Python 基于数据帧中另一个数据帧的掩码值在数据帧中生成NaN
我有一个数据框Python 基于数据帧中另一个数据帧的掩码值在数据帧中生成NaN,python,python-3.x,pandas,python-2.7,dataframe,Python,Python 3.x,Pandas,Python 2.7,Dataframe,我有一个数据框 df1 = pd.DataFrame([["A",1,98,56,51], ["B",1,99,74,36], ["C",1,97,82,83],["B",1,96,31,90], ["C",1,45,92,12], ["A",1,67,33,55]], columns=["id","date","c1"
df1 = pd.DataFrame([["A",1,98,56,51], ["B",1,99,74,36], ["C",1,97,82,83],["B",1,96,31,90], ["C",1,45,92,12], ["A",1,67,33,55]], columns=["id","date","c1","c2","c3"])
我有另一个数据帧具有相同的列名
df2 = pd.DataFrame([["A",1,False,False,True], ["B",1,False,False,True], ["C",1,False,False,False],["B",1,False,True,False], ["C",1,True,False,True], ["A",1,False,True,False]], columns=["id","date","c1","c2","c3"])
我想要一个数据帧df_out,其中值在df2中为True,在df1中替换为blank/nan,如果为False,则保持在df1中的状态
预期输出:
df_out = pd.DataFrame([["A",1,98,56, ""], ["B",1,99,74,""], ["C",1,97,82,83],["B",1,96,"",90], ["C",1,"",92,""], ["A",1,67,"",55]], columns=["id","date","c1","c2","c3"])
如何操作?尝试使用
where
l = ['c1','c2','c3']
df1[l] = df1[l].where(df2[l]==False,'')
df1
Out[199]:
id date c1 c2 c3
0 A 1 98 56
1 B 1 99 74
2 C 1 97 82 83
3 B 1 96 90
4 C 1 92
5 A 1 67 55