一例tornado框架下利用python panda对数据进行crud操作

 

• get提交部分

<script>
         /* $("#postbtn").click(function () {
              $.ajax({
                  url:'/loaddata',
                  datatype:'json',
                  data:{"filename":$("#excelfile").val()},
                  success:function (data) {
                      console.log(JSON.parse(data))
                  }
              })
          })*/
         $("#postbtn").click(function () {
            $.get('/loaddata',{'filename':$("#excelfile").val()},function (data) {
　　　　　　　　　　//ajax get请求的装逼写法$.get('响应请求的url',请求的数据，回调函数)
                console.log(data)
            },'json')
         })
    </script>

• 相关RequestHandler

class loaddata(RequestHandler):
    def get(self):
        wenwa = self.get_argument('filename')
        client = MongoClient("localhost",27017)
        db = client['olddream'] //选取数据库
        cols = db['bloodtype']//选取集合
        data = DataFrame(list(cols.find()))//读取记录
        print(data)
        rets = data.to_json(orient="records")//把dataframe类型转为json格式数据
        self.write(json.dumps(rets))

•  前端response数据形式（orient=“records”）

[{"_id":0,"bloodtype":"A"},
{"_id":1,"bloodtype":"B"},
{"_id":2,"bloodtype":"AB"},
{"_id":3,"bloodtype":"O"},
{"_id":4,"bloodtype":"RH"}]

• DataFrame类型转为其他格式的方法

split，样式为 {index -> [index], columns -> [columns], data -> [values]}
records，样式为[{column -> value}, … , {column -> value}]
index ，样式为 {index -> {column -> value}}
columns，样式为 {index -> {column -> value}}
values，数组样式
table，样式为{‘schema’: {schema}, ‘data’: {data}}，和records类似

下列部分引自

作者：huanbia 
来源：CSDN 
原文：https://blog.csdn.net/huanbia/article/details/72674832

大致效果

df = pd.DataFrame([['a', 'b'], ['c', 'd']],
index=['row 1', 'row 2'],
columns=['col 1', 'col 2'])
###########
split
###########
df.to_json(orient='split')
>'{"columns":["col 1","col 2"],
"index":["row 1","row 2"],
"data":[["a","b"],["c","d"]]}'
###########
index
###########
df.to_json(orient='index')
>'{"row 1":{"col 1":"a","col 2":"b"},"row 2":{"col 1":"c","col 2":"d"}}'

###########
records
###########
df.to_json(orient='records')
>'[{"col 1":"a","col 2":"b"},{"col 1":"c","col 2":"d"}]'

###########
table
###########
df.to_json(orient='table')
>'{"schema": {"fields": [{"name": "index", "type": "string"},
{"name": "col 1", "type": "string"},
{"name": "col 2", "type": "string"}],
"primaryKey": "index",
"pandas_version": "0.20.0"},
"data": [{"index": "row 1", "col 1": "a", "col 2": "b"},
{"index": "row 2", "col 1": "c", "col 2": "d"}]}'