[英]How to check not in on multiple dataframes pandas?
I have the following dataframes. 我有以下数据帧。
import pandas as pd
d={'P':['A','B','C'],
'Q':[5,6,7]
}
df=pd.DataFrame(data=d)
print(df)
d={'P':['A','C','D'],
'Q':[5,7,8]
}
df1=pd.DataFrame(data=d)
print(df1)
d={'P':['B','E','F'],
'Q':[5,7,8]
}
df3=pd.DataFrame(data=d)
print(df3)
Code to check one dataframe column not present in other is this: 用于检查其他数据帧列不存在的代码是:
df.loc[~df['P'].isin(df1['P'])]
How to check the same in multiple columns? 如何在多列中检查相同内容?
How to find P column in df3 not in P column of df and df1? 如何在df3中找到P列而不是在df和df1的P列中?
Expected Output: 预期产出:
P Q
0 E 7
1 F 8
You can chain 2 conditions with &
for bitwise AND
: 您可以使用&
为按位AND
链接2个条件:
cond1 = ~df3['P'].isin(df1['P'])
cond2 = ~df3['P'].isin(df['P'])
df = df3.loc[cond1 & cond2]
print (df)
P Q
1 E 7
2 F 8
Or join values of columns - by concatenate
or join list by +
: 或者连接列的值 - 通过concatenate
或连接列表+
:
df = df3.loc[~df3['P'].isin(np.concatenate([df1['P'],df['P']]))]
#another solution
#df = df3.loc[~df3['P'].isin(df1['P'].tolist() + df['P'].tolist())]
What about, However jezrael already given expert answer :) 怎么样,但是jezrael已经给了专家的答案:)
You can simply define the conditions, and then combine them logically, like: 您可以简单地定义条件,然后在逻辑上将它们组合起来,例如:
con1 = df3['P'].isin(df['P'])
con2 = df3['P'].isin(df1['P'])
df = df3[~ (con1 | con2)]
>>> df
P Q
1 E 7
2 F 8
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