Библиотека pandas в Python — это идеальный инструмент для тех, кто занимается анализом данных, используя для этого язык программирования Python.
В этом материале речь сначала пойдет об основных аспектах библиотеки и о том, как установить ее в систему. Потом вы познакомитесь с двумя структурам данных: series
и dataframes
. Сможете поработать с базовым набором функций, предоставленных библиотекой pandas, для выполнения основных операций по обработке. Знакомство с ними — ключевой навык для специалиста в этой сфере. Поэтому так важно перечитать материал до тех, пока он не станет понятен на 100%.
А на примерах сможете разобраться с новыми концепциями, появившимися в библиотеке — индексацией структур данных. Научитесь правильно ее использовать для управления данными. В конце концов, разберетесь с тем, как расширить возможности индексации для работы с несколькими уровнями одновременно, используя для этого иерархическую индексацию.
Библиотека Python для анализа данных
Pandas — это библиотека Python с открытым исходным кодом для специализированного анализа данных. Сегодня все, кто использует Python для изучения статистических целей анализа и принятия решений, должны быть с ней знакомы.
Библиотека была спроектирована и разработана преимущественно Уэсом Маккини в 2008 году. В 2012 к нему присоединился коллега Чан Шэ. Вместе они создали одну из самых используемых библиотек в сообществе Python.
Pandas появилась из необходимости в простом инструменте для обработки, извлечения и управления данными.
Этот пакет Python спроектирован на основе библиотеки NumPy. Такой выбор обуславливает успех и быстрое распространение pandas. Он также пользуется всеми преимуществами NumPy и делает pandas совместимой с большинством другим модулей.
Еще одно важное решение — разработка специальных структур для анализа данных. Вместо того, чтобы использовать встроенные в Python или предоставляемые другими библиотеками структуры, были разработаны две новых.
Они спроектированы для работы с реляционными и классифицированными данными, что позволяет управлять данными способом, похожим на тот, что используется в реляционных базах SQL и таблицах Excel.
Дальше вы встретите примеры базовых операций для анализа данных, которые обычно используются на реляционных или таблицах Excel. Pandas предоставляет даже более расширенный набор функций и методов, позволяющих выполнять эти операции эффективнее.
Основная задача pandas — предоставить все строительные блоки для всех, кто погружается в мир анализа данных.
Простейший способ установки библиотеки pandas — использование собранного решения, то есть установка через Anaconda или Enthought.
Установка в Anaconda
В Anaconda установка занимает пару минут. В первую очередь нужно проверить, не установлен ли уже pandas, и если да, то какая это версия. Для этого введите следующую команду в терминале:
conda list pandas
Если модуль уже установлен (например в Windows), вы получите приблизительно следующий результат:
# packages in environment at C:\Users\Fabio\Anaconda:
#
pandas 0.20.3 py36hce827b7_2
Если pandas не установлена, ее необходимо установить. Введите следующую команду:
conda install pandas
Anaconda тут же проверит все зависимости и установит дополнительные модули.
Solving environment: done
## Package Plan ##
Environment location: C:\Users\Fabio\Anaconda3
added / updated specs:
- pandas
The following new packages will be installed:
Pandas: 0.22.0-py36h6538335_0
Proceed ([y]/n)?
Press the y key on your keyboard to continue the installation.
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
Если требуется обновить пакет до более новой версии, используется эта интуитивная команда:
conda update pandas
Система проверит версию pandas и версию всех модулей, а затем предложит соответствующие обновления. Затем предложит перейти к обновлению.
Установка из PyPI
Pandas можно установить и с помощью PyPI, используя эту команду:
pip install pandas
Установка в Linux
Если вы работаете в дистрибутиве Linux и решили не использовать эти решения, то pandas можно установить как и любой другой пакет.
В Debian и Ubuntu используется команда:
sudo apt-get install python-pandas
А для OpenSuse и Fedora — эта:
zypper in python-pandas
Установка из источника
Если есть желание скомпилировать модуль pandas из исходного кода, тогда его можно найти на GitHub по ссылке https://github.com/pandas-dev/pandas:
git clone git://github.com/pydata/pandas.git
cd pandas
python setup.py install
Убедитесь, что Cython установлен. Больше об этом способе можно прочесть в документации: (http://pandas.pydata.org/pandas-docs/stable/install.html).
