Learn how to installed third party Python packages using the “conda” tool. You can learn why conda is better than pip when working with scientific packages.
- [Instructor] Let's now try to show the route un-ah-ma. For this, we're going to use a package called folium which uses the open street map project below the hood. Let's try to import it. We'll write import, folium, and execute. And it seems like it's not there. One of Python's mottos is batteries included which means you get a lot of useful packages included in the standard library. However, sometimes we'd like packages that are not in the standard library. Folium is such a library. Actually, Non-PI, Pandas, MatPlotLib, are also not part of the Python standard library.
How did we get these packages, then? Their install is part of the Anaconda install process. If you look at the main page of PyPI, you will see pip is the recommended installer. Pip is a great tool and has a lot of adoption, but for installing scientific packages which have some peculiar requirements, it can be complex to use. We're going to use the Conda tool that comes with Anaconda and was developed specifically to make installing scientific Python packages easier. And trust me, it's much easier to install scientific Python packages with Conda.
The subject of installing packages falls under what Fred Brooks in "The Mythical Man-Month" calls accidental complexity. These are problems that are not really related to the main issues you're trying to solve, but we have to solve them in order to continue. Installing a new package with Conda is very simple. I'll show you how to install a new package with Anaconda navigator UI. Conda can also be used from the command line, and your operation team will probably use it this way. Let's say we need to connect to a Mongo DB server. We'll use the PiMongo package to do that.
Click on environments on the top left, and we'll get the environments a bit later. Then, select the root environment. On the right side, you'll see a list of install packages. Click on the dropdown and change it to not installed. And then, in the search bar on the right, start typing "pym" until you find PyMongo. Select PyMongo and click on apply on the bottom right. Then, click okay.
And now we have PyMongo available. Let's check it out.
- 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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