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2016-06-28 06:57:23.786726222
之类的内容。
这就是我调用read_json的方式:
data = pd.read_json(remote_result_fullpath, convert_dates=False)
答案 0 :(得分:4)
对我而言:
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')