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Data are overwrite in pandas how to solve that

Data are overwritten in pandas how to resolve these problem...... How I get out of for loop to solve these problem kindly recommend any solution for that However, with every iteration through the loop, the previously extracted data is overwritten. How can I solve this problem?

from selenium import webdriver
import time
from selenium.webdriver.common.by import By
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver.support.select import Select
from selenium.webdriver.support import expected_conditions as EC
import pandas as pd


# url='https://www.amazon.com/dp/B00M0DWQYI?th=1'
# url='https://www.amazon.com/dp/B010RWD4GM?th=1'
PATH="C:\Program Files (x86)\chromedriver.exe"
driver =webdriver.Chrome(PATH)
df_urls = pd.read_csv('D:/selenium/inputs/amazone-asin.csv',encoding='utf-8')
list_dicts_urls =df_urls.to_dict('records')

item=dict()
product=[]
for url in list_dicts_urls:
    
    product_url = 'https://' + url['MARKETPLACE'] + '/dp/' + url['ASIN']
    driver.get(product_url)


    try:
        item['title'] = driver.find_element(By.CSS_SELECTOR,'span#productTitle').text
    except:
        item['title'] = ''
        
    try:
        item['brand'] = driver.find_element(By.CSS_SELECTOR,'a#bylineInfo').text.replace('Visit the','').replace('Store','').strip()
    except:
        item['brand'] = ''
    try:
        rating = driver.find_element(By.CSS_SELECTOR,'span#acrCustomerReviewText').text.replace('ratings','').strip()
        rating = int(rating.replace(',', ''))
        item['rating'] = rating
    except:
        item['rating'] = ''
        
    time.sleep(2)
    try:
        p1=driver.find_element(By.XPATH, '//span[@class="a-price-whole"]').text
        p2= driver.find_element(By.XPATH, '//span[@class="a-price-fraction"]').text
        item['price']=p1+p2
    except:
        item['price']=''
        
    product.append(item)
    
df=pd.DataFrame(product)
df.to_csv("ama.csv")


source https://stackoverflow.com/questions/74199150/data-are-overwrite-in-pandas-how-to-solve-that

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