Python pandas: output dataframe to csv with integers

I have a pandas.DataFrame that I wish to export to a CSV file. However, pandas seems to write some of the values as float instead of int types. I couldn’t not find how to change this behavior.

Building a data frame:

df = pandas.DataFrame(columns=['a','b','c','d'], index=['x','y','z'], dtype=int)
x = pandas.Series([10,10,10], index=['a','b','d'], dtype=int)
y = pandas.Series([1,5,2,3], index=['a','b','c','d'], dtype=int)
z = pandas.Series([1,2,3,4], index=['a','b','c','d'], dtype=int)
df.loc['x']=x; df.loc['y']=y; df.loc['z']=z

View it:

>>> df
    a   b    c   d
x  10  10  NaN  10
y   1   5    2   3
z   1   2    3   4

Export it:

>>> df.to_csv('test.csv', sep='t', na_rep='0', dtype=int)
>>> for l in open('test.csv'): print l.strip('n')
        a       b       c       d
x       10.0    10.0    0       10.0
y       1       5       2       3
z       1       2       3       4

Why do the tens have a dot zero ?

Sure, I could just stick this function into my pipeline to reconvert the whole CSV file, but it seems unnecessary:

def lines_as_integer(path):
    handle = open(path)
    yield handle.next()
    for line in handle:
        line = line.split()
        label = line[0]
        values = map(float, line[1:])
        values = map(int, values)
        yield label + 't' + 't'.join(map(str,values)) + 'n'
handle = open(path_table_int, 'w')
handle.writelines(lines_as_integer(path_table_float))
handle.close()

Answer

The answer I was looking for was a slight variation of what @Jeff proposed in his answer. The credit goes to him. This is what solved my problem in the end for reference:

    import pandas
    df = pandas.DataFrame(data, columns=['a','b','c','d'], index=['x','y','z'])
    df = df.fillna(0)
    df = df.astype(int)
    df.to_csv('test.csv', sep='t')

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