While social segregation is often assessed in terms of one socio-geographic space, usually place of residence, more recent approaches also incorporate activity-based and, in particular, mobility-based data. This study extends the use of mobility data to measure social segregation between multiple groups by developing a method to connect socio-economic data from the place of residence to mobility data. The method gets applied on the public transport smart card data of Stockholm County, Sweden, using the ordinal information theory index. Applying the index on the destination mix of 2017-2020 smart card data sets for week 5, shows significant differences between income groups' segregation along the radial public transport corridor. The findings also enable to assess the evolution of segregation. In Stockholm, the overall slight decrease in income segregation can be linked to declining segregation in the city center and its public transport hubs. Increasing zonal segregation is related to suburban and rural zones with commuter train stations. This method helps to quantify and thus better understand segregation based on the dynamics of social life. It also allows an evaluation of public transport, which should facilitate potential interaction between social groups.