Convert pandas dataframe to nest XML file in Python

I have a pandas dataframe looks like the following:

df2 = pd.DataFrame(np.array([['A', '2023-10-17', 'C', 4, 1, 1, 1.5], 
                             ['A', '2023-10-17', 'C', 5, 1, 5, 2.4],
                             ['A', '2023-10-17', 'D', 16, 1, 2, 2.3],
                             ['B', '2023-10-17', 'C', 4, 1, 1, 1.5], 
                             ['B', '2023-10-17', 'D', 5, 1, 5, 2.4],
                             ['B', '2023-10-17', 'D', 5, 2, 2, 3.3],]),
                   columns=['Item', 'Day', 'Type', 'Hour', 'SegmentID', 'quant', 'cost'])
df2

enter image description here

and I would like to convert it to a XML like this:

<ItemRecord Item="A" Day="2023-10-17">
    <C>
        <ItemRecordHourly hour="4">
            <Segment id="1">
                <quant>1</quant>
                <cost>1.5</cost>
            </BidSegment>
        </ItemRecordHourly>
        <ItemRecordHourly hour="5">
            <Segment id="1">
                <quant>5</quant>
                <cost>2.4</cost>
            </BidSegment>
        </ItemRecordHourly>
    </C>
    <D>
        <ItemRecordHourly hour="16">
            <Segment id="1">
                <quant>2</quant>
                <cost>2.3</cost>
            </BidSegment>
        </ItemRecordHourly>
    </D>
</ItemRecord>    
<ItemRecord Item="B" Day="2023-10-17">
    <C>
        <ItemRecordHourly hour="4">
            <Segment id="1">
                <quant>1</quant>
                <cost>1.5</cost>
            </BidSegment>
        </ItemRecordHourly>
    </C>
    <D>
        <ItemRecordHourly hour="5">
            <Segment id="1">
                <quant>5</quant>
                <cost>2.4</cost>
            </BidSegment>
            <Segment id="2">
                <quant>2</quant>
                <cost>3.3</cost>
            </BidSegment>
        </ItemRecordHourly>
    </D>
</ItemRecord> 

I tried to use xml.etree.ElementTree and pd.to_xml() but I could not get it converting the data correctly. Any suggestions would be very helpful! Thanks in advance!

Thanks @mcjeb! Here is the working solution:

grouped = df2.groupby(['Item', 'Day'])

import xml.etree.ElementTree as ET
# Create the root element of the XML
root = ET.Element("Data")
# Iterate through the grouped data and construct the XML structure
for (item, day), group in grouped:
    item_record = ET.SubElement(root, "ItemRecord", Item=item, Day=day)
    
    types = group['Type'].unique()
    for item_type in types:
        item_type_element = ET.SubElement(item_record, item_type)
        type_group = group[group['Type'] == item_type]
        for _, row in type_group.iterrows():
            item_hourly = ET.SubElement(item_type_element, "ItemRecordHourly", hour=str(row['Hour']))
            # segment tags
            segment = ET.SubElement(item_hourly, "Segment", id=str(row['SegmentID']))
            # quant tags
            quant = ET.SubElement(segment, "quant")
            quant.text=str(row["quant"]) 
            # cost tags
            cost = ET.SubElement(segment, "cost")
            cost .text=str(row["cost "])
tree = ET.ElementTree(root)