熊猫掉落部分重复

Question

I have 2 dfs:

df1:

    x  y  z
0   1  2  r
1   a  c  2
2  22  g  d

df2:

    x  y  z
0   1  2  r
1   a  b  2
2   3  g  d

I want to drop when column y and z are duplicated.

Desired result:

        x  y  z
    1   a  c  2

Because df1 and df2 both have same values in column y and z

Answer 1

 cols=['y','z']#columns to check for having same value
 df1[~(df1[cols]==df2[cols]).all(axis=1)]#extracting the rows where x and y are `not equal(~)` in both dataframes

Answer 2

Using pd.merge you can do

In [266]: dff = df1.merge(df2, on=['y', 'z'], how='left',  indicator=True,
                          suffixes=['', 'right'])

In [267]: dff.loc[dff['_merge'].eq('left_only'), ['x', 'y', 'z']]
Out[267]:
   x  y  z
1  a  c  2

Answer 3

One solution could be

df1[df1.merge(df2, 'left', ['y', 'z']).x_y.isnull()]

Or, somewhat more low-key,

df1[(df1[['y', 'z']] != df2[['y', 'z']]).any(1)]

Answer 4

Another way to achieve it is using loc

pd.DataFrame(df1.loc[(df1.y != df2.y) | (df1.z != df2.z)])

Output

    x  y  z
1   a  c  2