Delete Multiple Rows from A Dataset

user_17076299 0
Viewed 132

I want to delete multiple rows where, df.service == 'harvest' or 'http_2873' or 'red_i', but I'm running a for loop and going through the entire df instead

for _ in df1.service:
    i = df1[((df1.service == 'harvest'))].index
    df1.drop(i)
pandas dataframe python
3 Answers

You could exclude the rows that contain any of those strings you listed using str.contains, which allows | (or), and returns a boolean. Then you filter your DataFrame with .loc and ~ negation. :

new = df.loc[~df.Service.str.contains(r'harvest|http_2873|red_i')]

>>> new
          Date Customers Location  Sales Service
12  05/10/2021         A      NSW     12     one
13  03/10/2021         B      NSW     10     two
14  01/10/2021         C      NSW     33   three

You can also include case=False in str.contains('..',case=False) which disregards upper / lower cases in case you want to.

user_91673820

Use this:

df[~((df['Service'] == 'harvest') | (df['Service'] == 'http_2873') | (df['Service'] == 'red_i'))]

.

df
    Date        Customers   Location    Sales   Service
0   2021-10-05  A           NSW         12      harvest
1   2021-10-03  B           NSW         10      http_2873
2   2021-10-01  C           NSW         33      red_i
0   2021-10-05  A           NSW         12      harvest
1   2021-10-03  B           NSW         10      http_2873
2   2021-10-01  C           NSW         33      red_i
0   2021-10-05  A           NSW         12      harvest
1   2021-10-03  B           NSW         10      http_2873
2   2021-10-01  C           NSW         33      red_i
0   2021-10-05  A           NSW         12      harvest
1   2021-10-03  B           NSW         10      http_2873
2   2021-10-01  C           NSW         33      red_i

df[~((df['Service'] == 'harvest') | (df['Service'] == 'http_2873') | (df['Service'] == 'red_i'))]

    Date        Customers   Location    Sales   Service
1   2021-10-03  B           NSW         10      hello
2   2021-10-01  C           NSW         33      hello1
0   2021-10-05  A           NSW         12      hello3
user_156705270

df2 = df[(df['service'] != 'harvest') & (df['service'] != 'http_2873') & (df['service'] != 'red_i')]

Deleting those rows with service which equals harvest or http_2873 or red_i means leaving the rows with service which is not equal to harvest and not equal to http_2873 and not equal to red_i.

You have to assign df to a new DataFrame df2, otherwise you would not get the result you want.

user_164110300
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