铁雪资源网 Design By www.gsvan.com

今天用numpy 的linalg.det()求矩阵的逆的过程中出现了一个错误:

TypeError: No loop matching the specified signature and casting was found for ufunc det 

查了半天发现是数据类型的问题,numpy在算逆的时候会先检查一下数据类型是否一致,若不一致就会报错(话说这个错误提示信息也太难理解了,还得看源码o(╯□╰)o)。

由于我的数据是用pandas.DataFrame读取的,所以每一列的数据类型有可能不同。

回头检查一下数据,果然有的是int,有的是float。所以全部改为float64类型。

找到了如下的方法,以及DataFrame数据类型:

DataFrame 类型转换方法—astype()

import pandas as pd
df = pd.DataFrame([{'col1':'a', 'col2':'1'}, {'col1':'b', 'col2':'2'}])

print df.dtypes

df['col2'] = df['col2'].astype('int')
print '-----------'
print df.dtypes

df['col2'] = df['col2'].astype('float64')
print '-----------'
print df.dtypes

输出:

col1 object
col2 object
dtype: object
-----------
col1 object
col2  int32
dtype: object
-----------
col1  object
col2 float64
dtype: object

astype()也能一次改变所有数据的类型:

In[30]:a
Out[31]: 
   a   b   c   d
0 0.891380 0.442167 -0.539450 1.023458
1 -0.488131 -1.847104 -0.209799 -0.768713
2 1.290434 0.327096 0.358406 0.422209

In[32]:a.astype('int32')
Out[32]: 
 a b c d
0 0 0 0 1
1 0 -1 0 0
2 1 0 0 0

附:data type list

Data type Description
bool_ Boolean (True or False) stored as a byte
int_ Default integer type (same as C long; normally either int64 or int32)
intc Identical to C int (normally int32 or int64)
intp Integer used for indexing (same as C ssize_t; normally either int32 or int64)
int8 Byte (-128 to 127)
int16 Integer (-32768 to 32767)
int32 Integer (-2147483648 to 2147483647)
int64 Integer (-9223372036854775808 to 9223372036854775807)
uint8 Unsigned integer (0 to 255)
uint16 Unsigned integer (0 to 65535)
uint32 Unsigned integer (0 to 4294967295)
uint64 Unsigned integer (0 to 18446744073709551615)
float_ Shorthand for float64.
float16 Half precision float: sign bit, 5 bits exponent, 10 bits mantissa
float32 Single precision float: sign bit, 8 bits exponent, 23 bits mantissa
float64 Double precision float: sign bit, 11 bits exponent, 52 bits mantissa
complex_ Shorthand for complex128.
complex64 Complex number, represented by two 32-bit floats (real and imaginary components)
complex128 Complex number, represented by two 64-bit floats (real and imaginary components)

以上这篇基于DataFrame改变列类型的方法就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多多支持。

标签:
DataFrame,列类型

铁雪资源网 Design By www.gsvan.com
广告合作:本站广告合作请联系QQ:858582 申请时备注:广告合作(否则不回)
免责声明:本站文章均来自网站采集或用户投稿,网站不提供任何软件下载或自行开发的软件! 如有用户或公司发现本站内容信息存在侵权行为,请邮件告知! 858582#qq.com
铁雪资源网 Design By www.gsvan.com

评论“基于DataFrame改变列类型的方法”

暂无基于DataFrame改变列类型的方法的评论...