Gain insights into data science with easy-to-follow, hands-on explanations. Explore essential concepts quickly and efficiently, even without prior statistics knowledge, for a career boost.

GrokkingDataScientist.tar.gz

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Master the skills that can get you a $100K+ salary even if you bunked your statistics classes. 

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Grokking Data Science

 ### 1. Series From Lists and Arrays

A Pandas Series is a *1D* array of indexed data essentially a column. It can be created from a list or an array using the `pd.Series()` method as shown in the code-widget below. 

**Run** the code and **observe** the output to understand the concepts in a hands-on example.

Notice that the standard shorthand for importing Pandas is *pd*.



import pandas as pd 
series = pd.Series([0, 1, 2, 3])
print(series)

From the previous output, we can see that a Series consists of both a sequence of values and a sequence of indices. The values are simply a NumPy array, while the index is an array-like object of type `pd.Index`. Values can be accessed with the corresponding index using the already familiar **square-bracket and slicing notations**:


Python Fundamentals for Data Science

The Fundamentals of Statistics

Machine Learning 101

End-to-End Machine Learning Project

The Real Talk

Pandas Core Components - The Series Object