NumPy

Unlock the power of data science in Python 
Section 1: Introduction
01 Welcome.mov
2 mins
02 What is NumPy?
7 mins
03 Installing NumPy
10 mins
04 Importing NumPy
7 mins
Section 2: Basic NumPy arrays
NumPy course, section 2.ipynb
49.5 KB
05 What is a NumPy array?
5 mins
06 Creating NumPy arrays
9 mins
07 Exercises 1
1 min
exercises-1.txt
291 Bytes
08 Exercise solutions 1
3 mins
09 Generating random arrays
5 mins
09a Random seeds.mp4
3 mins
10 Vectorized operations.mp4
6 mins
11 Vectorized operations with two arrays.mp4
3 mins
12 Commonly used methods.mp4
5 mins
13 Exercises 2.mp4
2 mins
exercises-2.txt
471 Bytes
14 Exercise solutions 2.mp4
5 mins
Section 3: Indexing
NumPy course, section 3.ipynb
34.8 KB
15 Fancy indexing.mp4
4 mins
16 Boolean indexing.mp4
3 mins
17 Views vs copies.mp4
6 mins
18 Selecting with boolean indexes.mp4
6 mins
19 Evens and odds.mp4
3 mins
20 Exercises 3.mp4
2 mins
exercises-3.txt
327 Bytes
21 Exercise solutions 3.mp4
4 mins
22 Complex conditions.mp4
7 mins
23 Exercises 4.mp4
1 min
exercises-4.txt
224 Bytes
24 Exercise solutions 4.mp4
4 mins
25 Assigning via indexes.mp4
4 mins
26 Exercises 5.mp4
1 min
exercises-5.txt
422 Bytes
27 Exercise solutions 5.mp4
5 mins
Section 4: Data types
NumPy course, section 4.ipynb
41.5 KB
28 dtypes
8 mins
29 Setting dtypes
7 mins
30 Setting the dtype attribute
4 mins
31 Using astype
4 mins
32 String lengths
3 mins
33 Exercises 6
2 mins
exercises-6.txt
415 Bytes
34 Exercise solutions 6
5 mins
35 Complex numbers.mp4
3 mins
36 Booleans vs. integers.mp4
3 mins
37 Setting print options.mp4
5 mins
Section 5: nan
NumPy course, section 5.ipynb
28.2 KB
38 The need for nan.mp4
7 mins
39 Filtering with isnan.mp4
5 mins
40 Making sure that nan will work in your array.mp4
3 mins
41 Replacing nan values with the mean.mp4
3 mins
42 Exercises 7.mp4
1 min
exercises-7.txt
214 Bytes
43 Exercise solutions 7.mp4
3 mins
44 inf and nan.mp4
5 mins
Section 6: Multidimensional NumPy
NumPy course, section 6.ipynb
72.7 KB
45 Array shapes.mp4
10 mins
46 Multi-dimensional retrievals.mp4
7 mins
47 Exercises 8.mp4
2 mins
exercises-8.txt
374 Bytes
48 Exercise solutions 8.mp4
5 mins
49 Assigning to 2d arrays.mp4
7 mins
50 Axes and NumPy methods.mp4
6 mins
51 argmin and argmax.mp4
5 mins
52 Flattening arrays.mp4
4 mins
53 Transposing.mp4
3 mins
54 Sorting.mp4
6 mins
55 Concatenating arrays.mp4
5 mins
56 Exercises 9
1 min
exercises-9.txt
461 Bytes
57 Exercise solutions 9
4 mins
Section 7: Input and output
58 Intro to NumPy IO
4 mins
59 Storing with np.save
6 mins
60 Loading with np.load
4 mins
61 mmap_mode
5 mins
62 Saving and loading npz
6 mins
63 Storing CSV files with np.savetxt
5 mins
64 Loading CSV files with np.loadtxt
5 mins
65 Exercises 10.mp4
1 min
NumPy course, section 7.ipynb
51.4 KB
66 Exercise solutions 10.mp4
4 mins
Section 8: Matplotlib
NumPy course, section 8.ipynb
164 KB
67 Intro to Matplotlib.mp4
4 mins
68 Basic plots.mp4
5 mins
69 Format strings.mp4
4 mins
70 Bar plots.mp4
3 mins
71 Histograms.mp4
2 mins
72 Pie plots.mp4
2 mins
73 Exercises 11.mp4
2 mins
exercises-11.txt
440 Bytes
cisco_stock.csv
1.3 KB
74 Exercise solutions 11.mp4
5 mins
Section 9: Conclusion
Conclusion
2 mins
PDFs of slides
01 Data science intro
386 KB
02 Jupyter notebook
269 KB
03 NumPy
96 KB
04 NumPy indexes
45.5 KB
05 NumPy's nan
36.2 KB
06 NumPy and multidimensional arrays
37.4 KB
07 NumPy and input-output
34.7 KB