I am trying to delete the specific rows(MB, DT) of a cloumn("TYPE") from a dataframe in python. Can anyone provide the answer

Question

The column("TYPE) contains "IL", "FC", "DT", "MB".

test_data = test_data.drop(test_data[test_data.Type !='IL', 'FC'])

Does this answer your question? [How to filter Pandas dataframe using 'in' and 'not in' like in SQL](https://stackoverflow.com/questions/19960077/how-to-filter-pandas-dataframe-using-in-and-not-in-like-in-sql) — ScootCork, Jul 22 '20 at 15:07

kostas_math · Answer 1 · 2020-07-22T16:32:10.183

Let's say that your dataframe has the index column and the TYPE column only

data = {'TYPE':['IL', 'FC', 'DT', 'MB']}
df = pd.DataFrame(data)
df
  TYPE
0   IL
1   FC
2   DT
3   MB

If you want to delete DT, MB rows (2,3) then you can choose one of the following (not the only ones) :

df1 = df[:2]
df1
  TYPE
0   IL
1   FC

By droping the values based on their index. Add inplace=True in order to be permanent.

df.drop(df.index[[2,3]], inplace = True)

Return only the desired rows. You can assign it to a new dataframe. This is the closer one to what you were trying I think.

df2 = df[(df['TYPE']!='DT') & (df['TYPE']!='MB')]
df2    
  TYPE
0   IL
1   FC

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