使用dtype查看dataframe字段类型
print df.dtypes
使用astype实现dataframe字段类型转换
# -*- coding: UTF-8 -*-
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
输出结果:
col1 object
col2 object
dtype: object
-----------
col1 object
col2 int32
dtype: object
-----------
col1 object
col2 float64
dtype: object
注：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)