Operate the main scientific computing modules in Python, such as: NumPy, pandas, Matplotlib, etc.
Anaconda introduction:
Anaconda is a Python distribution for scientific computing. It supports Linux, Mac, and Windows systems. It provides package management and environment management functions. It can easily solve the coexistence, switching and various third-party package installation problems of multiple versions of Python. Anaconda uses tools and commands conda to manage packages and environments, and already includes Python and related supporting tools. Conda is a management system for open source packages and virtual environments.
Note: The installation path of Anaconda cannot have spaces
Advantages of Anaconda:
Save time and worry: anaconda greatly simplifies your workflow by managing toolkits, development environments, and Python versions. Not only can the toolkit be easily installed, updated, and uninstalled, but also the corresponding dependency packages can be automatically installed during installation, and different virtual environments can be used to isolate projects with different requirements.
Analysis tool: This is how you advertise yourself on Anaconda's official website: Python tools for enterprise big data analysis, which include more than 720 scientifically related open source packages, which are involved in data visualization, machine learning, deep learning and other aspects. . Not only can it do data analysis, it can even be used in the field of big data and artificial intelligence.
Anaconda Navigator: A graphical user interface for managing toolkits and environments. Many subsequent management commands can also be manually implemented in Navigator
Jupyter Notebook: A web-based interactive computing environment for editing human-readable documents that demonstrate the process of data analysis
Qtconsole: An imitation terminal graphical interface program that can execute IPython. Compared with the Python Shell interface, qtconsole can directly display the graphics generated by the code, realize multi-line code input execution, and built-in many useful functions and functions.
Spyder: An experimental Python language, cross-platform, scientific computing IDE.
Experimental conda management package
Create a new environment command: conda create –n env_name list of packages
For example: conda create –n py2 python=2.7 pandas
Source activate env_name #Enter the environment (Linex and Mac)
activate env_name #Enter the environment (Windows)
Source deactivate env_name #Exit the environment (Linex and Mac)
deactivate env_name #Exit the environment (Windows)
Conda env list #Show all environments by default, one environment is root
Also note that in the window system, experiment activate env_name and deactivate to enter and exit an environment. Similar to Virtualenv, Virtualenvwrapper,
View command: conda list #View all installation packages
conda list python #View Python installation package
conda search search_term
Update command:
Conda update
Conda update python numpy
Delete command: conda remove
Conda remove python scipy