UNIT-1 Data Handling using Pandas –I PART -A

 Pandas: 

• It is a package useful for data analysis and manipulation.

 • Pandas provide an easy way to create, manipulate and wrangle the data.

 • Pandas provide powerful and easy-to-use data structures, as well as the means to quickly perform operations on these structures. 

Data scientists use Pandas for its following advantages: 

• Easily handles missing data. 

• It uses Series for one-dimensional data structure and DataFrame for multi-dimensional data structure. 

• It provides an efficient way to slice the data.

 • It provides a flexible way to merge, concatenate or reshape the data.

DATA STRUCTURE IN PANDAS 

A data structure is a way to arrange the data in such a way that so it can be accessed quickly and we can perform various operation on this data like- retrieval, deletion, modification etc. 

Pandas deals with 3 data structure

1. Series

 2. Data Frame

 3. Panel

 We are having only series and data frame in our syllabus.

Series 

Series-Series is a one-dimensional array like structure with homogeneous data, which can be used to handle and manipulate data. 

What makes it special is its index attribute, which has incredible functionality and is heavily mutable. 

✓ We can say that Series is a labeled one-dimensional array which can hold any type of data. 

✓ Data of Series is always mutable, means it can be changed. 

✓ But the size of Data of Series is always immutable, means it cannot be changed. 

✓ Series may be considered as a Data Structure with two arrays out which one array works as Index (Labels) and the second array works as original Data. ✓ Row Labels in Series are called Index.

Syntax to create a Series