The student question came into class regarding column headers in pandas.

His specific question came about because he was adding column headers to his code, but they were being coerced into strings.

df=pd.DataFrame(index=['x','y'], data={'a':[1,2],'b':[3,4]})
will produce
   c1  c2
x  1   a
x  3   b
y  2   a
y  4   b


To convert column names into values:
Unstack
print (df.T.unstack().reset_index(level=1, name='c1')
                     .rename(columns={'level_1':'c2'})[['c1','c2']])
   c1 c2
x   1  a
x   3  b
y   2  a
y   4  b
================
Or:
Stack
print (df.stack().reset_index(level=1, name='c1')
                 .rename(columns={'level_1':'c2'})[['c1','c2']])
   c1 c2
x   1  a
x   3  b
y   2  a
y   4  b
===============
OR
Melting:

 (pd.melt(df.reset_index(), var_name='c2', value_name='c1', id_vars='index')
          .set_index('index'))

      c2  c1
index       
x      a   1
y      a   2
x      b   3
y      b   4
================
EVEN: HTML!!!
(add this to code above to bring in the df object)

from IPython.display import display, HTML

display(HTML(df.to_html()))
==============
 Tabulate
***Tablulate is a python download package.  Get it here:

https://pypi.org/project/tabulate/

Info on installing packages into Jupyter:
https://jakevdp.github.io/blog/2017/12/05/installing-python-packages-from-jupyter/



Code to use tabulate:

from tabulate import tabulate
import pandas as pd

df = pd.DataFrame({'col_two' : [0.0001, 1e-005 , 1e-006, 1e-007],
                   'column_3' : ['ABCD', 'ABCD', 'long string', 'ABCD']})
print(tabulate(df, headers='keys', tablefmt='psql'))
=====================
LASTLY: Use import csv method?

import csv
import os

inputFileName = "test.csv"
outputFileName = os.path.splitext(inputFileName)[0] + "_modified.csv"

headersDict = {'NUMBER, SEX AND AGE - Total Population - Under 5 years': 'TPop00_05',
               'NUMBER, SEX AND AGE - Total Population - 5 to 9 years': 'TPop05_09',
               'NUMBER, SEX AND AGE - Total Population - 10 to 14 years': 'TPop10_14',
               'NUMBER, SEX AND AGE - Total Population - 15 to 19 years': 'TPop15_19',
               'NUMBER, SEX AND AGE - Total Population - 20 to 24 years': 'TPop20_24',
               'NUMBER, SEX AND AGE - Total Population - 25 to 29 years': 'TPop25_29'
               }

with open(inputFileName, 'rb') as inFile, open(outputFileName, 'wb') as outfile:
    r = csv.reader(inFile)
    w = csv.writer(outfile)

    # read the first row from the reader, the old header
    header = next(r)
    print header

    # replace items in header using dictionary, if item not in dictionary, it will not be replaced
    newHeader = [ headersDict.get(item,item) for item in header ]
    print newHeader
    
    # write new header
    w.writerow(newHeader)

    # copy the rest
    for row in r:
        w.writerow(row)
=======================
Final Thought:

****A great example of displaying.  
https://github.com/ShikhaChm/Python_HeroesOfPymoli