DataFrame.to_json

DataFrame.to_json(path_or_buf=None, orient=None, date_format=None, double_precision=10, force_ascii=True, date_unit=’ms’, default_handler=None, lines=False, compression=’infer’, index=True, indent=None, storage_options=None)
将对象转换为JSON字符串。
NaN和None将被转换为null，datetime对象将被转换为UNIX时间戳。

path_or_buf	文件路径或对象。如果未指定，则返回字符串。
orient	指示预期的字符串格式： - split：`dict like {"index": [index], "column": [columns], "data": [values]}` - records：`dict like [{column: value}, ..., {column: value}]` - index：`dict like {index: {column: value}}` - columns：`dict like {column: {index: value}}` - values：`dict like [[values]]` - table：`dict like {"sechma": {schema}, "data":{data}}`
date_format	日期转换类型。 epoch：毫秒；iso：ISO8601。对于orient=table，默认为iso。其他默认为epoch
double_precision	编码浮点值时使用的小数位数
force_ascii	强制编码字符串为ASCII
date_unit	要编码的时间单位精度：s、ms、us、ns
default_handler	如果对象无法以其他方式转换为适用于JSON的格式时，要调用的处理程序。
lines	如果orient=records，则标识是否写出以行分隔的JSON格式
compression	仅在第一个参数是文件时适用。表示在输出文件中使用的压缩方式：infer、gzip、bz2、zip、xz、None
index	仅适用于orient=split或table时。标识是否在JSON字符串中包含索引值。
indent	用于缩进每条记录的空格长度
storage_options

Example：orient = ‘split’

import pandas as pd
data = pd.DataFrame({'site':['google', 'baidu', 'wiki', 'pandas'],
                    'age':[18, 39, 22, 45],
                    'price': [1.0, 2.0, 3.0, 4.0],
                    'color': ['red', 'black', None, 'red']})
data.to_json(orient='split')

{
    "columns": ["site", "age", "price", "color"],
    "index": [0, 1, 2, 3],
    "data": [
        ["google", 18, 1.0, "red"],
        ["baidu", 39, 2.0, "black"],
        ["wiki", 22, 3.0, null],
        ["pandas", 45, 4.0, "red"]
    ]
}

Example：orient = ‘records’

import pandas as pd
data = pd.DataFrame({'site':['google', 'baidu', 'wiki', 'pandas'],
                    'age':[18, 39, 22, 45],
                    'price': [1.0, 2.0, 3.0, 4.0],
                    'color': ['red', 'black', None, 'red']})
data.to_json(orient='records')

[{
    "site": "google",
    "age": 18,
    "price": 1.0,
    "color": "red"
}, {
    "site": "baidu",
    "age": 39,
    "price": 2.0,
    "color": "black"
}, {
    "site": "wiki",
    "age": 22,
    "price": 3.0,
    "color": null
}, {
    "site": "pandas",
    "age": 45,
    "price": 4.0,
    "color": "red"
}]

Example：orient = ‘index’

import pandas as pd
data = pd.DataFrame({'site':['google', 'baidu', 'wiki', 'pandas'],
                    'age':[18, 39, 22, 45],
                    'price': [1.0, 2.0, 3.0, 4.0],
                    'color': ['red', 'black', None, 'red']})
data.to_json(orient='index')

{
    "0": {
        "site": "google",
        "age": 18,
        "price": 1.0,
        "color": "red"
    },
    "1": {
        "site": "baidu",
        "age": 39,
        "price": 2.0,
        "color": "black"
    },
    "2": {
        "site": "wiki",
        "age": 22,
        "price": 3.0,
        "color": null
    },
    "3": {
        "site": "pandas",
        "age": 45,
        "price": 4.0,
        "color": "red"
    }
}

Example：orient = ‘columns’

import pandas as pd
data = pd.DataFrame({'site':['google', 'baidu', 'wiki', 'pandas'],
                    'age':[18, 39, 22, 45],
                    'price': [1.0, 2.0, 3.0, 4.0],
                    'color': ['red', 'black', None, 'red']})
data.to_json(orient='columns')

{
    "site": {
        "0": "google",
        "1": "baidu",
        "2": "wiki",
        "3": "pandas"
    },
    "age": {
        "0": 18,
        "1": 39,
        "2": 22,
        "3": 45
    },
    "price": {
        "0": 1.0,
        "1": 2.0,
        "2": 3.0,
        "3": 4.0
    },
    "color": {
        "0": "red",
        "1": "black",
        "2": null,
        "3": "red"
    }
}

Example：orient = ‘values’

import pandas as pd
data = pd.DataFrame({'site':['google', 'baidu', 'wiki', 'pandas'],
                    'age':[18, 39, 22, 45],
                    'price': [1.0, 2.0, 3.0, 4.0],
                    'color': ['red', 'black', None, 'red']})
data.to_json(orient='values')

[
    ["google", 18, 1.0, "red"],
    ["baidu", 39, 2.0, "black"],
    ["wiki", 22, 3.0, null],
    ["pandas", 45, 4.0, "red"]
]

Example：orient = ‘table’

import pandas as pd
data = pd.DataFrame({'site':['google', 'baidu', 'wiki', 'pandas'],
                    'age':[18, 39, 22, 45],
                    'price': [1.0, 2.0, 3.0, 4.0],
                    'color': ['red', 'black', None, 'red']})
data.to_json(orient='table')

{
    "schema": {
        "fields": [{
            "name": "index",
            "type": "integer"
        }, {
            "name": "site",
            "type": "string"
        }, {
            "name": "age",
            "type": "integer"
        }, {
            "name": "price",
            "type": "number"
        }, {
            "name": "color",
            "type": "string"
        }],
        "primaryKey": ["index"],
        "pandas_version": "0.20.0"
    },
    "data": [{
        "index": 0,
        "site": "google",
        "age": 18,
        "price": 1.0,
        "color": "red"
    }, {
        "index": 1,
        "site": "baidu",
        "age": 39,
        "price": 2.0,
        "color": "black"
    }, {
        "index": 2,
        "site": "wiki",
        "age": 22,
        "price": 3.0,
        "color": null
    }, {
        "index": 3,
        "site": "pandas",
        "age": 45,
        "price": 4.0,
        "color": "red"
    }]
}