Python字典到数据帧问题
我正在尝试接受api请求,并将它们放在SQL可访问的格式中——目前我有嵌套字典,我不确定如何快速修复它们 这是目前的代码Python字典到数据帧问题,python,pandas,numpy,Python,Pandas,Numpy,我正在尝试接受api请求,并将它们放在SQL可访问的格式中——目前我有嵌套字典,我不确定如何快速修复它们 这是目前的代码 timestr = time.strftime("%Y%m%d-%H%M%S") Name= "swing_data_"+timestr+".json" api_results = {} for items in States: url = url_swing + items request = requests.get(url)
timestr = time.strftime("%Y%m%d-%H%M%S")
Name= "swing_data_"+timestr+".json"
api_results = {}
for items in States:
url = url_swing + items
request = requests.get(url)
api_results[items]=(request.json())
with open(Name, 'w') as f:
json.dump(api_results, f)
数据帧输出是这样的
df = pd.DataFrame.from_dict([api_results])
df.head()
刚才编辑的问题,,
要格式化数据,列为类型、类型等,状态为另一列创建
数据框的字典
s,然后通过最后删除第二级多索引
,重命名
并将索引转换为列键
:
d = {k: pd.DataFrame(v) for k, v in api_results.items()}
df = pd.concat(d).reset_index(level=1, drop=True).rename_axis('key').reset_index()
print (df)
key type suburb street oldRange \
0 VIC House Carlton North 114 Garton Street $4,400,000 - $4,800,000
1 VIC House Fitzroy North 24 Egremont Street $1,600,000 - $1,750,000
2 VIC House Hamlyn Heights 6 Heritage Drive $1,180,000 - $1,280,000
3 VIC House Caulfield South 24 Emma Street $1,900,000 - $2,089,999
newRange dollarDelta percentDelta daysDelta
0 $4,100,000 -$700,000 -14% 42
1 $1,950,000 - $2,100,000 $350,000 20% 62
2 $990,000 - $1,050,000 -$230,000 -17% 82
3 $1,800,000 - $1,980,000 -$109,999 -5% 33
如果可能,在第一个循环中创建DataFrame
s:
api_results = {}
for items in States:
url = url_swing + items
request = requests.get(url)
api_results[items]= pd.DataFrame(request.json())
df = pd.concat(api_results).reset_index(level=1, drop=True).rename_axis('key').reset_index()
这里的问题到底是什么?^^刚刚编辑的问题,想要格式化数据,列为类型、郊区等,并将状态作为另一列。请共享dataframe的示例输入和预期输出,而不是以图像的形式。