Contents

Python NumPy For Your Grandma - 2.8 Challenge: Gold Miner

Setup

After binge watching the discovery channel, you ditch your job as a trial lawyer to become a gold miner. You decide to prospect five locations underneath a 7x7 grid of land. How much gold do you uncover at each location?

import numpy as np

np.random.seed(5555)
gold = np.random.randint(low=0, high=10, size=(7,7))
print(gold)
## [[2 3 0 5 2 0 3]
##  [8 8 0 7 1 5 3]
##  [0 1 6 2 1 4 5]
##  [4 0 8 9 9 8 7]
##  [4 2 7 0 7 2 1]
##  [9 8 9 2 5 0 8]
##  [1 9 8 2 6 4 3]]
locs = np.array([
    [0,4],
    [2,2],
    [2,3],
    [5,1],
    [6,3]
])

Solution

gold[locs[:, 0], locs[:, 1]]
## array([2, 6, 2, 8, 2])

Course Curriculum

  1. Introduction
    1.1 Introduction
  2. Basic Array Stuff
    2.1 NumPy Array Motivation
    2.2 NumPy Array Basics
    2.3 Creating NumPy Arrays
    2.4 Indexing 1-D Arrays
    2.5 Indexing Multidimensional Arrays
    2.6 Basic Math On Arrays
    2.7 Challenge: High School Reunion
    2.8 Challenge: Gold Miner
    2.9 Challenge: Chic-fil-A
  3. Intermediate Array Stuff
    3.1 Broadcasting
    3.2 newaxis
    3.3 reshape()
    3.4 Boolean Indexing
    3.5 nan
    3.6 infinity
    3.7 random
    3.8 Challenge: Love Distance
    3.9 Challenge: Professor Prick
    3.10 Challenge: Psycho Parent
  4. Common Operations
    4.1 where()
    4.2 Math Functions
    4.3 all() and any()
    4.4 concatenate()
    4.5 Stacking
    4.6 Sorting
    4.7 unique()
    4.8 Challenge: Movie Ratings
    4.9 Challenge: Big Fish
    4.10 Challenge: Taco Truck
  5. Advanced Array Stuff
    5.1 Advanced Array Indexing
    5.2 View vs Copy
    5.3 Challenge: Population Verification
    5.4 Challenge: Prime Locations
    5.5 Challenge: The Game of Doors
    5.6 Challenge: Peanut Butter
  6. Final Boss
    6.1 as_strided()
    6.2 einsum()
    6.3 Challenge: One-Hot-Encoding
    6.4 Challenge: Cumulative Rainfall
    6.5 Challenge: Table Tennis
    6.6 Challenge: Where’s Waldo
    6.7 Challenge: Outer Product

Additional Content

  1. Python Pandas For Your Grandpa
  2. Neural Networks For Your Dog
  3. Introduction To Google Colab