熊猫的to_datetime函数不会更改dtype

热心学生

我最近一直在使用python，但发现了一个似乎无法解决的问题。我正在使用熊猫数据集，并且当我想使用to_datetime函数将变量的dtype从'object'更改为'datetime64'时，它不会将其更改为所需的'datetime64'dtype。

到目前为止，我只尝试了to_datetime函数，但这似乎无法解决问题。我正在寻找一种解决方案，以使to_datetime起作用或任何其他可以将变量的dtype从'object'更改为'datetime64'的代码

在这里您可以找到有关数据集的信息：

df.head()
Formatted Date                      Summary  Precip Type Temperature (C)   Apparent Temperature (C)   Humidity   Wind Speed (km/h)   Wind Bearing (degrees)  Visibility (km)  Loud Cover Pressure (millibars)   Daily Summary
0   2006-04-01 00:00:00.000 +0200   Partly Cloudy   rain    9.472222    7.388889    0.89    14.1197     251.0   15.8263     0.0     1015.13     Partly cloudy throughout the day.
1   2006-04-01 01:00:00.000 +0200   Partly Cloudy   rain    9.355556    7.227778    0.86    14.2646     259.0   15.8263     0.0     1015.63     Partly cloudy throughout the day.
2   2006-04-01 02:00:00.000 +0200   Mostly Cloudy   rain    9.377778    9.377778    0.89    3.9284  204.0   14.9569     0.0     1015.94     Partly cloudy throughout the day.
3   2006-04-01 03:00:00.000 +0200   Partly Cloudy   rain    8.288889    5.944444    0.83    14.1036     269.0   15.8263     0.0     1016.41     Partly cloudy throughout the day.
4   2006-04-01 04:00:00.000 +0200   Mostly Cloudy   rain    8.755556    6.977778    0.83    11.0446     259.0   15.8263     0.0     1016.51     Partly cloudy throughout the day.

在这里，您可以在使用to_datetime函数之前看到dtypes：

df.dtypes
Formatted Date               object
Summary                      object
Precip Type                  object
Temperature (C)             float64
Apparent Temperature (C)    float64
Humidity                    float64
Wind Speed (km/h)           float64
Wind Bearing (degrees)      float64
Visibility (km)             float64
Loud Cover                  float64
Pressure (millibars)        float64
Daily Summary                object
dtype: object

在使用to_datetime函数之后：

df['Date'] = pd.to_datetime(df['Formatted Date'])
df.dtypes

Formatted Date               object
Summary                      object
Precip Type                  object
Temperature (C)             float64
Apparent Temperature (C)    float64
Humidity                    float64
Wind Speed (km/h)           float64
Wind Bearing (degrees)      float64
Visibility (km)             float64
Loud Cover                  float64
Pressure (millibars)        float64
Daily Summary                object
Date                         object
dtype: object

你能告诉我我在做什么错吗？提前致谢！

矢町

因为pandas>=0.24您需要添加参数utc=True。

import pandas as pd

# load dataset
df = pd.read_csv('weatherHistory.csv')

df['Date'] = df['Formatted Date'].apply(pd.to_datetime, utc=True)

df.dtypes
Formatted Date                           object
Summary                                  object
Precip Type                              object
Temperature (C)                         float64
Apparent Temperature (C)                float64
Humidity                                float64
Wind Speed (km/h)                       float64
Wind Bearing (degrees)                  float64
Visibility (km)                         float64
Loud Cover                              float64
Pressure (millibars)                    float64
Daily Summary                            object
Date                        datetime64[ns, UTC]

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