Репозиторий для Windows
Если вы работаете в Windows и предпочитаете управлять пакетами так, чтобы всегда была установлена последняя версия, то существует ресурс, где всегда можно загрузить модули для Windows: Christoph Gohlke’s Python Extension Packages for Windows (www.lfd.uci.edu/~gohlke/pythonlibs/). Каждый модуль поставляется в формате WHL для 32 и 64-битных систем. Для установки нужно использовать приложение pip:
pip install SomePackage-1.0.whl
Например, для установки pandas потребуется найти и загрузить следующий пакет:
pip install pandas-0.22.0-cp36-cp36m-win_amd64.whl
При выборе модуля важно выбрать нужную версию Python и архитектуру. Более того, если для NumPy пакеты не требуются, то у pandas есть зависимости. Их также необходимо установить. Порядок установки не имеет значения.
Недостаток такого подхода в том, что нужно устанавливать пакеты отдельно без менеджера, который бы помог подобрать нужные версии и зависимости между разными пакетами. Плюс же в том, что появляется возможность освоиться с модулями и получить последние версии вне зависимости от того, что выберет дистрибутив.
Проверка установки pandas
Библиотека pandas может запустить проверку после установки для верификации управляющих элементов (документация утверждает, что тест покрывает 97% всего кода).
Во-первых, нужно убедиться, что установлен модуль nose
. Если он имеется, то тестирование проводится с помощью следующей команды:
nosetests pandas
Оно займет несколько минут и в конце покажет список проблем.
Модуль Nose
Этот модуль спроектирован для проверки кода Python во время этапов разработки проекта или модуля Python. Он расширяет возможности модуль
unittest
. Nose используется для проверки кода и упрощает процесс.Здесь о нем можно почитать подробнее: _http://pythontesting.net/framework/nose/nose-introduction/.
Первые шаги с pandas
Лучший способ начать знакомство с pandas — открыть консоль Python и вводить команды одна за одной. Таким образом вы познакомитесь со всеми функциями и структурами данных.
Более того, данные и функции, определенные здесь, будут работать и в примерах будущих материалов. Однако в конце каждого примера вы вольны экспериментировать с ними.
Для начала откройте терминал Python и импортируйте библиотеку pandas. Стандартная практика для импорта модуля pandas следующая:
>>> import pandas as pd
>>> import numpy as np
Теперь, каждый раз встречая pd
и np
вы будете ссылаться на объект или метод, связанный с этими двумя библиотеками, хотя часто будет возникать желание импортировать модуль таким образом:
>>> from pandas import *
В таком случае ссылаться на функцию, объект или метод с помощью pd
уже не нужно, а это считается не очень хорошей практикой в среде разработчиков Python.
Pandas in Python is a package that is written for data analysis and manipulation. Pandas offer various operations and data structures to perform numerical data manipulations and time series. Pandas is an open-source library that is built over Numpy libraries. Pandas library is known for its high productivity and high performance. Pandas are popular because they make importing and analyzing data much easier. Pandas programs can be written on any plain text editor like Notepad, notepad++, or anything of that sort and saved with a .py extension.
To begin with Install Pandas in Python, write Pandas Codes, and perform various intriguing and useful operations, one must have Python installed on their System.
Check if Python is Already Present
To check if your device is pre-installed with Python or not, just go to the Command line(search for cmd in the Run dialog( + R). Now run the following command:
python --version
If Python is already installed, it will generate a message with the Python version available else install Python, for installing please visit: How to Install Python on Windows or Linux and PIP.
Python version
Pandas can be installed in multiple ways on Windows, Linux, and MacOS. Various ways are listed below:
Import Pandas in Python
Now, that we have installed pandas on the system. Let’s see how we can import it to make use of it.
For this, go to a Jupyter Notebook or open a Python file, and write the following code:
import pandas as pd
Here, pd is referred to as an alias to the Pandas, which will help us in optimizing the code.
How to Install or Download Python Pandas
Pandas can be installed in multiple ways on Windows, Linux and MacOS. Various different ways are listed below:
Install Pandas on Windows
Python Pandas can be installed on Windows in two ways:
- Using pip
- Using Anaconda
Install Pandas using pip
PIP is a package management system used to install and manage software packages/libraries written in Python. These files are stored in a large “online repository” termed as Python Package Index (PyPI).
Step 1 : Launch Command Prompt
To open the Start menu, press the Windows key or click the Start button. To access the Command Prompt, type “cmd” in the search bar, click the displayed app, or use Windows key + r, enter “cmd,” and press Enter.
