WARNING: for a modern macOS (2019) this can install python3, and for python2 you really need to do: brew install python@2. Install python3: brew install python3 UPDATE: Python 3. If you install python3, pip will be installed automatically. Brew install python3 NEW 2019: now to use pip version 3, use pip3, or you can execute: python3, to use. If you’re unsure of which datasets/models you’ll need, you can install the “popular” subset of NLTK data, on the command line type python -m nltk.downloader popular, or in the Python interpreter import nltk; nltk.download(‘popular’).
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 3.6.1 and above, 3.7, 3.8, and 3.9.
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.
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:
On Windows the command is:
The final step required is to install pandas. This can be done with thefollowing command:
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, 3.5 and 3.6 include pandas.
Installing using your Linux distribution’s package manager.¶
The commands in this table will install pandas for Python 3 from your distribution.
Distribution | Status | Download / Repository Link | Install method |
---|---|---|---|
Debian | stable | sudoapt-getinstallpython3-pandas | |
Debian & Ubuntu | unstable (latest packages) | sudoapt-getinstallpython3-pandas | |
Ubuntu | stable | sudoapt-getinstallpython3-pandas | |
OpenSuse | stable | zypperinpython3-pandas | |
Fedora | stable | dnfinstallpython3-pandas | |
Centos/RHEL | stable | yuminstallpython3-pandas |
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 conda
methods described above.Handling ImportErrors¶
Python Install For Mac High Sierra
If you encounter an ImportError, it usually means that Python couldn’t find pandas in the list of availablelibraries. Python internally has a list of directories it searches through, to find packages. You canobtain these directories with:
One way you could be encountering this error is if you have multiple Python installations on your systemand you don’t have pandas installed in the Python installation you’re currently using.In Linux/Mac you can run
whichpython
on your terminal and it will tell you which Python installation you’reusing. If it’s something like “/usr/bin/python”, you’re using the Python from the system, which is not recommended.It is highly recommended to use
conda
, for quick installation and for package and dependency updates.You can find simple installation instructions for pandas in this document: installation instructions </getting_started.html>.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.
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 >= 5.0.1 and Hypothesis >= 3.58, then run:
Dependencies¶
Package | Minimum supported version |
---|---|
24.2.0 | |
1.15.4 | |
2.7.3 | |
2017.2 |
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
nan
evaluations.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.
Optional dependencies¶
Pandas has many optional dependencies that are only used for specific methods.For example,
pandas.read_hdf()
requires the pytables
package, whileDataFrame.to_markdown()
requires the tabulate
package. If theoptional dependency is not installed, pandas will raise an ImportError
whenthe method requiring that dependency is called.Dependency | Minimum Version | Notes |
---|---|---|
BeautifulSoup4 | 4.6.0 | HTML parser for read_html (see note) |
Jinja2 | Conditional formatting with DataFrame.style | |
PyQt4 | Clipboard I/O | |
PyQt5 | Clipboard I/O | |
PyTables | 3.4.3 | HDF5-based reading / writing |
SQLAlchemy | 1.1.4 | SQL support for databases other than sqlite |
SciPy | 0.19.0 | Miscellaneous statistical functions |
XLsxWriter | 0.9.8 | Excel writing |
blosc | Compression for HDF5 | |
fsspec | 0.7.4 | Handling files aside from local and HTTP |
fastparquet | 0.3.2 | Parquet reading / writing |
gcsfs | 0.6.0 | Google Cloud Storage access |
html5lib | HTML parser for read_html (see note) | |
lxml | 3.8.0 | HTML parser for read_html (see note) |
matplotlib | 2.2.2 | Visualization |
numba | 0.46.0 | Alternative execution engine for rolling operations |
openpyxl | 2.5.7 | Reading / writing for xlsx files |
pandas-gbq | 0.12.0 | Google Big Query access |
psycopg2 | PostgreSQL engine for sqlalchemy | |
pyarrow | 0.12.0 | Parquet, ORC (requires 0.13.0), and feather reading / writing |
pymysql | 0.7.11 | MySQL engine for sqlalchemy |
pyreadstat | SPSS files (.sav) reading | |
pytables | 3.4.3 | HDF5 reading / writing |
pyxlsb | 1.0.6 | Reading for xlsb files |
qtpy | Clipboard I/O | |
s3fs | 0.4.0 | Amazon S3 access |
tabulate | 0.8.3 | Printing in Markdown-friendly format (see tabulate) |
xarray | 0.8.2 | pandas-like API for N-dimensional data |
xclip | Clipboard I/O on linux | |
xlrd | 1.1.0 | Excel reading |
xlwt | 1.2.0 | Excel writing |
xsel | Clipboard I/O on linux | |
zlib | Compression for HDF5 |
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.
Bob Savage <bobsavage@mac.com>
Python on a Macintosh running Mac OS X is in principle very similar to Python onany other Unix platform, but there are a number of additional features such asthe IDE and the Package Manager that are worth pointing out.
