json - 如何停止 Pandas Dataframe read_json 方法将我的时代转换为人类可读的字符串

Question

我使用 to_json 方法来序列化我的数据帧，内容如下所示:

"1467065160244362165":"1985.875","1467065161029130301":"1985.875","1467065161481601498":"1985.875","1467065161486508221":"1985.875"

如何停止 read_json 方法将我的纪元值从 1467065160244362165 转换为类似 2016-06-28 06:57:23.786726222 的值。
这就是我调用 read_json 的方式:

data = pd.read_json(remote_result_fullpath, convert_dates=False)

Answer 1

对我来说有效:

import pandas as pd

#added {} to file
remote_result_fullpath = 'https://dl.dropboxusercontent.com/u/84444599/file.json'

data = pd.read_json(remote_result_fullpath, 
                    convert_dates=False, #dont convert columns to dates 
                    convert_axes=False, #dont convert index to dates
                    typ='series') #if need convert output to Series

print (data)
1467065160244362165    1985.875
1467065161029130301    1985.875
1467065161481601498    1985.875
1467065161486508221    1985.875

print (data.dtypes)
dtype: float64
float64

如果需要字符串添加 dtype :

data = pd.read_json(remote_result_fullpath, 
                    convert_dates=False, 
                    convert_axes=False,
                    typ='series',
                    dtype='object')

print (data)
1467065160244362165    1985.875
1467065161029130301    1985.875
1467065161481601498    1985.875
1467065161486508221    1985.875

print (data.dtypes)
dtype: object
object

print (data.index)
Index(['1467065160244362165', '1467065161029130301', '1467065161481601498',
       '1467065161486508221'],
      dtype='object')