用 pandas 对象进行算术运算

Question

我想用 Python 计算两个 Pandas 系列之间的差异。不幸的是，返回了一个我无法理解的错误。我的代码的相关部分是：

import urllib.request 
import pandas as pd 

base_url = "http://ichart.finance.yahoo.com/table.csv?s="

def get_data(base_url,ticker):
    url = base_url + ticker
    source = urllib.request.urlopen(url)
    return  pd.read_csv(source,index_col=0,parse_dates=True,header=None)

ticker_list = {'INTC': 'Intel'}

for ticker in ticker_list:
    prices = get_data(base_url,ticker)
    prices.columns = 'Open','High','Low','Close','Volume','Adj Close'
    closing_prices = prices['Close']
    begin = closing_prices.ix[['2013-01-03']]
    end = closing_prices.ix[['2013-12-27']]
    difference = end.sub(begin)

Python 返回以下错误：

 TypeError: unsupported operand type(s) for -: 'str' and 'str'

但是，type(begin) 和 type(end) 一样返回 pandas.core.series.Series。我使用了end.sub() 的方法，因为我认为我想遵守此处所述的说明：http://pandas.pydata.org/pandas-docs/dev/generated/pandas.Series.sub.html。为了解决我的问题，我（除其他外）遵循了以下建议：Subtract a column from one pandas dataframe from another 无济于事。

您知道错误隐藏在我的代码中的什么地方吗？特别是，为什么 Python 声明我尝试减去字符串？我很感激任何帮助！

更新：在@EdChum 的评论之后，我想发布一些数据：输入begin 给出：

`2013-01-03    21.32
 Name: Close, dtype: object

closing_prices.head() 给出：

`0
Date          Close
2014-08-07    32.68 
2014-08-06    32.85
2014-08-05    32.82
2014-08-04    34.05
Name: Close, dtype: object` 

Answer 1

我不得不将 urllib 更改为 urllib2，并将 urllib.request.urlopen 更改为 urllib2.urlopen.. 但是，它应该是相同的。第一个问题是由将列名存储为值引起的。消除 header=None 可以解决这个问题。

这应该会给你指定的第一个和最后一个日期之间的差异：

import urllib2
import pandas as pd 

base_url = "http://ichart.finance.yahoo.com/table.csv?s="

def get_data(base_url,ticker):
    url = base_url + ticker
    source = urllib2.urlopen(url)
    return  pd.read_csv(source,index_col=0,parse_dates=True)

ticker_list = {'INTC': 'Intel'}

编辑-一定要检查数据的排序。它把最新的放在顶部，最旧的放在底部。

for ticker in ticker_list:
    prices = get_data(base_url,ticker)
    prices.columns = 'Open','High','Low','Close','Volume','Adj Close'
    closing_prices = prices['Close']
    closing_prices = closing_prices['2013-01-03':'2013-12-27']
    difference = closing_prices['2013-12-27'].values - closing_prices['2013-01-03'].values
    print difference

Answer 2

这听起来比实际上要复杂：您需要将end end begin 转换为数字数据类型。试试DataFrame.convert_objects：

...
begin = begin.convert_objects(convert_numeric=True)
end = end.convert_objects(convert_numeric=True)
difference = end.sub(begin)

更新：以下代码适用于我：

import urllib2
import pandas as pd 

base_url = "http://ichart.finance.yahoo.com/table.csv?s="

def get_data(base_url,ticker):
    url = base_url + ticker
    source = urllib2.urlopen(url)
    return  pd.read_csv(source,index_col=0,parse_dates=True,header=None)

ticker_list = {'INTC': 'Intel'}

for ticker in ticker_list:
    prices = get_data(base_url,ticker)
    prices.columns = 'Open','High','Low','Close','Volume','Adj Close'

    # this will convert the closing_prices Series to float
    closing_prices = prices['Close'].convert_objects(convert_numeric=True)

    # changed the double square brackets [[]] to single square brackets to
    # obtain a scalar, rather than a single element Series
    begin = closing_prices.ix['2013-01-03']
    end = closing_prices.ix['2013-12-27']
    difference = end - begin