Python 从多数据帧字典中提取数据帧

我有一个字典，其中包含大量的数据帧。我想从中提取所有数据帧，并将这些值存储到单个数据帧中。词典如图所示：

wwwwww = pd.DataFrame.from_dict(res, orient='index')

data2 = pd.DataFrame(res, index =[0])

import pandas as pd
import mysql.connector 
from nsepy import get_history
from datetime import date
stock =['3MINDIA','ABB','POWERINDIA','ACC','AIAENG'] //There are many values but I am including lesser values
res = dict(zip(stock,stock))
start = date (2019, 12, 1)
end = date (2020, 12, 10)

for stock_name in stock:
     data = get_history(symbol=stock_name['close'], start=start, end=end)
     res[stock_name]=data

data2 = pd.DataFrame([res], index =[0])


wwwwww = pd.DataFrame.from_dict(res, orient='index')

字典中存储的许多数据帧之一如下所示：

wwwwww = pd.DataFrame.from_dict(res, orient='index')

data2 = pd.DataFrame(res, index =[0])

import pandas as pd
import mysql.connector 
from nsepy import get_history
from datetime import date
stock =['3MINDIA','ABB','POWERINDIA','ACC','AIAENG'] //There are many values but I am including lesser values
res = dict(zip(stock,stock))
start = date (2019, 12, 1)
end = date (2020, 12, 10)

for stock_name in stock:
     data = get_history(symbol=stock_name['close'], start=start, end=end)
     res[stock_name]=data

data2 = pd.DataFrame([res], index =[0])


wwwwww = pd.DataFrame.from_dict(res, orient='index')

我已尝试使用“pd.DataFrame.from_dict”方法，如下所示：

wwwwww = pd.DataFrame.from_dict(res, orient='index')

data2 = pd.DataFrame(res, index =[0])

import pandas as pd
import mysql.connector 
from nsepy import get_history
from datetime import date
stock =['3MINDIA','ABB','POWERINDIA','ACC','AIAENG'] //There are many values but I am including lesser values
res = dict(zip(stock,stock))
start = date (2019, 12, 1)
end = date (2020, 12, 10)

for stock_name in stock:
     data = get_history(symbol=stock_name['close'], start=start, end=end)
     res[stock_name]=data

data2 = pd.DataFrame([res], index =[0])


wwwwww = pd.DataFrame.from_dict(res, orient='index')

但呈现给我的输出是乱码或不推荐的，如图所示：

wwwwww = pd.DataFrame.from_dict(res, orient='index')

data2 = pd.DataFrame(res, index =[0])

import pandas as pd
import mysql.connector 
from nsepy import get_history
from datetime import date
stock =['3MINDIA','ABB','POWERINDIA','ACC','AIAENG'] //There are many values but I am including lesser values
res = dict(zip(stock,stock))
start = date (2019, 12, 1)
end = date (2020, 12, 10)

for stock_name in stock:
     data = get_history(symbol=stock_name['close'], start=start, end=end)
     res[stock_name]=data

data2 = pd.DataFrame([res], index =[0])


wwwwww = pd.DataFrame.from_dict(res, orient='index')

因此，我做了进一步的搜索，找到了使用pandas将字典转换为数据帧的最简单的方法，并使用它，如图所示：

wwwwww = pd.DataFrame.from_dict(res, orient='index')

data2 = pd.DataFrame(res, index =[0])

import pandas as pd
import mysql.connector 
from nsepy import get_history
from datetime import date
stock =['3MINDIA','ABB','POWERINDIA','ACC','AIAENG'] //There are many values but I am including lesser values
res = dict(zip(stock,stock))
start = date (2019, 12, 1)
end = date (2020, 12, 10)

for stock_name in stock:
     data = get_history(symbol=stock_name['close'], start=start, end=end)
     res[stock_name]=data

data2 = pd.DataFrame([res], index =[0])


wwwwww = pd.DataFrame.from_dict(res, orient='index')

使用此选项，我得到一个值错误，如图所示：

wwwwww = pd.DataFrame.from_dict(res, orient='index')

data2 = pd.DataFrame(res, index =[0])

import pandas as pd
import mysql.connector 
from nsepy import get_history
from datetime import date
stock =['3MINDIA','ABB','POWERINDIA','ACC','AIAENG'] //There are many values but I am including lesser values
res = dict(zip(stock,stock))
start = date (2019, 12, 1)
end = date (2020, 12, 10)

for stock_name in stock:
     data = get_history(symbol=stock_name['close'], start=start, end=end)
     res[stock_name]=data

data2 = pd.DataFrame([res], index =[0])


wwwwww = pd.DataFrame.from_dict(res, orient='index')

ValueError：传递值的形状是（14501），索引暗示（1501）

因此，我进一步搜索，发现堆栈溢出的答案如下：

在这种情况下，字典作为行传递，如下所示：

data2 = pd.DataFrame([res], index =[0])

再次使用它，我得到一个乱码值，如图所示：

wwwwww = pd.DataFrame.from_dict(res, orient='index')

data2 = pd.DataFrame(res, index =[0])

import pandas as pd
import mysql.connector 
from nsepy import get_history
from datetime import date
stock =['3MINDIA','ABB','POWERINDIA','ACC','AIAENG'] //There are many values but I am including lesser values
res = dict(zip(stock,stock))
start = date (2019, 12, 1)
end = date (2020, 12, 10)

for stock_name in stock:
     data = get_history(symbol=stock_name['close'], start=start, end=end)
     res[stock_name]=data

data2 = pd.DataFrame([res], index =[0])


wwwwww = pd.DataFrame.from_dict(res, orient='index')

如何实现将字典中的所有数据帧提取到单个数据帧的任务？有没有什么有效的方法

如果需要代码，我附加如下所示：

wwwwww = pd.DataFrame.from_dict(res, orient='index')

data2 = pd.DataFrame(res, index =[0])

import pandas as pd
import mysql.connector 
from nsepy import get_history
from datetime import date
stock =['3MINDIA','ABB','POWERINDIA','ACC','AIAENG'] //There are many values but I am including lesser values
res = dict(zip(stock,stock))
start = date (2019, 12, 1)
end = date (2020, 12, 10)

for stock_name in stock:
     data = get_history(symbol=stock_name['close'], start=start, end=end)
     res[stock_name]=data

data2 = pd.DataFrame([res], index =[0])


wwwwww = pd.DataFrame.from_dict(res, orient='index')

---

由于字典中的值已经是数据帧，我认为您不想尝试将字典直接转换为数据帧。相反，迭代字典并将所有值添加到新的数据帧中

for key, df in res.items():
    # create a column called "key name"
    df['key_name'] = key

lst = list(res.values())
df = pd.concat(lst)

你在乎字典里的钥匙吗

如果没有一种可能的解决方案，那就是仅使用字典中的值创建一个列表，然后将其合并到具有的数据帧中

lst=list（res.values（））
df=局部混凝土（lst）

如果您确实关心字典中的键，可以尝试将键作为列添加到每个数据帧中

for key, df in res.items():
    # create a column called "key name"
    df['key_name'] = key

lst = list(res.values())
df = pd.concat(lst)

---

我真的很在乎钥匙