python 数据分析 pandas转json去掉index索引

DataFrame转成json，可以使用df.to_json()方法

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

print(df.to_json())

# {"name":{"0":"mashiro","1":"satori","2":"koishi","3":"nagisa"},"age":{"0":17,"1":17,"2":16,"3":21}}

我们看到虽然转化成了json，但是有些不完美，那就是它把索引也算进去了

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

# 如果不想加索引的话，那么指定index=False即可

try:

print(df.to_json(index=False))

except Exception as e:

print(e) # 'index=False' is only valid when 'orient' is 'split' or 'table'

# 但是它报错了，说如果index=False，那么orient必须指定我split或者table

我们看一下这个orient是什么

首先orient可以有如下取值：split、records、index、columns、values、table

我们分别演示一下，看看orient取不同的值，结果会有什么变化

orient='split'

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

print(df.to_json(orient="split"))

"""

{

"columns":["name","age"],

"index":[0,1,2,3],

"data":[["mashiro",17],["satori",17],["koishi",16],["nagisa",21]]

}

"""

print(df.to_json(orient="split", index=False))

"""

{

"columns":["name","age"],

"data":[["mashiro",17],["satori",17],["koishi",16],["nagisa",21]]

}

"""

我们看到会变成三个键值对，分别是列名、索引、数据

orient='records'

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

print(df.to_json(orient="records"))

"""

[{"name":"mashiro","age":17},

{"name":"satori","age":17},

{"name":"koishi","age":16},

{"name":"nagisa","age":21}]

"""

这种格式的数据是比较常用的，相当于列名和每一行数据组合成一个字典，然后存在一个列表里面。并且我们看到生成json默认跟索引没啥关系，所以不需要、也不可以加index=False

orient='index'

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

print(df.to_json(orient="index"))

"""

{

"0":{"name":"mashiro","age":17},

"1":{"name":"satori","age":17},

"2":{"name":"koishi","age":16},

"3":{"name":"nagisa","age":21}

}

"""

类似于records，只不过这里把字典作为value放在了外层字典里，其中key为对应的索引。当然这里同样不可以加index=False

orient='columns'

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

print(df.to_json(orient="columns"))

"""

{"name":{"0":"mashiro","1":"satori","2":"koishi","3":"nagisa"},"age":{"0":17,"1":17,"2":16,"3":21}}

"""

我们看到这个和不指定orient得到结果是一样的，其实不指定的话orient默认是columns

orient=values

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

print(df.to_json(orient="values"))

"""

[["mashiro",17],["satori",17],["koishi",16],["nagisa",21]]

"""

# 我们看到当orient指定为values，会只获取数据

# 另外这个方式类似于to_numpy

print(df.to_numpy())

"""

[['mashiro' 17]

['satori' 17]

['koishi' 16]

['nagisa' 21]]

"""

orient=table

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

# 以数据库二维表的形式返回

print(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": "mashiro", "age": 17},

{"index": 1, "name": "satori", "age": 17},

{"index": 2, "name": "koishi", "age": 16},

{"index": 3, "name": "nagisa", "age": 21}]

}

"""

print(df.to_json(orient="table", index=False))

"""

{

"schema": {

"fields": [{"name": "name", "type": "string"},

{"name": "age", "type": "integer"}],

"pandas_version": "0.20.0"

},

"data": [{"name": "mashiro", "age": 17},

{"name": "satori", "age": 17},

{"name": "koishi", "age": 16},

{"name": "nagisa", "age": 21}]

}

"""

转成dict

DataFrame也可以转成字典，转换成字典里面也有一个orient参数，里面有一部分和to_json是类似的。因为json这个数据结构本身就借鉴了python中的字典，是的你没有看错，json这种数据结构参考了python中的字典。

to_dict中的orient可以有如下取值：dict、list、series、split、records、index，默认是dict

orient='dict'

from pprint import pprint

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

pprint(df.to_dict(orient="dict"))

"""

{'age': {0: 17, 1: 17, 2: 16, 3: 21},

'name': {0: 'mashiro', 1: 'satori', 2: 'koishi', 3: 'nagisa'}}

"""

orient='list'

from pprint import pprint

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

pprint(df.to_dict(orient="list"))

"""

{'age': [17, 17, 16, 21], 'name': ['mashiro', 'satori', 'koishi', 'nagisa']}

"""

orient='series'

from pprint import pprint

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

# 这种结构真的不常用，就是一个key对应一个series

pprint(df.to_dict(orient="series"))

"""

{'age':

0 17

1 17

2 16

3 21

Name: age, dtype: int64,

'name': 0 mashiro

1 satori

2 koishi

3 nagisa

Name: name, dtype: object}

"""

orient='split'

from pprint import pprint

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

pprint(df.to_dict(orient="split"))

"""

{'columns': ['name', 'age'],

'data': [['mashiro', 17], ['satori', 17], ['koishi', 16], ['nagisa', 21]],

'index': [0, 1, 2, 3]}

"""

orient='records'

from pprint import pprint

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

pprint(df.to_dict(orient="records"))

"""

[{'age': 17, 'name': 'mashiro'},

{'age': 17, 'name': 'satori'},

{'age': 16, 'name': 'koishi'},

{'age': 21, 'name': 'nagisa'}]

"""

orient='index'

from pprint import pprint

import pandas as pd

df = pd.DataFrame({"name": ["mashiro", "satori", "koishi", "nagisa"],

"age": [17, 17, 16, 21]})

pprint(df.to_dict(orient="index"))

"""

{0: {'age': 17, 'name': 'mashiro'},

1: {'age': 17, 'name': 'satori'},

2: {'age': 16, 'name': 'koishi'},

3: {'age': 21, 'name': 'nagisa'}}

"""

python中的数据格式转成DataFrame

字典转成DataFrame

import pandas as pd

data = {0: {'age': 17, 'name': 'mashiro'},

1: {'age': 17, 'name': 'satori'},

2: {'age': 16, 'name': 'koishi'},

3: {'age': 21, 'name': 'nagisa'}}

df = pd.DataFrame.from_dict(data)

# 显然不是我们期待的格式

print(df)

"""

0 1 2 3

age 17 17 16 21

name mashiro satori koishi nagisa

"""

df = pd.DataFrame.from_dict(data, orient="index")

print(df)

"""

age name

0 17 mashiro

1 17 satori

2 16 koishi

3 21 nagisa

"""

所以df.to_dict和pd.DataFrame.from_json实现的是相反的功能，但是from_dict中的orient参数只有两种选择，要么是index，要么是columns，默认是columns

from_records

from_records是专门针对外层是列表的数据

import pandas as pd

data = [{'age': 17, 'name': 'mashiro'},

{'age': 17, 'name': 'satori'},

{'age': 16, 'name': 'koishi'},

{'age': 21, 'name': 'nagisa'}]

df = pd.DataFrame.from_records(data)

print(df)

"""

age name

0 17 mashiro

1 17 satori

2 16 koishi

3 21 nagisa

"""

其实这种数据就是to_dict(orient="records")生成的

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