比较两个数据帧上的列

Question

I have two dataframes that look like:

import pandas as pd

f1 = {'entity':['X','Y','Z'],'instrument':['A','B','C'],'Function':['Rates','FX','Rates'],'amt':[1,2,3]}
df1 = pd.DataFrame(data=f1)

f2 = {'entity':['X','Y','Z'],'instrument':['A','B','C'],'Depot':['A','A','B'],'amt':[1,2,3]}
df2 = pd.DataFrame(data=f2)

When I try to iterate over the columns of the two dataframes, I get an error. Any ideas why ?

common_cols=['entity','instrument']
common_cols_iter=iter(common_cols)

for index1,row1 in df1.iterrows():
    for index2,row2 in df2.iterrows():
        if row1[next(common_cols_iter)]==row2[next(common_cols_iter)]:
            print("common")
        else:
            print("not")

I am trying to achieve:

for index1,row1 in df1.iterrows():
    for index2,row2 in df2.iterrows():
        if (row1['entity']==row2['entity'] and row1['instrument']==row2['instrument']):
            print("common")
        else:
            print("not")

Answer 1

Why dont you iterate over columns using a for?

common_cols=['entity','instrument']
common_cols_iter=iter(common_cols)

def check_cond(row1,row2):
    for col in common_cols:
        if row1[col] != row2[col]:
            return False
    return True

for index1,row1 in df1.iterrows():
    for index2,row2 in df2.iterrows():
        if check_cond(row1,row2):
            print("common")
        else:
            print("not")

Answer 2

next(common_cols_iter)

只会在您的代码中工作两次，之后它会说停止迭代。