Learn how to combine Pandas plotting with matplotlib. You can also see how to generate interactive charts on the notebook and use IPyWidegts to add controls to Jupyter notebook.
- [Instructor] We saw how to plot attendance,…and we saw how to plot with mat properly.…Now let's see how we can combine them together.…Say we'd like to have pandas plot…on the matplotlib access we created.…We can do this easily by supplying the ax key…with argument to panda's plotting functions.…We'll open a new notebook, and this one we'll call tips.…We're going to use some stock information here,…so the usual matplotlib inline…and import matplotlib.pyplot as plt,…and import pandas as pd.…
And now let's read the data.…df = pd.read_csv( 'lnkd.csv', and, parse_dates=['Date'],…and we'll also set the index column to be the date.…And let's take a look at what we have.…The usual stock information, date, open price,…high price, low price, close and volume.…Now let's create some access.…We're going to use subplots command.…So fig, and (ax1, ax2) = plt.subplots…and this time subplots in plural.…
One row, two column, and the figsize will be 15 and six.…And now we tell the data frame to plot only the April data,…2016-04, and the close column, and plot it…
- 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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