Learn how to use styles in matplotlib to generate better looking graphs. You can see how to find the available styles and look into a gallery of all styles.
- [Instructor] Let's start with a basic chart…and see how we can customize it to make it look better.…Of course, beauty is in the eye of the beholder…and I usually get someone with a good sense of aesthetics…to give me an opinion before I publish a report.…We'll open a new notebook from the New, Python 3…and then let's name it Style.…When you work in a Jupyter notebook,…we need to tell matplotlib to draw in the notebook.…We do this with a percent matplotlib inline magic.…If you float something and it doesn't show in the notebook,…it probably means that you forgot…to write the matplotlib inline magic.…
If you forgot, you'll probably have to add the magic line…and then reload the notebook or even restart the canal.…Now let's import pandas and NumPy and generate some data.…So import numpy as np…We import pandas as pd, and then…we say that the x's is numpy linear space…from minus six to six and a hundred points.…And the y's is numpy the sinc function of the xs.…
Now let's operate a data frame from this data,…we'll say the data frame is pandas.dataframe.…
- Working with Jupyter notebooks
- Using code cells
- Extensions to the Python language
- Markdown cells
- Editing notebooks
- NumPy basics
- Broadcasting, array operations, and ufuncs
- Folium and Geo
- Machine learning with scikit-learn
- Plotting with matplotlib and bokeh
- Branching into Numba, Cython, deep learning, and NLP
Skill Level Intermediate
NumPy Data Science Essential Trainingwith Charles Kelly3h 54m Intermediate
1. Scientific Python Overview
2. The Jupyter Notebook
3. NumPy Basics
Manage environments5m 11s
6. Folium and Geo
7. NY Taxi Data
10. Other Packages
11. Development Process
Next steps1m 33s
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