preface
In the field of machine learning and data analysis, Python is a useful tool. Python syntax is concise, and there are many Python libraries. In daily use, we will use many Python packages, such as NumPy, Pandas, etc. We can choose to download one by one. This can be done using Python’s package manager PIP, but Anaconda makes it easier to download one package at a time.
Introduction to the
reference
Anaconda is a free, open source Python and R language distribution for computing science (data science, machine learning, big data processing, and predictive analytics). Anaconda is dedicated to simplifying package management systems and deployment. Anaconda packages are managed using the software package management system Conda. More than 12 million people use Anaconda distributions, and Anaconda has more than 1,400 data science packages for Windows, Linux, and MacOS.
Anaconda has over 1400 software packages. It includes Conda and virtual environment management, both of which are included in the Anaconda Navigator, so users don’t need to know about installing each library separately. You can use the conda install or PIP install commands included in Anaconda to install the open source software package from the Anaconda repository. Pip provides most of the functionality of Conda, and in most cases both can be used together. You can also use the conda build command to build custom packages and then share them with others by uploading them to the Anaconda Cloud, PyPI, or other repositories.
The installation
Anaconda
The Anaconda installation interface lists downloaders for different operating systems, and install them as required. (It is worth noting that MacOS Big Sur may fail to be installed due to a non-compatible operating system, but it is surprising that the software is installed and opens normally.) You can solve your own problems in the actual process.)
After installation, we verify:
PyCharm
Click Download on PyCharm’s official website to Download and configure it.
configuration
If a Python environment is already installed locally, Virtualenv is selected by default when you create a new project
After clicking Create to generate the project file, let’s click on the console below:
If we want to use Conda, we need to configure it at creation time, which can be changed after using the default configuration
To create a new project, we click the button on the right:
Then select the Python file in the AnaConda folder
Click the console again after the project is successfully created, and the icon changes and you can import some libraries
