title: `pd.concat` with `join=='inner'` doesn't produce intersection of pandas dataframes
body: <p>I am trying to extract common rows from several dataframes using pd.concat:</p>
  <pre><code>&gt;&gt;&gt; import numpy as np
  &gt;&gt;&gt; import pandas as pd
  &gt;&gt;&gt; x = np.random.random(size=(5, 3))
  &gt;&gt;&gt; df1 = pd.DataFrame(x)
  &gt;&gt;&gt; df2 = pd.DataFrame(x[1:3])
  &gt;&gt;&gt; df3 = pd.DataFrame(x[2:4])
  &gt;&gt;&gt; df1
            0         1         2
  0  0.257662  0.453542  0.805230
  1  0.060493  0.463148  0.715994
  2  0.452379  0.470137  0.965709
  3  0.447546  0.964252  0.163247
  4  0.187212  0.973557  0.871090
  &gt;&gt;&gt; df2
            0         1         2
  0  0.060493  0.463148  0.715994
  1  0.452379  0.470137  0.965709
  &gt;&gt;&gt; df3
            0         1         2
  0  0.452379  0.470137  0.965709
  1  0.447546  0.964252  0.163247
  </code></pre>
  <p>As you can see, only the row <code>0.452379  0.470137  0.965709</code> is common to all three dataframes. To extract it, I tried:</p>
  <pre><code>&gt;&gt;&gt; pd.concat([df1, df2, df3], join='inner')
            0         1         2
  0  0.257662  0.453542  0.805230
  1  0.060493  0.463148  0.715994
  2  0.452379  0.470137  0.965709
  3  0.447546  0.964252  0.163247
  4  0.187212  0.973557  0.871090
  0  0.060493  0.463148  0.715994
  1  0.452379  0.470137  0.965709
  0  0.452379  0.470137  0.965709
  1  0.447546  0.964252  0.163247
  </code></pre>
  <p>Thus, <code>join==inner</code> doesn't seem to work! I should also point out that <code>ignore_index=True</code> has no effect on the behavior. In <a href="https://realpython.com/pandas-merge-join-and-concat/" rel="nofollow noreferrer">an article</a> on Real Python, using <code>axis=1</code> is suggested. However, it is wrong in my opinion:</p>
  <pre><code>&gt;&gt;&gt; pd.concat([df1, df2, df3], join='inner', axis=1)
            0         1         2         0         1         2         0         1         2
  0  0.257662  0.453542  0.805230  0.060493  0.463148  0.715994  0.452379  0.470137  0.965709
  1  0.060493  0.463148  0.715994  0.452379  0.470137  0.965709  0.447546  0.964252  0.163247
  </code></pre>
  <p>What is wrong with what I am doing? Also, how would I extract common rows from several dataframes if this way doesn't work? I am using Pandas version 0.25.3.</p>