all rows in df1 that are NOT in df2

Question

I have a df (df1) that looks like:

df1 = pd.DataFrame([
        [\'YYZ\', \'SFO\', 1],
        [\'YYZ\', \'YYD\', 1],
        [\'YYZ\', \'EWR\', 1],
        [\'Y         


        

Answer 1

• Use merge with indicator=True
• Then use query to strip out only those with 'left_only'

---

df1.merge(
    df2, how='outer', indicator=True
).query('_merge == "left_only"').drop('_merge', 1)

  city1 city2  val
2   YYZ   EWR    1
3   YYZ   DFW    1
4   YYZ   LAX    1
5   YYZ   YYC    1

Answer 2

the ~ symbol reverses the isin and makes it effectively a isnotin

Answer 3

Just ask the question straight in plain English, hmm I mean in plain pandas. "Select all rows in df1 that are not in df2" translates to:

df1[~df1.isin(df2).all(axis=1)]
Out[127]: 
  city1 city2  val
2   YYZ   EWR    1
3   YYZ   DFW    1
4   YYZ   LAX    1
5   YYZ   YYC    1