Dataframe中的數據類型轉換
astype:理解爲 as type
df2['列名'] = df2['列名'].astype(數據類型)
# 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')
最常用就是轉 整形 與 時間 類型
附: 數據類型及描述
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) |