在pandas数据框中，如何检查同一行但不同列中是否存在两个字符串？

Question

So I have been trying to figure out how to write the simplest if statement in order to check if the string "A" exist in the rootID and "B" exist in the parentID in any of the rows. I then want to remove that row. In the following dataframe I would have wanted to remove row 0 in that case.

                     rootID   parentID    jobID  time
                  0    A         B          D    2019-01-30 14:33:21.339469
                  1    E         F          G    2019-01-30 14:33:21.812381
                  2    A         C          D    2019-01-30 15:33:21.812381
                  3    E         E          F    2019-01-30 15:33:21.812381
                  4    E         F          G    2019-01-30 16:33:21.812381

I know how to check if one element exists such as

   if df['rootID'].str.contains("A").any()

but how do I do it when I need to check for two different strings in two columns?

Answer 1

Use boolean indexing with masks chained by | for bitwise OR and ~ for invert boolean masks.

If need check substrings:

m1 = ~df['rootID'].str.contains("A")
m2 = ~df['parentID'].str.contains("B")

If need check strings use Series.ne :

m1 = df['rootID'].ne("A")
m2 = df['parentID'].ne("B")

#alternatives
#m1 = df['rootID'] != "A"
#m2 = df['parentID'] != "B"

---

df = df[m1 | m2]

print (df)
  rootID parentID jobID                        time
1      E        F     G  2019-01-30 14:33:21.812381
2      A        C     D  2019-01-30 15:33:21.812381
3      E        E     F  2019-01-30 15:33:21.812381
4      E        F     G  2019-01-30 16:33:21.812381

Another solution:

df = df.query('rootID != "A" | parentID != "B"')