A possible solution is to first load the csv into Pandas and then convert it row by row into XML, as so:
import pandas as pd
df = pd.read_csv('untitled.txt', sep='|')
With the sample data (assuming separator and so on) loaded as:
Title Type Format Year Rating Stars \
0 Enemy Behind War,Thriller DVD 2003 PG 10
1 Transformers Anime,Science Fiction DVD 1989 R 9
Description
0 Talk about...
1 A Schientific fiction
And then converting to xml with a custom function:
def convert_row(row):
return """<movietitle="%s">
<type>%s</type>
<format>%s</format>
<year>%s</year>
<rating>%s</rating>
<stars>%s</stars>
<description>%s</description>
</movie>""" % (
row.Title, row.Type, row.Format, row.Year, row.Rating, row.Stars, row.Description)
print '\n'.join(df.apply(convert_row, axis=1))
This way you get a string containing the xml:
<movietitle="Enemy Behind">
<type>War,Thriller</type>
<format>DVD</format>
<year>2003</year>
<rating>PG</rating>
<stars>10</stars>
<description>Talk about...</description>
</movie>
<movietitle="Transformers">
<type>Anime,Science Fiction</type>
<format>DVD</format>
<year>1989</year>
<rating>R</rating>
<stars>9</stars>
<description>A Schientific fiction</description>
</movie>
that you can dump in to a file or whatever.
Inspired by this great answer.
Edit: Using the loading method you posted (or a version that actually loads the data to a variable):
import csv
f = open('movies2.csv')
csv_f = csv.reader(f)
data = []
for row in csv_f:
data.append(row)
f.close()
print data[1:]
We get:
[['Enemy Behind', 'War', 'Thriller', 'DVD', '2003', 'PG', '10', 'Talk about...'], ['Transformers', 'Anime', 'Science Fiction', 'DVD', '1989', 'R', '9', 'A Schientific fiction']]
And we can convert to XML with minor modifications:
def convert_row(row):
return """<movietitle="%s">
<type>%s</type>
<format>%s</format>
<year>%s</year>
<rating>%s</rating>
<stars>%s</stars>
<description>%s</description>
</movie>""" % (row[0], row[1], row[2], row[3], row[4], row[5], row[6])
print '\n'.join([convert_row(row) for row in data[1:]])
Getting identical results:
<movietitle="Enemy Behind">
<type>War</type>
<format>Thriller</format>
<year>DVD</year>
<rating>2003</rating>
<stars>PG</stars>
<description>10</description>
</movie>
<movietitle="Transformers">
<type>Anime</type>
<format>Science Fiction</format>
<year>DVD</year>
<rating>1989</rating>
<stars>R</stars>
<description>9</description>
</movie>