Compare pandas dataframes and check overlaps?

Question

I am trying myself out at spame filters. I tried several methods to label text files as spam. As a result, I have three dataframes. They basically look like this:

df_method_1 = pd.DataFrame({'file': ['A','B' ,'C'], 'spam': ['1', '0', '0']})
df_method_2 = pd.DataFrame({'file': ['A','B' ,'C'], 'spam': ['1', '1', '0']})
df_method_3 = pd.DataFrame({'file': ['A','B' ,'C'], 'spam': ['1', '1', '0']})

I am now trying to creat a dataframe showing, if a file was labled as spam and if so by which method.

In the best case, I can create a dataframe containing the following infortmation:

df_summary = pd.DataFrame({'file': ['A','B' ,'C'], 'spam': ['All methods', 'Method 2 & Method 3', 'No method']})

Obviously, I am looking for the information. No need for the actual strings.

I tried pandas.DataFrame.isin() to make it happen. But I failed. Any ideas how to do this?

andrew_reece · Accepted Answer · 2017-08-24 15:30:30Z

1

How about merge()?

df1.merge(df2, on="file").merge(df3, on="file")
  file spam_x spam_y spam
0    A      1      1    1
1    B      0      1    1
2    C      0      0    0

answered Aug 24, 2017 at 15:30

andrew_reece

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