best python libraries for data science

Chapter I.1. Anaconda (the most famous Python data science platform)Let's start with the Anaconda.What is Anaconda????Reply:(1), Scientific computing platform(2), there are a lot of convenient bags for us to use(3), cross-platform: Mac \linux\windows(4), most importantly: Open source free of charge and community for small friends to exchange2, Installation Anacon

The 1th chapter constructs the experiment environment1-1 guided Video1-2 Anaconda and Jupyter Notebook introduction1-3 Anaconda installation demo on Mac1-4 Anaconda Installing the demo on Windows1-5 Anaconda installation demo on LinuxUse of 1-6 Jupyter-notebook demo2nd Chapter NumPy Introduction2-1 Data Science field 5 common Python libraries2-2 matrix operations

1. Introduction Interactive (interactive) data science and science computing tools, main cell interaction and quick display .It is an Open-source project derived from the IPython.Official Website Address cell interactionAt the command line, interact with the unit of behavior;In the IDE, execute once in the form of a source file.If you want to perform a paragraph

is assigned to BSimilarly:This sequence extension package is valid for all sequence typesNote that there is a boundary condition where Python automatically assigns an empty value to an item that is out of boundsIt is also important to note that the * symbol can only have one, and only one variable is not available *>>> a,*b,*c,d,*e= ' ABCD ' Syntaxerror:two starred expressions in assignment>>> a,b,c,d,e= ' ABCD ' Traceback (most recent): File "If a

with a large number of commonly used data science packages including Conda, Python, NumPy, and more than 150 scientific packages in anaconda. Anaconda was developed on the Conda, and the download file for Anaconda was relatively large (approximately MB), as it came with the most commonly used data

Eleven Python libraries you may not know There are so many Python packages that almost no one can master. Only PyPI can list 47,000 packages separately! Recently, when I heard a lot of data scientists switch to Python, I couldn't help but think that although they have some

Python Libraries might not Knowby Greg | January 20, 2015There is tons of Python packages out there.So many this no one man or woman could possibly catch them all. PyPi alone have over 47,000 packages listed!Recently, with-many data scientists making the switch to Python, I-

library should be larger than the "module". It is true, generally speaking, a "package" inside there will be multiple modules, of course, "library" is a larger concept, such as the Python standard library of each library has a lot of packages, each package has several modules. A package is made up of multiple modules, that is, multiple. py files, so this so-called "package" is a directory we are familiar with. Now you need to solve the problem of ho

Recently, as more and more data scientists began to use Python, I could not help but think that although they benefited from the libraries of Pandas, Scikit-learn and NumPy, they might have missed some of the older but also helpful python libraries. In this blog post, I wil

computing tools. So we excluded Scipy (although we also use it !). Another thing that needs to be mentioned is that we will also evaluate these libraries based on the integration results with other scientific computing libraries, because Machine Learning (supervised or unsupervised) it is also part of the data processing system. If the database you use does not

NumPy is a Python library for scientific computing and is often used in fields such as data mining or machine learning or scientific statistics .In the actual business, in order to play NumPy's high performance, when compiling numpy, it relies on some specially optimized third-party scientific computing libraries. For first-time newcomers to numpy, it is often no

For example, Python's matplotlib library bar, very convenient and even built-in from the Yahoo finance data on the class, even the regular expression do not have to lose ... C + + is a lot less than the library ... Even if there's a lot of code that looks messy (presumably because of the naming rules, I've seen the C + + code that uses Java naming conventions, which is pretty good, so selectively ignoring me), why is Python's library so humane? Reply

Linux different3. Fileinput ModuleUsed to read content in a text file.4. Data collection ModuleIn addition to our most commonly used lists, tuples, dictionaries, these are part of the python built-in language and can be used directly.There are also set, deque and other data structures.5. Time ModuleThe system date time can be obtained, and the date time and stri

(Address.q.person = = p1) >>> addresses >>> list (addresses) [ Storm Storm is a Python ORM that maps objects between a single or multiple databases and Python. To support dynamic storage and retrieval of object information, it allows developers to build complex queries across data tables. It was developed in Pyt