Practical5

 

Practical 5

AIM: 

Data Pre-processing and text analytics using orange. 

THEORY:

Data Preprocessing is a data mining technique in which raw data is converted to complete, accurate and consistent data in an understanding form. There are several procedures in the data preprocessing - Data cleaning, transformation, reduction.Every dataset is different and poses unique challenges. It can contain unformatted real-world data which can be composed of: Inaccurate or missing data, noisy or erroneous data, inconsistent data.So to handle raw data, Data preprocessing is performed.

Dataset Description:

This dataset gives description about the football players like their jersey number, club,nationality, height, weight, potential, wage etc

Total rows: 18207

Total columns: 89

Task:

Work flow

Assigning target variable

Preprocessing

Data obtained after pre-processing

Added python scripts

Python script for showing section > 2150

Displaying Output based on above code

Python script to keep only continuous attributes or having attributes length less than 5

Table displayed after running above script

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