I would recommend pandasread_xml() and to_csv() function, 3-liner:

Compare the documentation: to_csv, read_xml

import pandas as pd

df = pd.read_xml('employee.xml')
df.to_csv('out.csv', index=False)

Output -> (CSV-file):

id,name,age,salary,division
303,varma,20,120000,3
304,Cyril,20,900000,3
305,Yojith,20,900000,3

Using pandas and BeautifulSoup you can achieve your expected output easily:

#Code:

import pandas as pd
import itertools
from bs4 import BeautifulSoup as b
with open("file.xml", "r") as f: # opening xml file
    content = f.read()

soup = b(content, "lxml")
pkgeid =  [ values.text for values in soup.findAll("pkgeid")]
pkgname = [ values.text for values in soup.findAll("pkgname")]
time =  [ values.text for values in soup.findAll("time")]
oper =  [ values.text for values in soup.findAll("oper")]
# For python-3.x use `zip_longest` method
# For python-2.x use 'izip_longest method
data = [item for item in itertools.zip_longest(time, oper, pkgeid, pkgname)] 
df  = pd.DataFrame(data=data)
df.to_csv("sample.csv",index=False, header=None)

#output in `sample.csv` file will be as follows:
2015-09-16T04:13:20Z,Create_Product,10,BBCWRL
2015-09-16T04:13:20Z,Create_Product,18,CNNINT
2018-04-01T03:30:28Z,Deactivate_Dhct,,

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>