最近需要将csv文件转成DataFrame并以json的形式展示到前台,故需要用到Dataframe的to_json方法
to_json方法默认以列名为键,列内容为值,形成{col1:[v11,v21,v31…],col2:[v12,v22,v32],…}这种格式,但有时我们需要按行来转为json,形如这种格式[row1:{col1:v11,col2:v12,col3:v13…},row2:{col1:v21,col2:v22,col3:v23…}]
通过查找官网我们可以看到to_json方法有一个参数为orient,其参数说明如下:
orient : string
Series
default is ‘index’
allowed values are: {‘split’,’records’,’index’}
DataFrame
default is ‘columns’
allowed values are: {‘split’,’records’,’index’,’columns’,’values’}
The format of the JSON string
split : dict like {index -> [index], columns -> [columns], data -> [values]}
records : list like [{column -> value}, … , {column -> value}]
index : dict like {index -> {column -> value}}
columns : dict like {column -> {index -> value}}
values : just the values array
table : dict like {‘schema’: {schema}, ‘data’: {data}} describing the data, and the data component is like orient=’records’.
Changed in version 0.20.0
大致意思为:
看一下官网给的demo
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='index')
>'[{"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"}]}'
主要参考官网API:https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_json.html