Command Prompt
Step 2 : Run the Command
Pandas can be installed using PIP by use of the following command in Command Prompt.
pip install pandas
Installed Pandas
Install Pandas using Anaconda
Anaconda is open-source software that contains Jupyter, spyder, etc that is used for large data processing, Data Analytics, and heavy scientific computing. If your system is not pre-equipped with Anaconda Navigator, you can learn how to install Anaconda Navigator on Windows or Linux.
Install and Run Pandas from Anaconda Navigator
Step 1: Search for Anaconda Navigator in Start Menu and open it.
Step 2: Click on the Environment tab and then click on the Create button to create a new Pandas Environment.
Creating Environment
Step 3: Give a name to your Environment, e.g. Pandas, and then choose a Python and its version to run in the environment. Now click on the Create button to create Pandas Environment.
Naming the environment and selecting version
Step 4: Now click on the Pandas Environment created to activate it.
Activate the environment
Step 5: In the list above package names, select All to filter all the packages.
Getting all the packages
Step 6: Now in the Search Bar, look for ‘Pandas‘. Select the Pandas package for Installation.
Selecting the package to install
Step 7: Now Right Click on the checkbox given before the name of the package and then go to ‘Mark for specific version installation‘. Now select the version that you want to install.
Selecting the version for installation
Step 8: Click on the Apply button to install the Pandas Package.
Step 9: Finish the Installation process by clicking on the Apply button.
Step 10: Now to open the Pandas Environment, click on the Green Arrow on the right of the package name and select the Console with which you want to begin your Pandas programming.
Pandas Terminal Window:
Pandas Terminal
Install Pandas on Linux
Install Pandas on Linux, just type the following command in the Terminal Window and press Enter. Linux will automatically download and install the packages and files required to run Pandas Environment in Python:
pip3 install pandas
Install Pandas on MacOS
Install Pandas on MacOS, type the following command in the Terminal, and make sure that python is already installed in your system.
pip install pandas
Conclusion
With Pandas firmly installed, your Python journey into the data wilderness can begin. Remember, the installation process is just the first step, but a crucial one. So, saddle up, unleash the power of Pandas, and let your data analysis adventures commence!
You can install the Python pandas latest version or a specific version on windows either using pip
command that comes with Python binary or conda
if you are using Anaconda distribution. Before using either of these commands, you need to install Python or Anaconda distribution. If you already have either one installed, you can skip the document’s first section and directly jump to installing pandas. If not let’s see how to install pandas using these two approaches. You can use either one.
Related: Install pandas Using pip or conda on Linux & Mac OS
- pip (Python package manager) command that comes with python to install third-party packages from PyPI. Using pip you can install/uninstall/upgrade/downgrade any python library that is part of Python Package Index.
- Conda is the package manager that comes with Anaconda distribution, It is a package manager that is both cross-platform and language agnostic.
Table of Contents
- Install Python pandas On Windows
- Download & Install Python
- Install pandas using pip command
- Install pandas Using Anaconda Distribution
- Download & Install Anaconda
- Install pandas using conda command
As I said above if you already have python installed and have set the path to run python
and pip
from the command prompt, you can skip this section and directly jump to Install pandas using-pip-command-on-windows.
1.1 Download & Install Python
Let’s see step-by-step how to install python and set environment variables.
1.1.1 Download Python
Go to https://www.python.org/downloads/ and download the latest version for windows. If you want a specific version then use Active Python Releases section or scroll down to select the specific version to download.
This downloads the .exe file to your downloads folder.
1.1.2 Install Python to Custom Location
Now double click on the download to install it on windows. This will give you an installer screen similar to below.
From the below screen, you can select “Install Now” option if you wanted to install to the default location or select “Customize installation” to change the location where to install Python. In my case, I use the second option and installed at c:\apps\opt\python
folder.
Note: Select the check box bottom of the screen that reads “Add Python 3.9 to PATH”. This adds the python location to the PATH environment variable so that you can run pip and python from the command line. In case if you do not select, don’t worry I will show you how to add python installation location to PATH post-installation.
1.1.3 Set Python Installed Location to PATH Environment
Now set the Python installed location and scripts locations (C:\apps\opt\Python\Python39;C:\apps\opt\Python\Python39\Scripts) to PATH environment variables by following the below images in order.
1.1.4 Run Python shell from Command Prompt
Now open the windows command prompt by entering cmd
from windows run ( Press windows icon + R) or from the search command
This opens the command prompt. Now type python and press enter, this should give you a python prompt.
