How to do iterations to change dummy variable in multiple columns from 1 to 0 in Python and Pandas?

Question

I have a dataframe that have over 200 columns of dummy variable:

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

I want to do iteration to separate each feature to create extra 3 dataframes with df1 only contains keep the first feature that=1 as 1 and change all the later columns to 0 and df2 only contains keep the second feature that=1 as 1 and change all the previous and later columns to 0.

I have create codes to do it, but I figured there gotta be better ways to do it. Please help me with a more efficient way to approach this. Thank you!

Below is my code:

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

Answer 1

Here:

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

That should be what you are looking for.