text: Title: Better data type detection for pre_aggregated, indexed dataframes
  Body: When a dataframe is pre-aggregated, our type detection based on cardinality often fail to detect the type correctly. For example, when the dataset size is small (often the case when data is pre-aggregated), nominal fields would get recognized as a `quantitative` type.
  ```
  df = pd.read_csv("lux/data/car.csv")
  df["Year"] = pd.to_datetime(df["Year"], format='%Y') # change pandas dtype for the column "Year" to datetype
  a = df.groupby("Cylinders").mean()
  
  a.data_type
  ```
  <img src="https://user-images.githubusercontent.com/5554675/90112958-3f428600-dd83-11ea-9645-187788fb29e3.png" width=250></img>
  
  As a related issue, we should also support the detection of types for named index, for example, in this case, `Cylinders` is an index, so its data type is not being computed.