既然有读，必然有写。
可以使用DataFrame的to_csv方法，将数据导出为逗号分隔的文件：
In [57]: result
Out[57]:
one two three four key
0 0.467976 -0.038649 -0.295344 -1.824726 L
1 -0.358893 1.404453 0.704965 -0.200638 B
2 -0.501840 0.659254 -0.421691 -0.057688 G
3 0.204886 1.074134 1.388361 -0.982404 R
4 0.354628 -0.133116 0.283763 -0.837063 Q
In [58]: result.to_csv('d:/out.csv')
当然 ，也可以指定为其它分隔符，甚至将数据输出到sys.stdout中：
In [60]: result.to_csv(sys.stdout, sep='|') |one|two|three|four|key 0|0.467976300189|-0.0386485396255|-0.295344251987|-1.82472622729|L 1|-0.358893469543|1.40445260007|0.704964644926|-0.20063830401500002|B 2|-0.50184039929|0.659253707223|-0.42169061931199997|-0.0576883018364|G 3|0.20488621220199998|1.07413396504|1.38836131252|-0.982404023494|R 4|0.354627914484|-0.13311585229599998|0.283762637978|-0.837062961653|Q
缺失值默认以空字符串出现，当然也可以指定其它标识值对缺失值进行标注，比如使用‘NULL’：
In [70]: data = pd.DataFrame(np.random.randint(9,size=9).reshape(3,3)) In [71]: data Out[71]: 0 1 2 0 7 7 3 1 8 1 5 2 2 4 2 In [72]: data.iloc[2,2] = np.nan In [73]: data.to_csv(sys.stdout, na_rep='NULL') ,0,1,2 0,7,7,3.0 1,8,1,5.0 2,2,4,NULL
在写入的时候，我们还可以禁止将行索引和列索引写入：
In [74]: result.to_csv(sys.stdout, index=False, header=False) 0.467976300189,-0.0386485396255,-0.295344251987,-1.82472622729,L -0.358893469543,1.40445260007,0.704964644926,-0.20063830401500002,B -0.50184039929,0.659253707223,,-0.0576883018364,G 0.20488621220199998,1.07413396504,1.38836131252,-0.982404023494,R 0.354627914484,-0.13311585229599998,0.283762637978,-0.837062961653,Q
也可以挑选需要的列写入：
In [75]: result.to_csv(sys.stdout, index=False, columns=['one','three','key']) one,three,key 0.467976300189,-0.295344251987,L -0.358893469543,0.704964644926,B -0.50184039929,,G 0.20488621220199998,1.38836131252,R 0.354627914484,0.283762637978,Q
Series的写入方式也是一样的：
In [76]: dates = pd.date_range('1/1/2019', periods=7) # 生成一个日期Series
In [77]: dates
Out[77]:
DatetimeIndex(['2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04',
'2019-01-05', '2019-01-06', '2019-01-07'],
dtype='datetime64[ns]', freq='D')
In [78]: ts = pd.Series(np.arange(7), index=dates) # 将日期作为索引
In [79]: ts
Out[79]:
2019-01-01 0
2019-01-02 1
2019-01-03 2
2019-01-04 3
2019-01-05 4
2019-01-06 5
2019-01-07 6
Freq: D, dtype: int32
In [80]: ts.to_csv('d:/tseries.csv') # 写入文件中