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python dataframe astype 字段类型转换方法

2018年05月01日  | 移动技术网IT编程  | 我要评论

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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)

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