Dictionaries are one of python's default data structures which allow you to store key: value pairs and offer some built-in methods to manipulate your data, which you can read on the docs (here is a good summary to jump start your reading process). Panda's Series are one-dimensional ndarrays with axis-labels, which allow you to store array-like, dict, or scalar values and are one of numpy's (a scientific computing python library) built-in data structures. If you read the docs provided above (see: Panda's Series link) you will notice that they come with a vast amount of methods and attributes quite different, for the most part, from those of a python dictionary. So it is not just a syntax difference to say the least. If you only need to store some key:value pairs, your best and more elegant solution is to use the default dictionary. If you need to make some complex data manipulation on the stored data, then consider using panda's series