时间戳字符串（Unix时间）到datetime或pandas.Timestamp [英] timestamp string (Unix time) to datetime or pandas.Timestamp

问题描述

从源头我检索一些JSON格式的数据。我想将这些数据（时间的测量）保存为文本文件。反复我想去同一个来源，看看是否有新的测量可用，如果是的话，我想添加到其他测量。

我得到的数据看起来像这样：

  {xyz：[{unixtime：1458255600，time：00:00 day：18/ 03，值：11，paramlabel：30-500 mHz，popupcorr：550，iconnr ：30-500 mHz}，{unixtime：1458256200，时间：00:10，日：18 \ / 03，值：14 ：30-500 mHz，popupcorr：550，iconnr：7，paramname：30-500 mHz}等}} 
  

我将这些数据加载到大熊猫DataFrame中，以便更轻松地使用它。当我将它加载到数据框中时，所有列都将被视为字符串。如何确保unixtime列被视为时间戳（这样可以转换为datetime）？

解决方案

使用 to_datetime ，并通过 unit ='s'将值转换为 dtype to int using astype ：

  df ['unixtime'] = pd.to_datetime（df ['unixtime']。astype（int），unit ='s'）
  

示例：

 在[162]中：
 pd.to_datetime （1458255600，unit ='s'）
 
输出[162]：
时间戳（'2016-03-17 23:00:00'）
  

From a source I retrieve some data in JSON format. I want to save this data (measurements in time) as a text file. Repeatedly I want to go the same source and see if new measurements are available, if so I want to add it to the other measurements.

The data I get looks like this:

{"xyz":[{"unixtime":"1458255600","time":"00:00","day":"18\/03","value":"11","paramlabel":"30-500 mHz","popupcorr":"550","iconnr":"7","paramname":"30-500 mHz"},{"unixtime":"1458256200","time":"00:10","day":"18\/03","value":"14","paramlabel":"30-500 mHz","popupcorr":"550","iconnr":"7","paramname":"30-500 mHz"},etc.]}

I load this data into a pandas DataFrame to be able to work with it more easily. When I load this into a dataframe however, all columns are treated as strings. How can I make sure that the unixtime column is treated as a timestamp (such that I can convert to a datetime)?

解决方案

use to_datetime and pass unit='s' to treat the value as epoch time after converting the dtype to int using astype:

df['unixtime'] = pd.to_datetime(df['unixtime'].astype(int), unit='s')

Example:

In [162]:
pd.to_datetime(1458255600, unit='s')

Out[162]:
Timestamp('2016-03-17 23:00:00')

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