Mixed types of data for clustering I have the following types of data for clustering - Numeric, Categorical and Latitude Longitude data for a location in one dataframe in python. I would like to know how can I go about doing clustering when the data is mixed to this degree. 

Can I DBSCAN or hierarchical clustering and what do I need to do to convert categorical data to numeric.  Same with geo location data.
You don't need to convert the attributes to numeric data for DBSCAN nor for HAC (hierarchical clustering).

What you need is a distance function.

While there are some such as Gower's, these are just heuristics.

If you want really good results, you need to carefully design a proper distance function that is able to quantify how similar records are for your purpose. This is very much usage dependent, and hence you cannot find the answer already solved for you.