Abstract: The manipulation of raw or crude data and drawing conclusions out of it is called data analytics. In this paper we will be analysing car sales data of a particular dealer in a calendar year. Various car models have been sold to customers in the market by this dealer. We are interested in analysing this recorded data and various aspects profit making. The data is stored in .csv format and includes various fields which may or may not be dependent on each other. Real world data are generally noisy, inconsistent, contains many errors and incomplete. Proper manipulation of these factors improves the quality of analysis and prediction. The focus of data analytics lies in inference, the process of deriving conclusions with the help of graphs, statistics and many other non-statistical tools. In this paper we have carried out data analysis in steps yielding the best result exploiting various data science libraries and the code is written in Python.

Keywords: Manipulation of Raw or Crude Data and Drawing Conclusions - Data Analytics, Car Sales, Graphs, Data Pre-Processing, Statistics and Many Other Non-Statistical Tools

PDF | DOI: 10.17148/IJARCCE.2019.8439

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