python: pandas to

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时间格式参数：（timestamp）

# 单位：秒，格式： ISO8601（大写） df = df.to_json(orient="records", date_format = 'ISO8601', date_unit = 's')

官方文档：

date_format{None, ‘epoch’, ‘iso’}

Type of date conversion. ‘epoch’ = epoch milliseconds, ‘iso’ = ISO8601. The default depends on the orient. For orient='table', the default is ‘iso’. For all other orients, the default is ‘epoch’.

date_unitstr, default ‘ms’ (milliseconds)

The time unit to encode to, governs timestamp and ISO8601 precision. One of ‘s’, ‘ms’, ‘us’, ‘ns’ for second, millisecond, microsecond, and nanosecond respectively.

DataFrame转换为json的格式类型参数：orient

orient : str Indication of expected JSON string format.

Series:

default is ‘index’

allowed values are: {‘split’,’records’,’index’,’table’}.

DataFrame:

default is ‘columns’

allowed values are: {‘split’, ‘records’, ‘index’, ‘columns’, ‘values’, ‘table’}.

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, where data component is like orient='records'.

Changed in version 0.20.0.

For example: import pandas as pd df = pd.DataFrame({'name':['tian','ning'], 'age':[19,20]}) """python name age 0 tian 19 1 ning 20 """ columns df.to_json(orient='columns') # {"name":{"0":"tian","1":"ning"},"age":{"0":19,"1":20}} """ { "name":{ "0":"tian", "1":"ning" }, "age":{ "0":19, "1":20 } } """ table df.to_json(orient='table') # {"schema":{"fields":[{"name":"index","type":"integer"},{"name":"name","type":"string"},{"name":"age","type":"integer"}],"primaryKey":["index"],"pandas_version":"0.20.0"},"data":[{"index":0,"name":"tian","age":19},{"index":1,"name":"ning","age":20}]} """ { "schema":{ "fields":[ { "name":"index", "type":"integer" }, { "name":"name", "type":"string" }, { "name":"age", "type":"integer" } ], "primaryKey":[ "index" ], "pandas_version":"0.20.0" }, "data":[ { "index":0, "name":"tian", "age":19 }, { "index":1, "name":"ning", "age":20 } ] } """ index df.to_json(orient='index') # {"0":{"name":"tian","age":19},"1":{"name":"ning","age":20}} """ { "0":{ "name":"tian", "age":19 }, "1":{ "name":"ning", "age":20 } } """ values df.to_json(orient='values') # [["tian",19],["ning",20]] """ [ [ "tian", 19 ], [ "ning", 20 ] ] """ split df.to_json(orient='split') # {"columns":["name","age"],"index":[0,1],"data":[["tian",19],["ning",20]]} """ { "columns":[ "name", "age" ], "index":[ 0, 1 ], "data":[ [ "tian", 19 ], [ "ning", 20 ] ] } """ records df.to_json(orient='records') # [{"name":"tian","age":19},{"name":"ning","age":20}] """ [ { "name":"tian", "age":19 }, { "name":"ning", "age":20 } ] """

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