Python Pandas : output dataframe to csv with integers

Question

我有一个希望导出到 CSV 文件的 pandas.DataFrame。但是，pandas 似乎将一些值写为 float 而不是 int 类型。我找不到如何改变这种行为。

构建数据框:

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

查看:

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

导出:

>>> 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

为什么十位都有一个点零？

当然，我可以将这个函数粘贴到我的管道中以重新转换整个 CSV 文件，但这似乎没有必要:

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 1

这是 "gotcha" in pandas (Support for integer NA) ，其中带有 NaN 的整数列被转换为 float 。

This trade-off is made largely for memory and performance reasons, and also so that the resulting Series continues to be “numeric”. One possibility is to use dtype=object arrays instead.