PYODBC 到 Pandas - DataFrame 不工作 - 传递值的形状是 (x,y)，索引意味着 (w,z) [英] PYODBC to Pandas - DataFrame not working - Shape of passed values is (x,y), indices imply (w,z)

问题描述

我之前在 python 中使用了 pyodbc，但现在我已经将它安装在一台新机器上(win 8 64 位，Python 2.7 64 位，PythonXY with Spyder).

I used pyodbc with python before but now I have installed it on a new machine ( win 8 64 bit, Python 2.7 64 bit, PythonXY with Spyder).

以前我用过(在底部你可以找到更多真实的例子):

Before I used to (at the bottom you can find more real examples):

columns = [column[0] for column in cursor.description]
temp = cursor.fetchall()
data = pandas.DataFrame(temp,columns=columns)

它会工作得很好.现在似乎 DataFrame 无法再从从游标获取的数据中进行转换.它返回:

and it would work fine. Now it seems like DataFrame is not able to convert from the data fetched from the cursor anymore. It returns:

传递值的形状是 (x,y)，索引表示 (w,z)

Shape of passed values is (x,y), indices imply (w,z)

我有点明白问题出在哪里.基本上，想象一下我只获取一行.然后 DataFrame 想对它进行整形(1,1)，只有一个元素.虽然我想要 (1,X) 其中 X 是列表的长度.

I kind of see where the issue is. Basically, imagine I fetch only one row. Then DataFrame would like to shape it (1,1), one element only. While I would like to have (1,X) where X is the length of the list.

我不确定为什么行为会改变.可能是我的Pandas版本，或者pyodbc，但是更新有问题.我试图更新一些模块，但它搞砸了一切，我使用的任何方法(二进制文件--用于正确的机器/安装--pip 安装、简易安装、任何东西！等等.这确实非常令人沮丧.我可能会避免从现在开始，为 Python 赢得 8 64 位).

I am not sure why the behavior changed. Maybe it is the Pandas version I have, or the pyodbc, but updating is problematic. I tried to update some modules but it screws up everything, any method I use (binaries--for the right machine/installation--pip install, easy-install,anything! etc.. which is very frustrating indeed. I would probably avoid Win 8 64 bit from now on for Python).

真实例子:

sql = 'Select * form TABLE'
cursor.execute(sql)
columns = [column[0] for column in cursor.description]
data    = cursor.fetchall()
        con.close()
            results = DataFrame(data, columns=columns)

返回:* ValueError: 传递值的形状是 (1, 1540)，索引意味着 (51, 1540)

Returns: * ValueError: Shape of passed values is (1, 1540), indices imply (51, 1540)

请注意:

ipdb> type(data)
<type 'list'>
ipdb> np.shape(data)
(1540, 51)
ipdb> type(data[0])
<type 'pyodbc.Row'>

现在，例如，如果我们这样做:

Now, for example, if we do:

ipdb> DataFrame([1,2,3],columns=['a','b','c'])

* ValueError: 传递值的形状是 (1, 3)，索引意味着 (3, 3)

* ValueError: Shape of passed values is (1, 3), indices imply (3, 3)

如果我们这样做:

ipdb> DataFrame([[1,2,3]],columns=['a','b','c'])

a b c0 1 2 3

a b c 0 1 2 3

然而，即使尝试:

ipdb> DataFrame([data[0]], columns=columns)
*** ValueError: Shape of passed values is (1, 1), indices imply (51, 1)

或

ipdb> DataFrame(data[0], columns=columns)
*** PandasError: DataFrame constructor not properly called!

请帮忙:)谢谢！

推荐答案

从 Pandas 0.12(我相信)你可以做到:

As of Pandas 0.12 (I believe) you can do:

import pandas
import pyodbc

sql = 'select * from table'
cnn = pyodbc.connect(...)

data = pandas.read_sql(sql, cnn)

在 0.12 之前，您可以:

Prior to 0.12, you could do:

import pandas
from pandas.io.sql import read_frame
import pyodbc

sql = 'select * from table'
cnn = pyodbc.connect(...)

data = read_frame(sql, cnn)

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