Data analytics
Panda library for python, for financial and advanced
mathematical calculations and formula

Data Analytics


Service Offerings:-
  • Identify Data Patterns
  • Collect Data Related To User Preferences
  • Collect Data Related To Market Economics
  • Collect Data Related To Business Process
  • Ordered And Unordered Time Series Data
  • Any Form Of Statistical Data Sets

Data Analytics means extracting and categorizing data to analyze and identify behavioral data and patterns. Many organization across world collect and analyze data related to customers, business process, market economics etc. Example:-Social Networking site collects data associated to user preferences, interests or specific criteria like age or gender.

Using Python for data analysis includes manipulating, processing, cleaning and crunching data.

Pandas is open source, flexible and powerful data analysis library for Python. It provides labeled data structure, statistical functions and offers operation for manipulating numerical tables. Python with pandas is used for domains like finance, neuroscience, economics, statistics, advertising, web analytics and more.


It can be used for any kind of data like:-
  • Tabular Data With Heterogeneously Typed Columns
  • Ordered And Unordered Time Series Data
  • Arbitrary Matrix Data With Row And Column Labels
  • Any Form Of Statistical Data Sets

Features provided by pandas:-
  • DataFrame object is used for data manipulation with integrated indexing as it is fast and efficient
  • Provides tools for reading and writing data between in-memory data structure and other formats like CSV and text files, MS Excel, SQL database and HDF5 format
  • Gain automatics label based alignment and easily handle missing data
  • Flexible reshaping
  • Label based slicing, fancy indexing and subsetting of large data sets
  • Insert and delete columns from data structures for size mutability
  • Transform data using group by engine
  • Merge and join data sets
  • Works with high dimensional data in low dimensional data structure
  • Generate date range, converse frequency, move window statistics and linear regressions, shifting data
  • Create domain specific time offsets and join time series without losing data
  • Highly optimized for performance


Features


Case Study



GPS tracking and Viewpoint python script, for farming and seed management
Technology  Python Django framework

Project was completed on time

Mr. Gerard Shaw
CEO Listo ltd


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