Getting started

What is it?

Pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with "relational" and "labeled" data both easy and intutive. It aims to be the fundamental high-level building block for doing practical, real world data analyst in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analyst / manipulation tool available in any language. It is already well on its way towards this goal.

Main Features

Here are just a few of the things that pandas does well:

• Easy handling of missing data (represented as Nan, NA, or NaT ) 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 lables, or the user can simply ignore the labels and ler Series, 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 or large data sets.
• Intuitive merging and joining data sets.
• Flexible reshaping and pivoting of data sets.
• Hierachical labeling of axes (possible to have multiple labels per tick).
• Robust IO tools for loading data from flat files (CSV and delimited), Excel files, database, 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.

Installation

The source code is currently hosted on Github at: https://github.com/pandas-dev/pandas

conda install pandas

pip install pandas

Installation from source

To install pandas from source you need Cython in addition to the normal dependentcies 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:

python setup.py install

or for installing in development mode

python -m pip install -e . --no-build-isolation --no-use-pep517

or alternatively

python setup.py delvelop

see full instructions for installing from source.

Documentation

The official documentation is hosted on PyData.org: https://pandas.pydata.org/pandas-docs/stable/