PYTHON

pd if value delete row

df.drop(df.loc[df['line_race']==0].index, inplace=True)

delete rows with value in column pandas

df = df[df.line_race != 0]

drop rows from dataframe based on column value

def filter_rows_by_values(df, col, values):
    return df[~df[col].isin(values)]

removing rows with specific column values from a dataframe

+---+--------------------------+----------------------------------+-----------+
| 1 | Sign up date | no_stores | no_unin_app     no_stores_recei  | ed_order  |
+---+--------------------------+----------------------------------+-----------+
| 2 | 2020-04-01   |      1    |             0                    |   0       |
| 3 | 2020-04-04   |     11    |             3                    |   6       |
| 4 | 2020-04-13   |      8    |             1                    |   4       |
+---+--------------------------+----------------------------------+-----------+

dataframe drop all rows with value

# create a new dataframe CONTAINING ONLY the rows, where the value
# of some_column = some_value
new_df = old_df.loc[old_df['some_column']=='some_value']
# create a new dataframe EXCLUDING the rows, where the value of
# some_column = some_value
new_df = old_df.loc[old_df['some_column']!='some_value']