Matplotlib基于值的条形图的不同颜色 [英] Matplotlib different colors for bar graph based on value

问题描述

我正在绘制部门及其所有股票的收益.我希望值> 100为绿色，而< 100为红色.这是我的代码:

I'm plotting returns for sectors and all the stocks in them. I would like to have the values > 100 to be green, and < 100 to be red. Here's my code:

sector_lst = ['XLK','XLF','XLE']  ## etc.

for i in sector_lst:                   
    fig = plt.figure(figsize=(12, 8)) 

    for x in sectordict[i]:                #sectordict[i] is all the stocks in a sector (so AAPL, GOOG, etc. for tech) 
        if pct_change[x] > 1:              
             pct_change[sectordict[i]].plot(kind='bar',color='g') 

        ##if pct_chg < 1
        else:                              
             pct_change[sectordict[i]].plot(kind='bar',color='r') 


plt.title(i)

到目前为止，这会将整个扇形图返回为绿色或红色；如果第一个值大于100，则所有库存均为绿色，反之亦然.

So far this is returning the whole sector graphs as green or red; if the first value is > 100 all stocks will be green and vice versa.

我的预期输出是有11张图表(当前执行此操作)，但是图表中每只股票具有不同的颜色，如果股票回报率> 100％，则显示绿色，而< 100％显示为红色.

My expected output is to have 11 graphs (which it currently does), but with different colors for each stock within the graph, if stock had > 100% return then it shows green and < 100% it shows red.

推荐答案

在使用Pandas plot()进行了几次尝试之后，我没有找到实现您所期望的方法，但是您可以直接使用Matplotlib轻松地做到这一点.

After few tries with Pandas plot() I didn't find a way to achieve what you expect but you can easily do that with Matplotlib directly.

我希望这会有所帮助:

我创建了示例df:

df = pd.DataFrame({'a' : [2,6,2,4,5,3,7]})

然后我创建两个temp df，它将仅存储满足条件的值:

and I create two temp df which will store only values satisfying the condition:

t1 = df[df['a']<5]
t2 = df[df['a']>=5]

然后将其绘制:

plt.bar(t1.index.values, t1['a'], color='r')
plt.bar(t2.index.values, t2['a'], color='g')

最终结果如下:

这是您的期望吗?

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