What is Pandas?
pandas provide rich data structures and functions designed to make working with structured data fast, easy, and expressive. It is, as you will see, one of the critical ingredients enabling Python to be a powerful and productive data analysis environment. The primary object in pandas that will be used in this book is the DataFrame, a two�dimensional tabular, column-oriented data structure with both row and column labels: >>>
frame total_bill tip sex smoker day time size
1 16.99 1.01 Female No Sun Dinner 2
2 10.34 1.66 Male No Sun Dinner 3
3 21.01 3.5 Male No Sun Dinner 3
4 23.68 3.31 Male No Sun Dinner 2
5 24.59 3.61 Female No Sun Dinner 4
6 25.29 4.71 Male No Sun Dinner 4
7 8.77 2 Male No Sun Dinner 2
8 26.88 3.12 Male No Sun Dinner 4
9 15.04 1.96 Male No Sun Dinner 2
10 14.78 3.23 Male No Sun Dinner 2
pandas combine the high-performance array-computing features of NumPy with the flexible data manipulation capabilities of spreadsheets and relational databases (such as SQL). It provides sophisticated indexing functionality to make it easy to reshape, slice and dice, perform aggregations, and select subsets of data. pandas is the primary tool that we will use in this book.
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