如何将两个数据帧与一个索引合并到一个数据帧中？

Question

我创建了两个panda数据帧，第一个称为dfmas，索引为Date，然后是dates、data和3个移动平均列

             OPEN   HIGH    LOW   LAST     ma5     ma8  ma21
Date                                                        
11/23/2009  88.84  89.19  88.58  88.97     NaN     NaN   NaN
11/24/2009  88.97  89.07  88.36  88.50     NaN     NaN   NaN
11/25/2009  88.50  88.63  87.22  87.35     NaN     NaN   NaN
11/26/2009  87.35  87.48  86.30  86.59     NaN     NaN   NaN
11/27/2009  86.59  87.02  84.83  86.53  87.588     NaN   NaN
11/30/2009  87.17  87.17  85.87  86.41  87.076     NaN   NaN
12/1/2009   86.41  87.53  86.17  86.68  86.712     NaN   NaN
12/2/2009   86.68  87.49  86.59  87.39  86.720  87.302   NaN
12/3/2009   87.39  88.48  87.32  88.26  87.054  87.214   NaN
12/4/2009   88.26  90.77  88.00  90.56  87.860  87.471   NaN

第二个数据帧是由移动平均值交叉时的上述数据组成的

ma = [0,]
ma5Last = ma5[0]
ma8Last = ma8[0]

for ma5Curr, ma8Curr in zip(ma5[1:], ma8[1:]):
    if ma5Curr > ma5Last and ma8Curr > ma8Last:
        ma.append(1)
    elif ma5Curr < ma5Last and ma8Curr < ma8Last:
        ma.append(-1)
    else:
        ma.append(0)
    ma5Last = ma5Curr
    ma8Last = ma8Curr        

maX = pd.DataFrame(ma).astype('float')
maX.columns = ['maX']

下面称为“maX”

   maX
0  0.0
1  0.0
2  0.0
3  0.0
4  0.0
5  0.0
6  0.0
7  0.0
8  0.0
9  1.0

但是，我无法合并/合并2个数据帧。 如何将'Date'索引添加到第二个'maX'数据帧，然后将这两个数据帧合并/合并/合并在一起？非常感谢

Answer 1

如果数据帧长度相同，只需从原始DataFrame添加index作为对齐索引：

maX = pd.DataFrame(ma, index=df.index).astype('float')

Answer 2

这就是你要找的吗

df['maX'] = maX.maX.values

df
Out[1263]: 
             OPEN   HIGH    LOW   LAST     ma5     ma8  ma21  maX
Date                                                             
11/23/2009  88.84  89.19  88.58  88.97     NaN     NaN   NaN  0.0
11/24/2009  88.97  89.07  88.36  88.50     NaN     NaN   NaN  0.0
11/25/2009  88.50  88.63  87.22  87.35     NaN     NaN   NaN  0.0
11/26/2009  87.35  87.48  86.30  86.59     NaN     NaN   NaN  0.0
11/27/2009  86.59  87.02  84.83  86.53  87.588     NaN   NaN  0.0
11/30/2009  87.17  87.17  85.87  86.41  87.076     NaN   NaN  0.0
12/1/2009   86.41  87.53  86.17  86.68  86.712     NaN   NaN  0.0
12/2/2009   86.68  87.49  86.59  87.39  86.720  87.302   NaN  0.0
12/3/2009   87.39  88.48  87.32  88.26  87.054  87.214   NaN  0.0
12/4/2009   88.26  90.77  88.00  90.56  87.860  87.471   NaN  1.0