Installing and Upgrading Windows. There are two ways to install Taurus on Windows. The recommended way is to use the prebuilt installer that will install latest Taurus on your PC. However, if you already have Python installed, you can install Taurus manually with pip, Python package manager. The easiest way to install pandas is to install it as part of the Anaconda distribution, a cross platform distribution for data analysis and scientific computing. This is the recommended installation method for most users. Instructions for installing from source, PyPI, ActivePython, various Linux distributions, or a development version are also provided.

The easiest way to install pandas is to install itas part of the Anaconda distribution, across platform distribution for data analysis and scientific computing.This is the recommended installation method for most users.

Instructions for installing from source,PyPI, ActivePython, various Linux distributions, or adevelopment version are also provided.

Python version support¶

Officially Python 3.5.3 and above, 3.6, and 3.7.

Installing pandas¶

Installing with Anaconda¶

Installing pandas and the rest of the NumPy andSciPy stack can be a littledifficult for inexperienced users.

The simplest way to install not only pandas, but Python and the most popularpackages that make up the SciPy stack(IPython, NumPy,Matplotlib, …) is withAnaconda, a cross-platform(Linux, Mac OS X, Windows) Python distribution for data analytics andscientific computing.

After running the installer, the user will have access to pandas and therest of the SciPy stack without needing to installanything else, and without needing to wait for any software to be compiled.

Installation instructions for Anacondacan be found here.

A full list of the packages available as part of theAnaconda distributioncan be found here.

Another advantage to installing Anaconda is that you don’t needadmin rights to install it. Anaconda can install in the user’s home directory,which makes it trivial to delete Anaconda if you decide (just deletethat folder).

Installing with Miniconda¶

The previous section outlined how to get pandas installed as part of theAnaconda distribution.However this approach means you will install well over one hundred packagesand involves downloading the installer which is a few hundred megabytes in size.

If you want to have more control on which packages, or have a limited internetbandwidth, then installing pandas withMiniconda may be a better solution.

Conda is the package manager that theAnaconda distribution is built upon.It is a package manager that is both cross-platform and language agnostic(it can play a similar role to a pip and virtualenv combination).

Miniconda allows you to create aminimal self contained Python installation, and then use theConda command to install additional packages.

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First you will need Conda to be installed anddownloading and running the Minicondawill do this for you. The installercan be found here

The next step is to create a new conda environment. A conda environment is like avirtualenv that allows you to specify a specific version of Python and set of libraries.Run the following commands from a terminal window:

This will create a minimal environment with only Python installed in it.To put your self inside this environment run:

https://ninreg.netlify.app/mini-mac-25-chainsaw-manual.html. On Windows the command is:

The final step required is to install pandas. This can be done with thefollowing command:

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To install a specific pandas version:

To install other packages, IPython for example:

To install the full Anacondadistribution:

If you need packages that are available to pip but not conda, theninstall pip, and then use pip to install those packages:

Installing from PyPI¶

pandas can be installed via pip fromPyPI.

Installing with ActivePython¶

Installation instructions forActivePython can be foundhere. Versions2.7 and 3.5 include pandas.

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Installing using your Linux distribution’s package manager.¶

The commands in this table will install pandas for Python 3 from your distribution.To install pandas for Python 2, you may need to use the python-pandas package.

However, the packages in the linux package managers are often a few versions behind, soto get the newest version of pandas, it’s recommended to install using the pip or condamethods described above.

Installing from source¶

See the contributing guide for complete instructions on building from the git source tree. Further, see creating a development environment if you wish to create a pandas development environment.

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Running the test suite¶

pandas is equipped with an exhaustive set of unit tests, covering about 97% ofthe code base as of this writing. To run it on your machine to verify thateverything is working (and that you have all of the dependencies, soft and hard,installed), make sure you have pytest >= 4.0.2 and Hypothesis >= 3.58, then run:

Dependencies¶

Recommended dependencies¶

• numexpr: for accelerating certain numerical operations.numexpr uses multiple cores as well as smart chunking and caching to achieve large speedups.If installed, must be Version 2.6.2 or higher.
• bottleneck: for accelerating certain types of nanevaluations. bottleneck uses specialized cython routines to achieve large speedups. If installed,must be Version 1.2.1 or higher.

Note

You are highly encouraged to install these libraries, as they provide speed improvements, especiallywhen working with large data sets.

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Optional dependencies¶

Pandas has many optional dependencies that are only used for specific methods.For example, pandas.read_hdf() requires the pytables package. If theoptional dependency is not installed, pandas will raise an ImportError whenthe method requiring that dependency is called.

Optional dependencies for parsing HTML¶

One of the following combinations of libraries is needed to use thetop-level read_html() function:

• BeautifulSoup4 and html5lib
• BeautifulSoup4 and lxml
• BeautifulSoup4 and html5lib and lxml
• Only lxml, although see HTML Table Parsingfor reasons as to why you should probably not take this approach.

Warning

• if you install BeautifulSoup4 you must install eitherlxml or html5lib or both.read_html() will not work with onlyBeautifulSoup4 installed.
• You are highly encouraged to read HTML Table Parsing gotchas.It explains issues surrounding the installation andusage of the above three libraries.

This guide covers the following topics:

Note

This guide relies heavily on command-line tools.It assumes you are the least familiar with the macOS Terminal application.

Installing Dependencies¶

Install those packages or make sure you have them in your system.

Downloading the Repository¶

Simply check out the Blender Manual’s repository using:

The repository will now be downloaded which may take a few minutes depending on your internet connection.

Setting up the Build Environment¶

• Open a Terminal window.

• Enter the blender_docs folder which was just added by the SVN checkout:

• Inside that folder is a file called requirements.txt which contains a list of all the dependencies we need.To install these dependencies, we can use the pip command:

Note

Every now and then you may want to make sure your dependencies are up to date using:

Continue with the next step: Building.