如何执行“(df1& not df2)"数据框在大 pandas 中合并? [英] How to do "(df1 & not df2)" dataframe merge in pandas?
问题描述
我有2个pandas数据帧df1&具有常见列/键(x，y)的df2.
I have 2 pandas dataframes df1 & df2 with common columns/keys (x,y).
我想对键(x，y)进行(df1& not df2)"合并，这意味着我希望我的代码返回仅包含df1& ;不在df2中.
I want to merge do a "(df1 & not df2)" kind of merge on keys (x,y), meaning I want my code to return a dataframe containing rows with (x,y) only in df1 & not in df2.
SAS具有等效功能
data final;
merge df1(in=a) df2(in=b);
by x y;
if a & not b;
run;
谁能优雅地在熊猫中复制相同的功能? 如果我们可以在merge()中指定how ="left-right"，那就太好了.
Who to replicate the same functionality in pandas elegantly? It would have been great if we can specify how="left-right" in merge().
推荐答案
我刚刚升级到10天前发布的版本0.17.0 RC1. 刚刚发现pd.merge()在此新发行版中有一个新的参数，称为indicator = True，可以以Pandonic方式实现这一目标！
I just upgraded to version 0.17.0 RC1 which was released 10 days ago. Just found out that pd.merge() have new argument in this new release called indicator=True to acheive this in pandonic way!!
df=pd.merge(df1,df2,on=['x','y'],how="outer",indicator=True)
df=df[df['_merge']=='left_only']
指示符:在输出数据帧中添加一列称为_merge，其中包含有关每一行源的信息. _merge是分类类型的，对于合并键仅出现在"left"数据帧中的观测值，其观察值取为left_only；对于合并键仅出现在"right"数据帧中的观测值，则取值为right_only；如果在两个观测值中都找到了观察值的合并键，则取值为
indicator: Add a column to the output DataFrame called _merge with information on the source of each row. _merge is Categorical-type and takes on a value of left_only for observations whose merge key only appears in 'left' DataFrame, right_only for observations whose merge key only appears in 'right' DataFrame, and both if the observation’s merge key is found in both.
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