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Pandas Part 1


Introduction

  • Pandas is an important module for python programming language

  • It provides high- performance data structures and data analysis tools

  • Python with pandas is used in a wide range of field (Data Science, Statistic,analytics,etc..)


Key Features Of Pandas

  • Fast data structure objects (This data structures are built on top of NumPy )

  • Lots of tools to do manipulations on this data structures

  • Tools for loading data into data objects

  • Organization and labeling of data are perfectly taken care of by the intelligent methods of alignment and indexing, which can be found within Pandas

  • Pandas allows you to implement a mathematical operation on the data

  • Pandas supports Multiple file formats


Installation


  1. Python does not come with Pandas module . So we need to install it using pip (Python package installer)

  2. Open idle or any other tools where you are coding and type the below code and run it

pip install pandas


Data Structures Provided By Pandas

  • Pandas provides with three different data structures

  1. Series

  2. DataFrame

  3. Panel


Description of each Data Structures


Series

  • It is a one dimensional labelled array (think as a single column)

  • Elements inside the series have a label to it (labelled array)

  • It contains homogenous data (all the elements should be of same datatype)

  • Once a series data structure is created we cant change its size (size is immutable)

  • Values inside the series data structures are changeable ( mutable)



DataFrame

  • It is a two dimensional data structure with labelled axis (think as a table which contains both rows and columns)

  • Elements inside the DataFrame have a label to it (row label and column label)

  • It contains heterogenous data along rows axis and homogenous data along column axis

  • Once a DataFrame is created we can change its size (size is mutable)

  • Values inside the DataFrame are changeable ( mutable)


Panel

  • Panel is a three dimensional data structures

  • Panel can be thought of as a container of DataFrame

  • It contains heterogenous data

  • Size is mutable

  • Data is mutable


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