Python转置，列名在数据帧记录内(Python transpose, column name are inside the dataframe records)

 我很确定我在这里遗漏了一些非常基本的东西，但我并没有真正找到我在pandas文档中寻找的内容。 
 
 我下载了一个ForEx数据框，并希望保存它，但在我这样做之前，我必须将其格式化为8列/ X行，矩阵/数据帧/向量（根据需要多行）。 我把它作为一行，每个记录旁边都有他的列名。 （我可以将它保存在.CSV中） 
 
 我在这里的权力是.transpose，仅此而已。 
 
 我已经成功了这一次，但我似乎已经忘记了保存代码而且它已经有一段时间了......但是多亏了这个我可以告诉你一个较旧的csv我读到python，并显示我想要的格式化它。 
 
 （列名：索引（不是真正的列，它只是索引），关闭，日期，高，低，打开，关闭，qouteVolume，音量，weightedAvarage） 
 
   
 
    source_df = get_ForEx_data(**params)
list(source_df )
list(TransposedData)
TransposedData = source_df .transpose()
 
 编辑:(从互联网获取数据的功能） 
 
def get_poloinex_data(s, a, b, c):

import requests
from pandas import DataFrame
from io import StringIO

url = 'https://poloniex.com/public?command=returnChartData'

url += '&currencyPair=' + s #USDT a dollár
url += '&start=' + a
url += '&end=' + b
url += '&period=' + c

csv = requests.get(url)

if csv.ok:
    return DataFrame.from_csv(StringIO(csv.text), sep=',') #Separátor itt!
else:
    return None
 
 我在python中使用的数据是这样的： 
 
Columns: [high:1.85, low:0.50000021, open:1.65, close:1.85, volume:144.42819254, quoteVolume:84.01638508, weightedAverage:1.71904792}, {"date":1439020800, high:1.7, low:1.40000001, open:1.7, close:1.40000001, volume:129.57577588, quoteVolume:92.52305316, weightedAverage:1.40047016}, {"date":1439035200, high:1.40000001, low:1.40000001.1, open:1.40000001, close:1.40000001.1, volume:0, quoteVolume:0, weightedAverage:1.40000001}, {"date":1439049600, high:1.40000001.1, low:1.40000001.2, open:1.40000001.1, close:1.40000001.2, volume:0.1, quoteVolume:0.1, weightedAverage:1.40000001}.1, {"date":....
 
 我要找的是这样的： 
 
              close                 date       high        low       open  \
0      1.850000  2015-08-08 04:00:00   1.850000   0.500000   1.650000   
1      1.400000  2015-08-08 08:00:00   1.700000   1.400000   1.700000   
2      1.400000  2015-08-08 12:00:00   1.400000   1.400000   1.400000   
3      1.400000  2015-08-08 16:00:00   1.400000   1.400000   1.400000
 
 等等剩下的列 

I'm quite sure that I'm missing something very elementary here, but I didn't really found what i was looking for in the pandas documentation.
 
I download a ForEx data-frame , and want to save it, but before I do that, I have to format it to a 8 columns/X rows, matrix/data-frame/vector (as many rows as needed). I have it as a line with every record having his column name next to it. (I can save it in .CSV)
 
My powers here are .transpose, which alone isn't doing the trick.
 
I already succeded with this once, but I seems to have forgotten to save the code and it was a while back.... But thanks to this I can show you an older csv I read in to python, and show how I want to format it.
 
(column names: Index(not really a column, it is just the index),close,date,high,low,open,close,qouteVolume,volume,weightedAvarage)
 
 
 
    source_df = get_ForEx_data(**params)
list(source_df )
list(TransposedData)
TransposedData = source_df .transpose()
 
Edit: (function that gets the data from the internet)
 
def get_poloinex_data(s, a, b, c):

import requests
from pandas import DataFrame
from io import StringIO

url = 'https://poloniex.com/public?command=returnChartData'

url += '&currencyPair=' + s #USDT a dollár
url += '&start=' + a
url += '&end=' + b
url += '&period=' + c

csv = requests.get(url)

if csv.ok:
    return DataFrame.from_csv(StringIO(csv.text), sep=',') #Separátor itt!
else:
    return None
 
The data I get using this is like this in python:
 
Columns: [high:1.85, low:0.50000021, open:1.65, close:1.85, volume:144.42819254, quoteVolume:84.01638508, weightedAverage:1.71904792}, {"date":1439020800, high:1.7, low:1.40000001, open:1.7, close:1.40000001, volume:129.57577588, quoteVolume:92.52305316, weightedAverage:1.40047016}, {"date":1439035200, high:1.40000001, low:1.40000001.1, open:1.40000001, close:1.40000001.1, volume:0, quoteVolume:0, weightedAverage:1.40000001}, {"date":1439049600, high:1.40000001.1, low:1.40000001.2, open:1.40000001.1, close:1.40000001.2, volume:0.1, quoteVolume:0.1, weightedAverage:1.40000001}.1, {"date":....
 
what I looking for is like this:
 
              close                 date       high        low       open  \
0      1.850000  2015-08-08 04:00:00   1.850000   0.500000   1.650000   
1      1.400000  2015-08-08 08:00:00   1.700000   1.400000   1.700000   
2      1.400000  2015-08-08 12:00:00   1.400000   1.400000   1.400000   
3      1.400000  2015-08-08 16:00:00   1.400000   1.400000   1.400000
 
and so on with the remaining columns 

原文：https://stackoverflow.com/questions/43479858