将两个 Pandas 数据帧连接在一起（在 python 中）
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Concatenate two pandas data frames together (in python)
提问by Tom
I am working on a simple trading also and need some help with concatenating to data frames together. Until my now my approach does't work.
我也在做一个简单的交易，需要一些帮助来将数据帧连接在一起。直到我现在我的方法不起作用。
My code is the following:
我的代码如下：
Connect to quantle API
连接到 quantle API
quandl.ApiConfig.api_key = 'xxxxxxxxxxxxxxx'
Ticker symbols
股票代码
ticker = ['FSE/ZO1_X',"FSE/WAC_X"]
Create a panel object with quotes from panda -> create a pandas DataFrame
用Pandas的引号创建一个面板对象 -> 创建一个Pandas数据帧
df = quandl.get(ticker, start_date='2017-01-01', end_date='2017-11-03')
Slicing the close prices for each stock out of the panel data set
从面板数据集中切出每只股票的收盘价
close1 = df['FSE/ZO1_X - Close']
close2 = df['FSE/WAC_X - Close']
Concatenate the two data frames together - THIS STEP DOESN'T WORK
将两个数据帧连接在一起 - 这一步不起作用
close = pd.concat(close1,close2)
The type of close1 and close 2 is pandas.core.series.Series.
close1 和 close 2 的类型是 pandas.core.series.Series。
How can I put close1 and close2 together, so that the index is the date and I have two additional columns with the close prices of stock 1 (close1) and stock 2 (close2) - similar like an ordinary excel sheet.
如何将 close1 和 close2 放在一起，以便索引是日期，并且我有两个附加列，其中包含股票 1 (close1) 和股票 2 (close2) 的收盘价 - 类似于普通的 Excel 表格。
回答by Omkar Neogi
close = pd.concat([close1, close2], axis=1)
should do it.
应该这样做。
Full example:
完整示例：
import pandas as pd
import numpy as np
s = pd.Series([1,2,3,4,5])
t = pd.Series([11,12,13,14,15])
s = pd.concat([s,t], axis=1)
print(s)
Output:
输出：
0 1
0 1 11
1 2 12
2 3 13
3 4 14
4 5 15
