Filling missing values with the value above-CodePudding

I have a dataframe with some missing values. I need to update one 'nan' value with the last value not 'nan' in a row.

Example:

    nome
0   ESTAMPA DIGITAL 1
1   nan
2   nan
3   nan
4   nan
5   ESTAMPA DIGITAL 2
6   nan
7   nan
8   nan
9   nan

need to produce something like this:

    nome
0   ESTAMPA DIGITAL 1
1   ESTAMPA DIGITAL 1
2   ESTAMPA DIGITAL 1
3   ESTAMPA DIGITAL 1
4   ESTAMPA DIGITAL 1
5   ESTAMPA DIGITAL 2
6   ESTAMPA DIGITAL 2
7   ESTAMPA DIGITAL 2
8   ESTAMPA DIGITAL 2
9   ESTAMPA DIGITAL 2

current code is:

for index, row in df_produtos.iterrows():
    is_null = pd.isnull(row['nome'])
    if is_null == False:
        nome = row['nome']
        print(nome)
    elif is_null == True:
        row['nome'] = nome

But it's not working. Somebody can help please? PS: the print(nome) is printing only "valid" values that is not 'nan'. But it's not setting the new value.

CodePudding user response：

Try using .ffill() to forward fill the NaN values, as follows:

df_produtos['nome'] = df_produtos['nome'].ffill()