使用两个条件比较来自两个不同数据框的两列

Question

The context here is that I'm comparing the values of two columns—the key and the date. If the criterion is met, we will now create a new column with the flag = Y else ""

Condition: if key are matching and date in df1 > date in df2 then "Y" else ""

We will therefore iterate through all of the rows in df1 and see if the key matches in df2, at which point we will check dateF and date for that row to see if it is greater, and if it is, we will save "Y" in a new column flag.

Update 1: There can be multiple rows in df1 with same key and different dates

Df1:

Key	Date	Another
123	2022-03-04	Apple
321	2022-05-01	Red
234	2022-07-08	Green

Df2:

Key	Date
123	2022-03-01
321	2022-05-01
234	2022-07-01

Expected O/P: Explanation: as we can see first row and 3rd row key are matching and the DateF in df1 > Date in df2 so Y

Key	Date	Another	Flag
123	2022-03-04	Apple	Y
321	2022-05-01	Red
234	2022-07-08	Green	Y

Code to create all dfs:

import pandas as pd

data = [[123, pd.to_datetime('2022-03-04 '),'Apple'],
[321, pd.to_datetime('2022-05-01 '),'Red'],
[234, pd.to_datetime('2022-07-08 '),'Green']]
df1 = pd.DataFrame(data, columns=['Key', 'DateF', 'Another'])

#df2
data1 = [[123, pd.to_datetime('2022-03-01 ')],
[321, pd.to_datetime('2022-05-01 ')],
[234, pd.to_datetime('2022-07-01 ')]]
df2 = pd.DataFrame(data1, columns=['Key', 'Date'])

Have tried this but i think i am going wrong.

for i in df1.Key.unique():
   df1.loc[(df1[i] == df2[i]) & (r['DateF'] > df2['Date]), "Flag"] = "Y"

Thank You!

Answer 1

You can use pandas.Series.gt to compare the two dates then pandas.DataFrame.loc with a boolean mask to create the new column and flag it at the same time.

df1.loc[df1['Date'].gt(df2['Date']), "Flag"]= "Y"

# Output:

print(df1)

   Key       Date Another Flag
0  123 2022-03-04   Apple    Y
1  321 2022-05-01     Red  NaN
2  234 2022-07-08   Green    Y

Answer 2

You can use merge if your dataframes are not the same size:

final=df1.merge(df2,left_on='Key',right_on='Key',how='left')
final.loc[final['DateF'] > final['Date'], "Flag"]="Y"
final=final.drop(['Date'],axis=1)

    Key DateF   Another Flag
0   123 2022-03-04  Apple   Y
1   321 2022-05-01  Red 
2   234 2022-07-08  Green   Y

Answer 3

This code is not as elegant as the answers, but it also works:

ref_dates   = dict(zip(df2.Key,df2.Date))
df1['Flag'] = ['Y' if date>ref_dates.get(key,'0000-00-00') else '' for key,date in zip(df1.Key,df1.DateF)]

We first create a dictionary ( ref_dates ) with the dates in df2 , and then iterate over df1 comparing them with DateF .