I reccommend that you go over the jupyter notebooks / colab and play beyond.
Some questions that you can answer while doing the work are on each chapter, you can check the solutions here
Ipython is a wonderful way to write new code interactively. I also usually have a text editor (VIM) and Ipython window open in paralell.
Command | Purpose |
---|---|
run scriptName.py | run script |
? | shows docstrings |
?? | shows full code |
whos | shows variables in memory |
Numpy arrays provide you with C-like speed for numerical operations
The Pandas library provides efficient storage and manipulation of dense type arrays in python.
You can define a pandas dataframe as:
Questions:
Matplotlib is a plotting library that was made as a Matlab alternative
you can use a nicer style with axis style
plt.style.use('seaborn-white')
plt.style.use('seaborn-whitegrid') # add grid by default
plt.axis('tight')
plt.axis('equal')
you can also plot error bars
plt.errorbar(x, y, yerr=dy, fmt='.k');
As well as 3D data in 2D plots using
plt.contour
, plt.contourf
, and plt.imshow
Seaborn makes some nicer plots that matplotlib
import seaborn as sns sns.set()