join two dataframes on common column

Question

I want to join two data sources, orders and customers:

orders is an SQL Server table:

orderid| customerid | orderdate | ordercost
------ | ----------         


        

Answer 1

I think problem is columns customerid has different dtypes in both DataFrames so no match.

So need convert both columns to int or both to str.

df1['customerid'] = df1['customerid'].astype(int)
df2['customerid'] = df2['customerid'].astype(int)

Or:

df1['customerid'] = df1['customerid'].astype(str)
df2['customerid'] = df2['customerid'].astype(str)

Also is possible omit how='inner', because default value of merge:

merged= pd.merge( df1, df2, on= 'customerid')