortion:
df['currencyConditional'] = df['currencyConditional'].apply(lambda x: x.get('@curCd') if not isinstance(x,float) else "NA" )
df[['name','lei','curCd','currencyConditional']]

Output (partial, obviously) - note the last row:

168     BNP PARIBAS     R0MUWSFPU8MPRO8K5P83    USD     NA
169     Societe Generale    O2RNE8IBXP4R0TD8PU41    USD     NA
170     BARCLAYS PLC    213800LBQA1Y9L22JB70    NaN     GBP