如何检查Pandas中另一个dataframe中是否存在两列的组合值？

Question

I have multiple dfs with two common columns

Sample df

user_id and event_date
abc   |  1st june
abc   |  2nd June
cdf   | 15th july
dfg   | 17th July

I want to check if a user_id on a particular event_date in df1 also exists in df2, df3, df4, and df5

How do I find this?

the following methods I tried but it worked with only taking " user_id " into consideration and not with " event_date "

method 1:

upi_sms =df1.assign(Insms=df2.user_id.isin(df1.user_id).astype(int))

method 2: merging dataframes on = [user_id, event_date]

none of it gives me expected results.

Expected Result:

Combination of abc and 1st June should exist in df2 

How do I achieve this?

Answer 1

I would do it following way, consider simple example:

import pandas as pd
df1 = pd.DataFrame({'x':['A','B','C'],'y':[1,2,3]})
df2 = pd.DataFrame({'x':['C','A','B'],'y':[3,2,1]})
df3 = pd.DataFrame({'x':['A','B','C'],'y':[0,0,0]})

and say you are interested in last row of df1 , ie where x is C and y is 3. Such row is also present in df2 (1st) but not df3 where there is row with x being C but have different.

row = tuple(df1.iloc[-1]) # get last row of df1 as tuple
print(row in df2.itertuples(index=False)) # True
print(row in df3.itertuples(index=False)) # False

Observe it is important to pass index=False as we did not want to take into account where number is inside pandas.DataFrame