DataFrame改变列类型

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)