Python Pandas插入长整数 [英] Python pandas insert long integer

问题描述

我正在尝试在Pandas Dataframe中插入长整数

I'm trying to insert long integers in a Pandas Dataframe

import numpy as np
from pandas import DataFrame

data_scores = [(6311132704823138710, 273), (2685045978526272070, 23), (8921811264899370420, 45), (17019687244989530680L, 270), (9930107427299601010L, 273)]
dtype = [('uid', 'u8'), ('score', 'u8')]
data = np.zeros((len(data_scores),),dtype=dtype)
data[:] = data_scores
df_crawls = DataFrame(data)
print df_crawls.head()

但是当我查看数据框时，长的最后一个值现在是负数:

But when I look in the dataframe, last values which are long are now negative :

                       uid  score
0  6311132704823138710    273
1  2685045978526272070     23
2  8921811264899370420     45
3 -1427056828720020936    270
4 -8516636646409950606    273

uid是64位unsigned int，因此'u8'应该是正确的dtype?有什么想法吗?

uids are 64 bits unsigned int, so 'u8' should be the correct dtype ? Any ideas ?

推荐答案

是的-这是目前对熊猫的限制-我们确实计划在将来增加对无符号整数dtypes的支持.错误消息会更好:

Yes-- it's a present limitation of pandas-- we do plan to add support for unsigned integer dtypes in the future. An error message would be much better:

http://github.com/pydata/pandas/issues/2355

现在，您可以将列dtype=object设为解决方法.

For now you can make the column dtype=object as a workaround.

编辑2012-11-27

EDIT 2012-11-27

现在检测溢出，不过直到DataFrame更好地支持无符号数据类型之前，该检测现在将变为dtype = object.

Detecting overflows now, though will become dtype=object for now until DataFrame has better support for unsigned data types.

In [3]: df_crawls
Out[3]: 
                    uid  score
0   6311132704823138710    273
1   2685045978526272070     23
2   8921811264899370420     45
3  17019687244989530680    270
4   9930107427299601010    273

In [4]: df_crawls.dtypes
Out[4]: 
uid      object
score     int64

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