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KNIME_​day1

Lab 2: Deriving Total Booking Cost with Math Formula

Lab 1: Standardizing Movie Ratings and Titles

Lab 3: Splitting User's Name

Lab 4: Loyalty Points Categorization

Lab 5: Structuring Food Orders for Analytics 

Lab 6: Creating Booking Identifiers

Lab 7: Creating Booking Cost Categories

Lab 10: Normalizing Movie Ratings

Lab 9: Deriving Show Timings and Day Segments

Lab 8: Normalizing Ticket Scans and Downloads

ASSIGNMENT 1 DATA TRANSFORMATION

read movie.csv
CSV Reader
converting datatype
String to Number
Calculate total_item_cost
Math Formula
remove duplicate movies
Duplicate Row Filter
fill missing value as mean
Missing Value
renaming column
Column Renamer
sorting as per movie rating
Sorter
read booking.csv
CSV Reader
Expression
read booking.csv
CSV Reader
read booking.csv
CSV Reader
Categorize Booking Category
Expression
create a constant column
Constant Value Column Appender
create a booking identifier
Expression
Convert show_datetimeto KNIME Date/Time
String to Date&Time
Extract Hour of the Day
Date&Time Part Extractor
Sort bytotal_cost
Sorter
READ show.CSV
CSV Reader
read movie.csv
CSV Reader
round final_cost upto 2 decimals
Number Rounder
Convert Rating Data Type
String to Number
Categorize ShowSegment
Rule Engine
calculating gst
Math Formula
change column names
Column Renamer
Normalize Ratingson a scale of 0-5
Normalizer
calculate finalcost total + gst
Math Formula
read membership.csv
CSV Reader
Read ticket.csv
CSV Reader
read user.csv
CSV Reader
Remove Duplicate Movies
Duplicate Row Filter
split first name and last name
Cell Splitter
Fill Missing valuesas Mean
Missing Value
read foodorderitem.csv
CSV Reader
Rename price_at_timeto Unit Price
Column Renamer
Categorize a User intoMembership Category
Rule Engine
Derive scan_status based on download and scan information
Rule Engine
re-organize column
Column Resorter
Sort tickets by scan status
Sorter

Nodes

Extensions

Links