Joins

SQL JOIN LEFT

df_Join = pd.merge(df1, df2, left_on='Email', right_on='email', how='left')[['Email', 'source']]

Another example:

df_Merged = df1.merge(df2, on='id', how='left')

Another example to find the non-matching records on 2 fields:

df_join = pd.merge(df1, df2, left_on=['id1', 'field1'], right_on=['id2', 'field2'], how='left')[['id1', 'field1', 'field2']]
df_NoMatch = df_join[df_join['field2'].isna()]

SQL INNER JOIN

df_Join = pd.merge(df1, df2, on='Email')

Or:

df_Merged = df1.merge(df2, on='id', how='inner')

Find difference

df_difference = pd.DataFrame(df_First[~df_First['Email'].isin(df_Second['email'])])