Learn about the Bokeh plotting library which offers interactive features on Jupyter notebooks. You can see how to generate plots and how to generate plots from data and how to synchronize plots together.
New, Python three,…and let's call this one bokeh.…From bokeh.plotting…import output notebook.…And then output notebook.…This is very much like the Matplotlib inline magic we used.…Then let's load some data.…So import pandas es PD…and DF equal pd.read CSV…and we read the stock information…and parse dates equal date.…
And now let's plot.…So from bokeh.plotting,…we'll import figure, and show.…Then we create the figure,…and we say the the X axis type is data,…and we tell the figure to do a line plot of,…the X will be the data frame date,…
- 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
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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