drop values in a pandas dataframe in a for loop-CodePudding

I'm working with a dataframe which carries daily data from february 2013 to may 2022 and has the following format:

    Unnamed: 0  prod    und proc    tipo    min mcom    max merc    date    year    month   day
0   0   Bacalhau    Cx.25Kg NOR Saith   NaN 437.50  NaN Est 2013/02/01  2013    2   1
1   1   Camarao Kg  NaN 7 Barba NaN NaN NaN Sin 2013/02/01  2013    2   1
2   2   Camarao com casca   Kg  NaN Grande  NaN NaN NaN Sin 2013/02/01  2013    2   1
3   3   Camarao com casca   Kg  NaN Medio   NaN NaN NaN Sin 2013/02/01  2013    2   1
4   4   Camarao com casca   Kg  NaN Pequeno NaN NaN NaN Sin 2013/02/01  2013    2   1
5   5   Peixe de agua salgada   Kg  RS  Albacora    7.80    10.00   10.00   Est 2013/02/01  2013    2   1
6   6   Peixe de agua salgada   Kg  RS-SC   Anchova 8.80    8.80    9.00    Est 2013/02/01  2013    2   1
7   7   Peixe de agua salgada   Kg  RS-SC   Castanha    NaN 5.00    NaN Est 2013/02/01  2013    2   1
8   8   Peixe de agua salgada   Kg  RS-SC   Cavalinha   4.00    4.00    4.38    Est 2013/02/01  2013    2   1
9   9   Peixe de agua salgada   Kg  RS-SC   Cioba   15.98   15.98   16.50   Est 2013/02/01  2013    2   1

doing an explanatory analysis I realized that there are some date that must be removed. These data are in the rows were the month value is '2', the day value is '29' and the year values are '2013', '2014', '2015', '2017', '2018', '2019', '2021' and '2022'.

How removing it row by row would polute so much the code i tried to remove it by using a for loop according to the following command:

anos = [2013,2014,2015,2017,2018,2019,2021,2022]

for df['year'].values in anos:
    df = df.drop(df[(df['month'] == 2) & (df['day'] == 29)].index, inplace= True)

but it didn't work. Could someone help me?

CodePudding user response：

you don't need to loop over it, all can be done in a single statement

df.drop(df[( (df['year'].isin(anos)) &  (df['month'] == 2) & (df['day'] == 29) )].index)

PS: can you post the dataframe example as a csv?

CodePudding user response：

This will do the job without loops:

anos = [2013,2014,2015,2017,2018,2019,2021,2022]
df = df[(df['month'] != 2) | (df['day'] != 29) | ~df['year'].isin(anos)]
df