Python 熊猫：基于一列中的相似值，使用多个数据帧中的值填充数据帧中的空列

我有一个大型数据框，它有两列，但有许多行，因此这只是一个示例：

df1 = {"text":["see you in five minutes.", "she is my friend.", "she goes to school in five minutes.","he is my friend.","that is right.","sky is blue.","sky is yellow."],
       "goal":[" "," "," "," "," "," "," "]}

我还有另外三个不同大小的数据帧，但它们都有df1中文本列中的一些行：

 df2= {"text":["see you in five minutes.", "he is my friend."],
       "second":["num","friend"]}

 df3 = {"text":["she goes to school in five minutes.","she is my friend.","that is right."],
       "third":["num","friend","correct"]}

 df4 = {"text":["sky is blue.","sky is yellow."],
       "fourth":["color","color"]}

我想做的是将“第二”、“第三”和“第四”列合并到df1中，以填充df1中的空列“目标”

 desired output:
 df1 = {"text":["see you in five minutes.", "she is my friend.", "she goes to school in five minutes.","he is my friend.","that is right.","sky is blue.","sky is yellow."],
       "goal":["num","friend","num","friend","correct","color","color"]}

我尝试对每个数据帧进行多次左合并，但输出将显示在不同的列中。是否有一种方法可以立即完成并将其添加到目标列中

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感谢您

使用将数据帧

df2

、

df3

和

df4

连接起来，创建一个映射系列

m

，然后使用此映射系列以及映射

df1

中的文本列：

m = pd.concat([df.set_index('text').iloc[:, 0] for df in (df2, df3, df4)])
df1['goal'] = df1['text'].map(m)

结果:

# print(df1)
                                  text     goal
0             see you in five minutes.      num
1                    she is my friend.   friend
2  she goes to school in five minutes.      num 
3                     he is my friend.   friend
4                       that is right.  correct
5                         sky is blue.    color
6                       sky is yellow.    color