python dataframe字段类型转换

最新推荐文章于 2025-06-10 09:18:18 发布

原创最新推荐文章于 2025-06-10 09:18:18 发布 · 2.6k 阅读

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#python #df #dataframe #pd #to_datatime

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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)