python dataframe :dropping rows that the value of all column is a certain value

Question

There is a dataframe, like the following :

   id       a            b           c            d              e
    a     23_2_1     34_55_0    34_55_0      -1_-1_-1        34_55_0
    b     3_55_0    34_55_0   34_55_0       34_55_0          34_55_0
    c     -1_-1_-1    34_55_0   34_55_0       34_55_0        -1_-1_-1
    d     34_55_0    -1_-1_-1   34_55_0       34_55_0        34_55_0
    e     34_55_0    34_55_0   34_55_0       34_55_0         34_55_0
    f     34_55_0    34_55_0   34_55_0       34_55_0         34_55_0

I want to delete the rows that if there is value of columns is '-1_-1_-1' in the dataframe, and also extract the id that include the '-1_-1_-1'.

My trying:

lst_col = list(df.columns)[:-1]
df2 = df_bl[~df_bl[lst_col].isin(['-1_-1_-1'])]

John Zwinck · Accepted Answer · 2018-03-31 04:17:59Z

2

First, find the values you care about:

match_cells = df == '-1_-1_-1'

That gives you a DataFrame with True wherever the indicated value is, and False elsewhere.

Now select the rows that have a match:

match_rows = match_cells.any(axis=1)

Then take the rows without matches:

df2 = df[~match_rows]

And get the row labels with matches:

match_ids = df.index[match_rows]

answered Mar 31, 2018 at 4:17

John Zwinck

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