Error df1 must have all columns from join_columns

[bukreevai]

I try compare two pandas dataframes

                comparer = datacompy.Compare(
                    source_df,
                    target_df,
                    join_columns=fields_list,  #You can also specify a list of columns
                    abs_tol=0.01, #Optional, defaults to 0
                    rel_tol=0, #Optional, defaults to 0
                    df1_name='SOURCE', #Optional, defaults to 'df1'
                    df2_name='TARGET' #Optional, defaults to 'df2'
                    )

head of my DFs:
df1:

     user_id  type currency  amount
0  133265969     1      EUR      10
1  133265975     1      EUR  695.99
2  133266265     1      EUR       0
3  133266266     4      USD   10000
4  133266267     1      EUR  274.24
5  133266268     1      EUR  274.24
6  133266269     4      USD   10000
7  133266270     1      GBP   99.99
8  133266271     1      EUR   99.99
9  133266272     1      GBP   99.99

df2:

     user_id  type currency  amount
0  133265969     4      EUR   10000
1  133265969     1      EUR      10
2  133265975     4      USD   10000
3  133265975     1      EUR  695.99
4  133266265     1      EUR       0
5  133266265     4      USD   10000
6  133266266     1      USD       0
7  133266266     4      USD   10000
8  133266267     4      USD   10000
9  133266267     1      EUR  274.24

dtypes of my DFs:
df1

user_id      int64
type         int64
currency    object
amount      object
dtype: object

df2:

user_id      int64
type         int64
currency    object
amount      object

And I has Error: df1 must have all columns from join_columns

What is it incorrect?

[fdosani]

What is the value of fields_list?

[fdosani]

@bukreevai Feel free to reopen. I'm closing this for now since there hasn't been an update.