基于DataFrame改变列类型的方法
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)
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