4.1. Getting and Installing MacPython¶
![Mac upgrade python 3 Mac upgrade python 3](/uploads/1/2/5/8/125869177/892011411.gif)
Mac OS X 10.8 comes with Python 2.7 pre-installed by Apple. If you wish, youare invited to install the most recent version of Python 3 from the Pythonwebsite (https://www.python.org). A current “universal binary” build of Python,which runs natively on the Mac’s new Intel and legacy PPC CPU’s, is availablethere.
What you get after installing is a number of things:
- A
Python3.9
folder in yourApplications
folder. In hereyou find IDLE, the development environment that is a standard part of officialPython distributions; and PythonLauncher, which handles double-clicking Pythonscripts from the Finder. - A framework
/Library/Frameworks/Python.framework
, which includes thePython executable and libraries. The installer adds this location to your shellpath. To uninstall MacPython, you can simply remove these three things. Asymlink to the Python executable is placed in /usr/local/bin/.
The Apple-provided build of Python is installed in
/System/Library/Frameworks/Python.framework
and /usr/bin/python
,respectively. You should never modify or delete these, as they areApple-controlled and are used by Apple- or third-party software. Remember thatif you choose to install a newer Python version from python.org, you will havetwo different but functional Python installations on your computer, so it willbe important that your paths and usages are consistent with what you want to do.IDLE includes a help menu that allows you to access Python documentation. If youare completely new to Python you should start reading the tutorial introductionin that document.
If you are familiar with Python on other Unix platforms you should read thesection on running Python scripts from the Unix shell.
4.1.1. How to run a Python script¶
![Mac Mac](/uploads/1/2/5/8/125869177/559636517.jpg)
Your best way to get started with Python on Mac OS X is through the IDLEintegrated development environment, see section The IDE and use the Help menuwhen the IDE is running.
If you want to run Python scripts from the Terminal window command line or fromthe Finder you first need an editor to create your script. Mac OS X comes with anumber of standard Unix command line editors, vim andemacs among them. If you want a more Mac-like editor,BBEdit or TextWrangler from Bare Bones Software (seehttp://www.barebones.com/products/bbedit/index.html) are good choices, as isTextMate (see https://macromates.com/). Other editors includeGvim (http://macvim-dev.github.io/macvim/) and Aquamacs(http://aquamacs.org/).
To run your script from the Terminal window you must make sure that
/usr/local/bin
is in your shell search path.To run your script from the Finder you have two options:
- Drag it to PythonLauncher
- Select PythonLauncher as the default application to open yourscript (or any .py script) through the finder Info window and double-click it.PythonLauncher has various preferences to control how your script islaunched. Option-dragging allows you to change these for one invocation, or useits Preferences menu to change things globally.
4.1.2. Running scripts with a GUI¶
With older versions of Python, there is one Mac OS X quirk that you need to beaware of: programs that talk to the Aqua window manager (in other words,anything that has a GUI) need to be run in a special way. Use pythonwinstead of python to start such scripts.
With Python 3.9, you can use either python or pythonw.
4.1.3. Configuration¶
Python on OS X honors all standard Unix environment variables such as
PYTHONPATH
, but setting these variables for programs started from theFinder is non-standard as the Finder does not read your .profile
or.cshrc
at startup. You need to create a file~/.MacOSX/environment.plist
. See Apple’s Technical Document QA1067 fordetails.For more information on installation Python packages in MacPython, see sectionInstalling Additional Python Packages.
4.2. The IDE¶
MacPython ships with the standard IDLE development environment. A goodintroduction to using IDLE can be found athttp://www.hashcollision.org/hkn/python/idle_intro/index.html.
4.3. Installing Additional Python Packages¶
There are several methods to install additional Python packages:
- Packages can be installed via the standard Python distutils mode (
pythonsetup.pyinstall
). - Many packages can also be installed via the setuptools extensionor pip wrapper, see https://pip.pypa.io/.
4.4. GUI Programming on the Mac¶
There are several options for building GUI applications on the Mac with Python.
PyObjC is a Python binding to Apple’s Objective-C/Cocoa framework, which isthe foundation of most modern Mac development. Information on PyObjC isavailable from https://pypi.org/project/pyobjc/.
The standard Python GUI toolkit is
tkinter
, based on the cross-platformTk toolkit (https://www.tcl.tk). An Aqua-native version of Tk is bundled with OSX by Apple, and the latest version can be downloaded and installed fromhttps://www.activestate.com; it can also be built from source.wxPython is another popular cross-platform GUI toolkit that runs natively onMac OS X. Packages and documentation are available from https://www.wxpython.org.
PyQt is another popular cross-platform GUI toolkit that runs natively on MacOS X. More information can be found athttps://riverbankcomputing.com/software/pyqt/intro.
4.5. Distributing Python Applications on the Mac¶
The standard tool for deploying standalone Python applications on the Mac ispy2app. More information on installing and using py2app can be foundat http://undefined.org/python/#py2app.
4.6. Other Resources¶
The MacPython mailing list is an excellent support resource for Python users anddevelopers on the Mac:
Python For Macbook
Another useful resource is the MacPython wiki: