我不能明白的代码

Question

这个练习的目标是生成一个图表作为该页面中的特定部分：（http://www.realclearpolitics.com/epolls/2012/president/us/general_election_romney_vs_obama-1171.html）

用于生成这样的图上的数据被存储为XML页，网址如： http://charts.realclearpolitics.com/charts/[id].xml 这里，[id]是一个唯一的整数，位于显示图形的页面的URL的末尾。奥巴马，罗姆尼的比赛ID是1171：

import re 

def get_poll_xml(poll_id): 
    url ="http://charts.realclearpolitics.com/charts/%i.xml" %int(poll_id) 
    return requests.get(url).text 

def _strip(s): # function to remove characters 
    return re.sub(r'[\W_]+', '', s) 

def plot_colors(xml): 
    ''' 
    Given an XML document like the link above, returns a python dictionary 
    that maps a graph title to a graph color. 

    Both the title and color are parsed from attributes of the <graph> tag: 
    <graph title="the title", color="#ff0000"> -> {'the title': '#ff0000'} 
    ''' 
    dom = web.Element(xml) 
    result = {} 
    for graph in dom.by_tag('graph'): 
     title = _strip(graph.attributes['title']) 
     result[title] = graph.attributes['color'] 
    return result 

def rcp_poll_data(xml): 
    """ 
    A pandas DataFrame with the following columns: 
    date: The date for each entry 
    title_n: The data value for the gid=n graph 

    This DataFrame should be sorted by date 

    Example 
    ------- 
    Consider the following simple xml page: 

    <chart> 
    <series> 
    <value xid="0">1/27/2009</value> 
    <value xid="1">1/28/2009</value> 
    </series> 
    <graphs> 
    <graph gid="1" color="#000000" balloon_color="#000000" title="Approve"> 
    <value xid="0">63.3</value> 
    <value xid="1">63.3</value> 
    </graph> 
    <graph gid="2" color="#FF0000" balloon_color="#FF0000" title="Disapprove"> 
    <value xid="0">20.0</value> 
    <value xid="1">20.0</value> 
    </graph> 
    </graphs> 
    </chart> 

    Given this string, rcp_poll_data should return 
    result = pd.DataFrame({'date': pd.to_datetime(['1/27/2009', '1/28/2009']), 
         'Approve': [63.3, 63.3], 'Disapprove': [20.0, 20.0]}) 
    """ 
    dom = web.Element(xml) 
    result = {}   

    dates = dom.by_tag('series')[0]  
    dates = {n.attributes['xid']: str(n.content) for n in dates.by_tag('value')} 

    keys = dates.keys() 
    result['date'] = pd.to_datetime([dates[k] for k in keys]) 

    for graph in dom.by_tag('graph'): 
     name = graph.attributes['title'] 
     data = {n.attributes['xid']: float(n.content) if n.content else np.nan for n in graph.by_tag('value') } 
     keyl = data.keys()  
     result[name] = [data[k]for k in keyl] 

    result = pd.DataFrame(result) 
    result = result.sort(columns=['date']) 

    return result 

def poll_plot(poll_id): 
    xml = get_poll_xml(poll_id) 
    data = rcp_poll_data(xml) 
    colors = plot_colors(xml) 

    #remove characters like apostrophes 
    data = data.rename(columns = {c: _strip(c) for c in data.columns}) 

    #normalize poll numbers so they add to 100%  
    norm = data[colors.keys()].sum(axis=1)/100  
    for c in colors.keys(): 
     data[c] /= norm 

    for label, color in colors.items(): 
     plt.plot(data.date, data[label], color=color, label=label)   

    plt.xticks(rotation=70) 
    plt.legend(loc='best') 
    plt.xlabel("Date") 
    plt.ylabel("Normalized Poll Percentage") 

poll_plot(1044) 
plt.title("Obama Job Approval") 

在上述代码中，我不可能了解以下部分，可有人给我解释一下。我完全失去了。

data = data.rename(columns = {c: _strip(c) for c in data.columns}) 

#normalize poll numbers so they add to 100%  
norm = data[colors.keys()].sum(axis=1)/100  
for c in colors.keys(): 
    data[c] /= norm 

for label, color in colors.items(): 
    plt.plot(data.date, data[label], color=color, label=label) 

Answer 1

你在评论中说你想知道什么意思/=。它被称为增强分配并在PEP 203中定义。

你有一个INT var和希望值总和为它

n = 1 
n = n + 1 
print n 
2 

这里是一个优化的方式来做到这一点

n = 1 
n += 1 

正是在循环

使用起来非常有用

n = 1 
while n < 10: 
    n += 1 

print n 
10 

所以用/=你正在使用格操盘添加

n = 4 
n /= 2 
print n 
2 

n = 10 
while n > 2: 
    n /= 2 

print n 
2 

欲了解更多信息有关增强Assignement看看Wikepedia项。

Answer 2

如果您想知道语法data[c] /= norm的含义，它与更常见的+=运算符类似。它占据作业左侧的左侧，并将其指定为左侧值除以右侧值。它相当于data[c] = data[c]/norm。例如

x = 6.0 
x /= 2.0 

现在x将有3.0

值，请尽量在什么你问你的问题，并呼唤你不理解的代码的特定部分更加清晰。