比较两个不同数据帧的“名称”列

Question

actual_df['new_col'] = np.where(lookup_df['name'].str.contains(actual_df['name'] + '-'), lookup_df['name'], 'Not Found')

The above code throws the following error:上面的代码抛出以下错误：

'Series' objects are mutable, thus they cannot be hashed “系列”对象是可变的，因此它们不能被散列

How to do the required lookup with another data frame?如何使用另一个数据框进行所需的查找？

Answer 1

Instead of "str.contains()" method, use slicing, if length of both columns are same.如果两列的长度相同，请使用切片而不是“str.contains()”方法。

actual_df['new_col']= np.where(lookup_df['name'] == actual_df["name"].str[:-1], df2['name2'], 'Not Found')

and if not, use "df.isin()" method of pandas :如果没有，请使用熊猫的“df.isin()”方法：

actual_df['new_col'] = actual_df["name"][actual_df["name"].isin(lookup_df["name"].str[:-1])]