python dataframe字段类型转换

本文详细介绍了如何在Pandas DataFrame中进行数据类型转换,包括使用astype方法转换为整型、浮点型等基本类型,以及利用pd.to_datetime将字符串转换为日期时间格式。文章还列举了各种数据类型及其描述,帮助读者更好地理解和应用。

 

Dataframe中的数据类型转换

astype:理解为 as  type


df2['列名'] = df2['列名'].astype(数据类型)

# 拓展
df['date_time'] = pd.to_datetime(df['date_time'])
df['date_time'] = pd.to_datetime(df[column_name], format='%d/%m/%y %H:%M')

最常用就是转 整形 与 时间 类型

附: 数据类型及描述

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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