I am trying to use iterrows() in a for loop to add data to a new column within a dataframe. However, this sadly produces just a new empty column. I am not entirely sure where I am going wrong here. When you run the code, print(row['Key_words']) output values, so its not like there isn't any data in the new column because there is nothing to add.

I am not sure what's going wrong here. The frustrating part is this has worked just fine for me in the past. I am wondering if there are any revisions to the code/alternative solutions to solve this problem?

Data:

df = pd.DataFrame({'id': {0: 1, 1: 2, 2: 3}, 'name': {0: 'Sandwich Cookies', 1: 'All-Seasons Salt', 2: 'Unsweetened Oolong Tea'}, 'a_id': {0: 'cookies cakes', 1: 'spices seasonings', 2: 'tea'}, 'd_id': {0: 'snacks', 1: 'pantry', 2: 'beverages'}})

Example code:

df['Key_words'] = ''
i = 1
for index, row in df.iterrows():
    row['Key_words'] = list(str(i))
    i = i   1
    print(row['Key_words'])

df

CodePudding user response：

Try this:

df['Key_words'] = ''
i = 1
for index, row in df.iterrows():
    df.loc[index, 'Key_words'] = list(str(i))
    i = i   1
    print(row['Key_words'])

df

CodePudding user response：

This should solve the issue without having to resort to iterating row by row. This assumes that your index is as shown in your post (thus starting from 0).

df['key_words'] = df.apply(lambda x: x.name 1, axis=1)