python - Pandas DataFrame filtering with condition on other DataFrame, which no longer works on version 0.20.x -


up until pandas version 0.19.2, below filtering worked

df = pd.dataframe(np.random.randn(6,5), columns=list('abcde')) df_filter = pd.dataframe(np.array([[1, 2, 10], [2, 1, 7], [1, 8, 3], [3, 9, 4], [1, 20, 2], [1, 4, 8]]), columns=list('bce')) df[df_filter < 5]

and output of df below (since random)

          b   c   d   e 0   0.257206    0.510411    -0.548331   -0.083934   1.824593 1   -1.534482   -1.073950   0.639955    0.351071    -1.897773 2   0.749863    0.152933    -0.960877   1.162595    0.374817 3   -0.360232   0.479257    0.956225    -0.039248   0.381733 4   -0.519164   0.188241    0.614066    -0.356650   -0.886236 5   0.314688    -1.021030   0.689874    1.723714    -1.487867

also output of df_filter

    b   c   e 0   1   2   10 1   2   1   7 2   1   8   3 3   3   9   4 4   1   20  2 5   1   4   8

and output of df[df_filter < 5]

      b   c   d   e 0   nan 0.510411    -0.548331   nan nan 1   nan -1.073950   0.639955    nan nan 2   nan 0.152933    nan nan 0.374817 3   nan 0.479257    nan nan 0.381733 4   nan 0.188241    nan nan -0.886236 5   nan -1.021030   0.689874    nan nan

however, after pandas version 0.20.x, df[df_filter < 5] no longer works , raises exception.

is there other ways can same filtering did above pandas version 0.19.2 on version 0.20.x?

you might want reindex (df_filter < 5) mask

in [866]: df[(df_filter < 5).reindex(df.index, df.columns, fill_value=false)] out[866]:             b         c   d         e 0 nan -0.269032 -1.129067 nan       nan 1 nan -0.048834  0.373961 nan       nan 2 nan -0.210012       nan nan -0.763331 3 nan -0.767513       nan nan  1.016767 4 nan  0.255832       nan nan -1.494916 5 nan -1.364790  0.345673 nan       nan

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