使用 Pandas.query() 方法过滤数据？

Question

I want to filter product_type which is having "others" for all ticket_id and replace "others" with voice.

Sample dataframe

ticket_id  network  product_type

123        AAA      tv
345        AAA      others       
567        BBB      others
678        CCC      others
789        DDD      broad

Expected output

ticket_id  network  product_type

123        AAA      tv
345        AAA      voice       
567        BBB      voice
678        CCC      voice
789        DDD      broad

I tried the below function but it gives an error:

ERROR:root:The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

def product_mapping(df):
    try:
        data = df.query('product_type == "others"')['ticket_id']
        if data:
            data["product_type"] = data["product_type"].replace({"others": "voice"})
            return data
        else:
            return df
    except Exception as error:
        logger.error(error)

Answer 1

try this:

df['product_type'] = df.product_type.str.replace('others', 'voice')

Output:

ticket_id   network product_type
0   123 AAA tv
1   345 AAA voice
2   567 BBB voice
3   678 CCC voice
4   789 DDD broad

You can check if 'others' exist in product_type by:

if 'others' in df.product_type.tolist():
    #there is 'others' in product_type
else:
    #there is no 'others' in product_type

Answer 2

def mapping(df):
    try:
        if 'others' in df.product.tolist():
            df["product"] = df["product"].replace(['others'],'voice')  
            return df
        else:
            return df
        
    except Exception as error:
        logger.error(error)