Python处理Json数据

作者：--    发布时间：2019-11-20

json文件以可读的格式将数据存储为文本。 json代表javascript object notation。 使用read_json函数，pandas可以读取json文件。

输入数据

通过将以下数据复制到文本编辑器(如记事本)来创建json文件。选择文件类型作为所有文件(.)，使用.json扩展名保存文件，假设保存的文件名称为:input.json。

{ 
   "id":["1","2","3","4","5","6","7","8" ],
   "name":["rick","dan","michelle","ryan","gary","nina","simon","guru" ]
   "salary":["623.3","515.2","611","729","843.25","578","632.8","722.5" ],

   "startdate":[ "1/1/2012","9/23/2013","11/15/2014","5/11/2014","3/27/2015","5/21/2013",
      "7/30/2013","6/17/2014"],
   "dept":[ "it","operations","it","hr","finance","it","operations","finance"]
}

读取json文件

pandas库的read_json函数可用于将json文件读入为pandas dataframe数据结构类型。

import pandas as pd

data = pd.read_json('path/input.json')
print (data)

当我们执行上面的代码时，它会产生以下结果。

         dept  id    name  salary   startdate
0          it   1    rick  623.30    1/1/2012
1  operations   2     dan  515.20   9/23/2013
2          it   3   tusar  611.00  11/15/2014
3          hr   4    ryan  729.00   5/11/2014
4     finance   5    gary  843.25   3/27/2015
5          it   6   rasmi  578.00   5/21/2013
6  operations   7  pranab  632.80   7/30/2013
7     finance   8    guru  722.50   6/17/2014

读取特定的列和行

与在前一章中已经看到的读取csv文件类似，读取json文件到dataframe后，pandas库的read_json函数也可用于读取一些特定列和特定行。 使用.loc()的多轴索引方法。选择显示salary和name列的某些行。

import pandas as pd
data = pd.read_json('path/input.xlsx')

# use the multi-axes indexing funtion
print (data.loc[[1,3,5],['salary','name']])

当我们执行上面的代码时，它会产生以下结果。

   salary   name
1   515.2    dan
3   729.0   ryan
5   578.0  rasmi

将json文件作为记录读取

还可以将to_json函数与参数一起应用于将json文件内容读入单个记录。

import pandas as pd
data = pd.read_json('path/input.xlsx')

print(data.to_json(orient='records', lines=true))

执行上面示例代码，得到以下结果 -

{"dept":"it","id":1,"name":"rick","salary":623.3,"startdate":"1\/1\/2012"}
{"dept":"operations","id":2,"name":"dan","salary":515.2,"startdate":"9\/23\/2013"}
{"dept":"it","id":3,"name":"tusar","salary":611.0,"startdate":"11\/15\/2014"}
{"dept":"hr","id":4,"name":"ryan","salary":729.0,"startdate":"5\/11\/2014"}
{"dept":"finance","id":5,"name":"gary","salary":843.25,"startdate":"3\/27\/2015"}
{"dept":"it","id":6,"name":"rasmi","salary":578.0,"startdate":"5\/21\/2013"}
{"dept":"operations","id":7,"name":"pranab","salary":632.8,"startdate":"7\/30\/2013"}
{"dept":"finance","id":8,"name":"guru","salary":722.5,"startdate":"6\/17\/2014"}