在第一个数据帧中的值是另一个数据帧中的值的子字符串的条件下合并两个数据帧

Question

所以假设我有一个retailer_info这样的数据框：    price   product_name    url0   5005    Intel Pentium Gold G5400 3.70 GHz Processor https://www.theitdepot.com/details-Intel+Penti...1   7150    Intel Core i3-9100F 3.60 GHz Processor  https://www.theitdepot.com/details-Intel+Core+...2   8210    AMD Ryzen 3 2200G with Radeon Vega 8 Graphics   https://www.theitdepot.com/details-AMD+Ryzen+3...3   8415    AMD Ryzen 3 3200G with Radeon Vega 8 Graphics   https://www.theitdepot.com/details-AMD+Ryzen+3...4   10330   AMD Ryzen 5 1600 3.2 GHz Processor  https://www.theitdepot.com/details-AMD+Ryzen+5...我有另一个数据框，cpu_info如下所示：    Type    Part Number Brand   Model   Rank92  CPU YD1600BBAEBOX   AMD Ryzen 5 1600    9396  CPU YD250XBBM4KAF   AMD Ryzen 5 2500X   97108 CPU YD3200C5FHBOX   AMD Ryzen 3 3200G   109129 CPU YD150XBBAEBOX   AMD Ryzen 5 1500X   130138 CPU YD2400C5FBBOX   AMD Ryzen 5 2400G   139139 CPU YD2200C5FBBOX   AMD Ryzen 3 2200G   140153 CPU YD130XBBAEBOX   AMD Ryzen 3 1300X   154现在对于系列中的每个值cpu_info['Model']，我需要检查它是否是系列中任何值的子字符串，retailer_info['product_name']如果是，我想将urldf中的列合并retailer_info到 dataframe cpu_info。预期结果：    Type    Part Number Brand   Model   Rank    url92  CPU YD1600BBAEBOX   AMD Ryzen 5 1600    93  https://www.theitdepot.com/details-AMD+Ryzen+5...96  CPU YD250XBBM4KAF   AMD Ryzen 5 2500X   97  NaN108 CPU YD3200C5FHBOX   AMD Ryzen 3 3200G   109 https://www.theitdepot.com/details-AMD+Ryzen+3...129 CPU YD150XBBAEBOX   AMD Ryzen 5 1500X   130 NaN138 CPU YD2400C5FBBOX   AMD Ryzen 5 2400G   139 NaN139 CPU YD2200C5FBBOX   AMD Ryzen 3 2200G   140 https://www.theitdepot.com/details-AMD+Ryzen+3...153 CPU YD130XBBAEBOX   AMD Ryzen 3 1300X   154 NaN我意识到new_df = pd.merge(cpu, it['product_name', 'url'], on='', how='left')仅当您只想基于列值进行合并时才有效。我不确定如何达到我想要的结果。我真的很感激任何帮助。谢谢。

Answer 1

可以添加多个条件：

dicc = pd.Series(retailer_info["url"].values,index=retailer_info["product_name"]).to_dict()

cpu_info["url"] = ""

for index, row in cpu_info.iterrows():

    for key in dicc:

        if row["Brand"] in key and row["Model"] in key:

            cpu_info.at[index, "url"] = dicc[key]

            break

Answer 2

尝试这个。它应该工作

def find_url(model_name):

    try:

        return retailer_info[retailer_info['product_name'].str.contains(model_name)]['address'].values[0]

    except:

        return None

cpu_info['url'] = cpu_info['Model'].apply(model_name)