如何进行迭代以在Python和Pandas中将多个列中的虚拟变量从1更改为0?

时间:2016-10-07 23:50:38

标签: python pandas for-loop

我的数据框有超过200列虚拟变量:

Row1 Feature1 Feature2 Feature3 Feature4 Feature5
A    0        1        1        1        0
B    0        0        1        1        1
C    1        0        1        0        1
D    0        1        0        1        0

我想进行迭代以分离每个特征以创建额外的3个数据帧,df1仅包含将第一个特征= 1保持为1并将所有后面的列更改为0而df2仅包含将第二个特征保持为= 1 1并将所有前一列和后一列更改为0.

我已经创建了代码来完成它,但我认为必须有更好的方法来实现它。请帮助我更有效地解决这个问题。谢谢!

以下是我的代码:

for index, row in hcit1.iterrows():
    for i in range(1,261):
        title="feature"+str(i)
        if int(row[title])==1:
            for j in range(i+1,261):
                title2="feature"+str(j)
                hcit1.loc[index,title2]=0          
        else:
            pass

for index, row in hcit2.iterrows():
    for i in range(1,261):
        title="feature"+str(i)
        if int(row[title])==1:
            for j in range(i+1,261):
                title2="feature"+str(j)
                if row[title2]==1:
                for k in range(j+1,261):
                    title3="feature"+str(k)
                    hcit1.loc[index,title3]=0 
                    hcit1.loc[index,title]=0 
    else:
        pass

for index, row in hcit3.iterrows():
    for i in range(1,261):
        title="feature"+str(i)
        if int(row[title])==1:
            for j in range(i+1,261):
                title2="feature"+str(j)
                if row[title2]==1:
                    for k in range(j+1,261):
                        title3="feature"+str(k)
                        if row[title3]==1:
                            for l in range(k+1,261):
                                title4="feature"+str(l)
                                hcit1.loc[index,title4]=0 
                                hcit1.loc[index,title2]=0 
                                hcit1.loc[index,title]=0 
        else:
            pass

for index, row in hcit4.iterrows():
    for i in range(1,261):
        title="feature"+str(i)
        if int(row[title])==1:
            for j in range(i+1,261):
                title2="feature"+str(j)
                if row[title2]==1:
                    for k in range(j+1,261):
                        title3="feature"+str(k)
                        if row[title3]==1:
                            for l in range(k+1,261):
                                title4="feature"+str(l)
                                if row[title4]==1:
                                    for m in range(l+1,261):
                                        title5="feature"+str(m)
                                        hcit1.loc[index,title5]=0 
                                        hcit1.loc[index,title3]=0 
                                        hcit1.loc[index,title2]=0 
                                        hcit1.loc[index,title]=0 
        else:
            pass

1 个答案:

答案 0 :(得分:0)

下面:

df1 = df[df['Feature1'] == 1]
df1.iloc[:, :] = 0
df1.loc[:, 'Feature1'] = 1
df2 = df[df['Feature2'] == 1]
df2.iloc[:, :] = 0
df2.loc[:, 'Feature2'] = 1
df3 = df[df['Feature2'] == 1]
df3.iloc[:, :] = 0
df3.loc[:, 'Feature3'] = 1

那应该是你要找的东西。