In case if you get an error like "'python' is not recognized as an internal or external command"
then something wrong with your PATH environment variable from the above step. Correct it and re-open the command line and try python again. If you still get an error then try setting PATH from the command prompt by running the below command. Change paths according to your installation.
set PATH=%PATH%;C:\apps\opt\Python\Python39;C:\apps\opt\Python\Python39\Scripts;
Now type again python and confirm you are seeing the below message.
1.2 Install Pandas Using pip Command on Windows
Python that I have installed comes with pip
and pip3
commands (You can find these in the python installed folder @ C:\apps\opt\Python\Python39\Scripts
.
pip (Python package manager) is used to install third-party packages from PyPI. Using pip you can install/uninstall/upgrade/downgrade any python library that is part of Python Package Index.
Since the pandas package is available in PyPI, we should use this to install pandas latest version on windows.
# Install pandas using pip
pip install pandas
(or)
pip3 install pandas
This should give you output as below. If your pip is not up to date, then upgrade pip to the latest version.
To check what version of pandas installed use pip list
or pip3 list
commands.
If you want to install a specific version of pandas, use the below command
# Installing pandas to specific version
pip install pandas==1.3.1
In case if you wanted to upgrade pandas to the latest or specific version
# Using pip3 to upgrade pandas
pip3 install --upgrade pandas
# Alternatively you can also try
python -m pip install --upgrade pandas
This completes the installation of pandas to the latest or specific version on windows. If you have trouble installing or any steps are incorrect here, please comment. Your comment would help others !!
2. Install Pandas From Anaconda Distribution
If you already have Anaconda install then jump to Install pandas using conda command on Windows
2.1 Download & Install Anaconda distribution
Follow the below step-by-step instructions to install Anaconda on windows.
2.1.1 Download Anaconda .exe File
Go to https://anaconda.com/ and select Anaconda Individual Edition to download the latest version of Anaconda. This downloads the .exe
file to the windows default downloads folder.
2.1.2 Install Anaconda on Windows
By double-clicking the .exe file starts the Anaconda installation. Follow the below screen shot’s and complete the installation
This finishes the installation of the Anaconda distribution. Now let’s see how to install pandas.
2.2 Install Pandas using conda command on Windows
2.2.1 Open Anaconda Navigator from the windows start or search box.
2.2.2 Create Anaconda Environment
This is optional but recommended to create an environment before you proceed. This gives complete segregation of different package installs for different projects you would be working on. If you already have an environment, you can use it too.
Select + Create option -> select the Python version you would like to use and enter your environment name. I am using the environment as pandas-tutorial.
2.2.3 Open Anaconda Terminal
You open the Anaconda terminal from Anaconda Navigator
or open it from the windows start menu/search.
2.2.4 Install Pandas using conda
Now enter conda install pandas
to install pandas in your environment. Note that along with pandas it also installs several other packages including the most used numpy
.
2.2.5 Test Pandas From Command Line or Using Jupyter Notebook
now open Python terminal by entering python
on the command line and then run the following command at prompt >>>.
>>> import pandas as pd
>>> pd.__version__
'1.3.2'
>>>
Writing pandas commands from the terminal is not practical in real-time, so let’s see how to run panda programs from Jupyter Notebook
.
Go to Anaconda Navigator -> Environments -> your environment (mine pandas-tutorial) -> select Open With Jupyter Notebook
This opens up Jupyter Notebook in the default browser.
Now select New -> PythonX and enter the below lines and select Run.
This completes installing pandas on Anaconda and running sample pandas statements on the command line and Jupyter Notebook.
I have tried my best to cover each step, if you notice I missed any step or If you have trouble installing, please comment. Your comment would help others !!
Happy Learning !!
Frequently Asked Questions on Install Pandas on Windows Step-by-Step
How do I install Pandas on Windows?
Installing Pandas on Windows is straightforward. You can use the following steps:
Open a command prompt or Anaconda prompt.
Run the command: pip install pandas
What are the prerequisites for installing Pandas on Windows?
Before installing Pandas, ensure that you have Python installed on your Windows machine. You can download and install Python from the official Python website (https://www.python.org/).
Can I install Pandas using a virtual environment on Windows?
It’s recommended to use a virtual environment to manage dependencies. You can create a virtual environment, activate it, and then install Pandas using the provided steps.
Are there alternative methods to install Pandas on Windows?
