Pandas sub columns

|     Start      |       Intermediary       |        End        |
|       |        |            |             |         |         |
_________________________________________________________________
| s_lat | s_lng  |  i_lat     |  i_lng      | e_lat   | e_lng   |

mux = pd.MultiIndex.from_product([['Start','Intermediary','End'], ['lat','lng']])
df = pd.DataFrame(data, columns=mux)

Source: stackoverflow.com

Pandas sub dataframe

age_sex = titanic[["Age", "Sex"]]

Source: pandas.pydata.org

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