NumPy and Pandas Overview

Flashcards covering key concepts about NumPy and Pandas libraries in Python for numerical computation and data analysis.

NumPy

A fundamental library for numerical computing in Python that stands for Numerical Python.

ndarray

The ndarray type is a mutable container in NumPy where all elements must be of the same type.

reshape()

A function in NumPy that changes the shape of an array without changing its data.

ravel()

A function in NumPy that returns a flattened array.

insert()

A function in NumPy that inserts values along a specified axis of an array.

zeros()

A function in NumPy that creates an array filled with zeros.

ones()

A function in NumPy that creates an array filled with ones.

Pandas

A powerful Python library for data analysis, built on top of NumPy.

Series

A one-dimensional array-like object in Pandas that contains data with associated indexes.

DataFrame

A two-dimensional, size-mutable, potentially heterogeneous tabular data structure in Pandas.

NaN

Represents a null value or missing data in a Pandas Series.

Element-wise addition

An arithmetic operation in NumPy where two arrays are added together element by element.

Element-wise subtraction

An arithmetic operation in NumPy where one array is subtracted from another array element by element.

Element-wise multiplication

An arithmetic operation in NumPy where two arrays are multiplied together element by element.

Element-wise division

An arithmetic operation in NumPy where one array is divided by another array element by element.

Mathematical functions in NumPy

Functions such as sqrt(), log(), sin(), max(), and median that operate on array elements.