如何比较两个 dataframe 列并将第三列值提取为 python 中的 output

Question

I have two dataframes as shown below

df1:

subject
laptop issue
password reset
account unlock
...

df2:

key                       Automation    
reset password              70%
lock account                50%
unlock                      70%
...

I want to take first row from dataframe (df1) and check with "key" column in df2. check if all the words from first row appears in df2 ("key" column). For eg laptop issue is not there in df2, whereas password reset appears in df2.

when "password reset" matches with the df2, its respective "Automation" value has to be printed as output in a separate column in df1.

so df1 will look like:

df1:

subject                    Automation
laptop issue                   0%
password reset                 70%
account unlock                 0%

How I should go ahead with this in python.

words in a sentence can be in any order. not necessary it should be the same sentence.

Answer 1

The below will work for exact ordered/unordered matches by creating sorted keys to match with the subjects:

import pandas as pd

df = pd.DataFrame({"subject":["laptop issue","password reset","account unlock"]})
df2 = pd.DataFrame({"key":["lock account","reset password","unlock"],
                    "Automation":["50%","70%","70%"]})

df["new"] = df["subject"].apply(lambda x: " ".join(sorted(x.split())))
df2["new"] = df2["key"].apply(lambda x: " ".join(sorted(x.split())))

print (df.merge(df2,on="new",how="left").fillna("0%").drop(columns=['new', 'key']))

#
          subject Automation
0    laptop issue         0%
1  password reset        70%
2  account unlock         0%