Delete row from DataFrame where value is present in another column and 'col3' == Missing

Question

I am dealing with this example DataFrame:

         A      B        C
1       Cat      0     Missing
2       Dog    Dog     Match
3       Cat    Cat     Match

I would like to remove row[1] as it meets the condition of 'C' == "Missing" and 'A'.isin('B')

Could use help writing this.

Currently I have tried;

if df['C'] == "Missing":
   df = df.loc[~df.A.isin(B)]

But no luck thus far. Thanks.

For row 1, are you checking if 'Cat' appears anywhere in column B, or in exactly row 1 column B? — sjw, Feb 23 '18 at 15:48
@thesilkworm, I am looking for a value in row 1 in column A anywhere in column B, also where row 1 column C equals "Missing" — Kiran J. Mistry, Feb 23 '18 at 15:59

score 0 · Accepted Answer · answered Feb 23 '18 at 15:46

0

This should work:

b = df['B']
df = df[~((df['A'].isin(b)) & (df['C'] == 'Missing'))]

answered Feb 23 '18 at 15:46

sjw

score 0 · Answer 2 · edited Feb 23 '18 at 21:59

0

try df.loc[~(df['C'] == "Missing") & (df['A'].isin(df['B'].unique()))]

edited Feb 23 '18 at 21:59

ktdrv

answered Feb 23 '18 at 16:05

While this code may answer the question, providing additional context regarding **how** and **why** it solves the problem would improve the answer's long-term value. – Alexander Feb 23 '18 at 17:23

2 Answers2