If you are using Anaconda, you can install Pandas through the Anaconda Navigator or Anaconda prompt. Additionally, you can use other package managers like conda for installation.
What do I do if I encounter installation errors on Windows?
If you encounter any installation errors, check that your Python environment is correctly set up, and ensure that you have the necessary permissions to install packages. You may also consider using a virtual environment to isolate your project dependencies.
Can I install specific versions of Pandas on Windows?
You can install a specific version of Pandas by specifying the version number in the installation command. For example, pip install pandas==1.3.3
installs Pandas version 1.3.3.
Related Articles
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- Install Python Pandas on Windows, Linux & Mac OS
- Pandas Window Functions Explained
- Pandas API on Spark | Explained With Examples
- How to Install Anaconda on Windows
- Pandas Convert JSON to CSV
- How to Check Pandas Version?
- How to Upgrade pandas to Latest Version?
- JupyterLab Error – JupyterLab application assets not found
- Pandas Read Multiple CSV Files into DataFrame
- Pandas ExcelWriter Explained with Examples
- Upgrade Pandas Version to Latest or Specific Version
1. Overview
In this tutorial, we’ll learn how to install Pandas and Python on Windows. We will cover the most popular ways of installation.
The instructions described below have been tested on Windows 7 and 20.
2. Install Python on Windows 10
Python is a widely-used easy to learn, user friendly, concise and high-level programming language. It is very easy to start coding on it and has a huge community.
Python is one of the most liked and wanted languages according to: stackoverflow — Python is the most wanted language for its fifth-year
2.1. Download and Install Python on Windows
Unlike Linux, Windows doesn’t come with a pre-installed Python version.
So if we want to use the latest version of Python then manual installation is the way to go. The steps to install Python on Windows are:
- Go to Python Releases for Windows
- Select the Python version you like — I prefer to go with the Stable Releases. For example —
Python 3.9.10 - Jan. 14, 2022
- Select the type of the installation — I prefer
Download Windows installer (64-bit)
— python-3.9.10-amd64.exe - Download the desired version
- Run the Python Installer
- During installation
6.1. Select Install launcher for all users — if you like to have it for all users
6.2. Check Add Python 3.9 to PATH in order Python to be visible for other programs - Press Install Now
- Finally you can verify the installation by checking the version —
Python -V
— expected output —Python 3.9.10
2.2. Create a virtual environment (optional)
Python offers a powerful package system venv
which helps separate different Python packages. In simple words, you can create several virtual environments in multiple Pandas versions:
- pandas 1.3.4
- pandas 1.0.0
To create new virtual environment called pandas1
:
- create folder for your virtual environments ( or select existing one)
- Run command:
python -m venv pandas1
- activate the environment by:
cd pandas1
source bin/activate
Once environment is activated you will see change in the terminal:
(pandas1) $ deactivate
The command above deactivates the environment.
To learn more please check:
- venv — Creation of virtual environments
2.3. Install PIP (optional)
PIP is one of the most popular package managers for Python. If it’s not installed:
pip -V
will return message that the command is not recognized — then you can install it by:
py -m ensurepip --upgrade
To learn more please check:
- PIP Installation
3. Install Pandas on Windows
3.1. Install Pandas by Pypi
Next step is to install Pandas on Windows. The most easiest way of installing Pandas is by running:
pip install pandas
You can find more information for Pandas on: pandas — pypi.org.
3.2. Install Anaconda and Pandas on Windows
If you like to use alternative installation methods you can check the official docs: Installing Anaconda on Windows.
For example Pandas is part of Anaconda — so if you install Anaconda on your system you will get Pandas:
-
download the Anaconda installer for Windows
-
Verify data integrity with SHA-256. (optional but highly RECOMMENDED step)
-
Install Anaconda by double click on the installer
-
Press Next
-
«I Agree» on — licensing terms
-
Select «Just Me» — if you are going to use it for yourself only
-
Select a destination folder
-
Click the Next button
-
Add «Anaconda to your PATH environment variable» — highly recommended
-
Continue the rest depending on your personal preferences or refer to the official installation guide
3.3. Verify Pandas installation
Finally you can test Pandas installation by running next commands:
pip freeze | grep pandas
result will be:
pandas==1.4.0
4. Conclusion
To summarize, in this article, we’ve seen examples of installing Python and Pandas on Windows in several ways. We’ve briefly explained these installation methods and how to verify the installation.
