Sure thing. For slicing, see Jake VanderPlas's book: https://jakevdp.github.io/PythonDataScienceHandbook/03.02-data-indexing-and-selection.html https://jakevdp

Sure thing. For slicing, see Jake VanderPlas's book: https://jakevdp.github.io/PythonDataScienceHandbook/03.02-data-indexing-and-selection.html https://jakevdp.github.io/PythonDataScienceHandbook/03.02-da...) that describes the complexities -- some kinds of pandas slicing include the last index, some kinds don't. View vs copy is even worse. There are some situations where indexing on a DataFrame yields a view, some situations where it yields a copy, and they are effectively indeterminate in a lot of situations. From the Pandas documentation https://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy https://pandas.pydata.org/pandas-docs/stable/indexing.html#i...: See that __getitem__ in there? Outside of simple cases, it’s very hard to predict whether it will return a view or a copy (it depends on the memory layout of the array, about which pandas makes no guarantees), and therefore whether the __setitem__ will modify dfmi or a temporary object that gets thrown out immediately afterward. By contrast, the vanilla python rules are much simpler: slicing always leaves off the last index, and the rules for view vs copy of mutable data structures like lists are at least determinate...