python - json.dumps - json.loads - requests.get

import numpy as np
import pandas as pd
from pandas import Series, DataFrame   # pandas 数据分析包

#JSON数据
obj = """
{"name": "Wes",
"places_lived": ["United States", "Spain", "Germany"],
"pet": null,
"siblings": [{"name": "Scott", "age": 25, "pet": "Zuko"},
{"name": "Katie", "age": 33, "pet": "Cisco"}]
}
"""

import json
result = json.loads(obj)  #解码python json格式，可以用这个模块的json.loads()函数的解析方法
#print( result )

asjson = json.dumps(result) #json.dumps是将一个Python数据类型列表进行json格式的编码解析
#print( asjson )

_list = ['iplaypython',[1,2,3], {'name':'xiaoming'}]
_list_to_json = json.dumps(_list) # 将一个list列表对象，进行了json格式的编码转换
#print( _list_to_json )
'''
python 3.x 之前

json.dumps:dict转成str        json.dump是将python数据保存成json
json.loads:str转成dict        json.load是读取json数据

json.dump和json.dumps很不同，json.dump主要用来json文件读写，和json.load函数配合使用。

python 3.x 之后只剩下 dumps 和 loads
'''

siblings = DataFrame(result['siblings'], columns=['name', 'age'])
siblings

#二进制数据格式
#pickle
frame = pd.read_csv('data/ex1.csv')
frame
frame.to_pickle('data/frame_pickle')

pd.read_pickle('data/frame_pickle')

#HDF5格式
store = pd.HDFStore('mydata.h5')
store['obj1'] = frame
store['obj1_col'] = frame['a']
store

store['obj1']

store.close()
#os.remove('mydata.h5')

#使用HTML和Web API
import requests
url = 'https://api.github.com/repos/pydata/pandas/milestones/28/labels'
resp = requests.get(url)
resp

data=json.loads(resp.text)

issue_labels = DataFrame(data)
#print( issue_labels )