And finally, we’ve seen how to manage multiple Python/Pandas installations on Windows like systems with different package versions.
Project description
pandas: powerful Python data analysis toolkit
Testing | |
Package | |
Meta |
What is it?
pandas is a Python package that provides fast, flexible, and expressive data
structures designed to make working with «relational» or «labeled» data both
easy and intuitive. It aims to be the fundamental high-level building block for
doing practical, real world data analysis in Python. Additionally, it has
the broader goal of becoming the most powerful and flexible open source data
analysis / manipulation tool available in any language. It is already well on
its way towards this goal.
Table of Contents
- Main Features
- Where to get it
- Dependencies
- Installation from sources
- License
- Documentation
- Background
- Getting Help
- Discussion and Development
- Contributing to pandas
Main Features
Here are just a few of the things that pandas does well:
- Easy handling of missing data (represented as
NaN
,NA
, orNaT
) in floating point as well as non-floating point data - Size mutability: columns can be inserted and
deleted from DataFrame and higher dimensional
objects - Automatic and explicit data alignment: objects can
be explicitly aligned to a set of labels, or the user can simply
ignore the labels and letSeries
,DataFrame
, etc. automatically
align the data for you in computations - Powerful, flexible group by functionality to perform
split-apply-combine operations on data sets, for both aggregating
and transforming data - Make it easy to convert ragged,
differently-indexed data in other Python and NumPy data structures
into DataFrame objects - Intelligent label-based slicing, fancy
indexing, and subsetting of
large data sets - Intuitive merging and joining data
sets - Flexible reshaping and pivoting of
data sets - Hierarchical labeling of axes (possible to have multiple
labels per tick) - Robust IO tools for loading data from flat files
(CSV and delimited), Excel files, databases,
and saving/loading data from the ultrafast HDF5 format - Time series-specific functionality: date range
generation and frequency conversion, moving window statistics,
date shifting and lagging
Where to get it
The source code is currently hosted on GitHub at:
https://github.com/pandas-dev/pandas
Binary installers for the latest released version are available at the Python
Package Index (PyPI) and on Conda.
# conda conda install -c conda-forge pandas
# or PyPI pip install pandas
The list of changes to pandas between each release can be found
here. For full
details, see the commit logs at https://github.com/pandas-dev/pandas.
Dependencies
- NumPy — Adds support for large, multi-dimensional arrays, matrices and high-level mathematical functions to operate on these arrays
- python-dateutil — Provides powerful extensions to the standard datetime module
- pytz — Brings the Olson tz database into Python which allows accurate and cross platform timezone calculations
See the full installation instructions for minimum supported versions of required, recommended and optional dependencies.
Installation from sources
To install pandas from source you need Cython in addition to the normal
dependencies above. Cython can be installed from PyPI:
pip install cython
In the pandas
directory (same one where you found this file after
cloning the git repo), execute:
pip install .
or for installing in development mode:
python -m pip install -ve . --no-build-isolation --config-settings=editable-verbose=true
See the full instructions for installing from source.
License
BSD 3
Documentation
The official documentation is hosted on PyData.org.
Background
Work on pandas
started at AQR (a quantitative hedge fund) in 2008 and
has been under active development since then.
Getting Help
For usage questions, the best place to go to is StackOverflow.
Further, general questions and discussions can also take place on the pydata mailing list.
Discussion and Development
Most development discussions take place on GitHub in this repo, via the GitHub issue tracker.
Further, the pandas-dev mailing list can also be used for specialized discussions or design issues, and a Slack channel is available for quick development related questions.
There are also frequent community meetings for project maintainers open to the community as well as monthly new contributor meetings to help support new contributors.
Additional information on the communication channels can be found on the contributor community page.
Contributing to pandas
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.
A detailed overview on how to contribute can be found in the contributing guide.
If you are simply looking to start working with the pandas codebase, navigate to the GitHub «issues» tab and start looking through interesting issues. There are a number of issues listed under Docs and good first issue where you could start out.
You can also triage issues which may include reproducing bug reports, or asking for vital information such as version numbers or reproduction instructions. If you would like to start triaging issues, one easy way to get started is to subscribe to pandas on CodeTriage.
Or maybe through using pandas you have an idea of your own or are looking for something in the documentation and thinking ‘this can be improved’…you can do something about it!
Feel free to ask questions on the mailing list or on Slack.
As contributors and maintainers to this project, you are expected to abide by pandas’ code of conduct. More information can be found at: Contributor Code of Conduct
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