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This plan includes
- Instant access to 11,000+ online courses
- Play & Pause Course Videos
HD Video Recorded Lectures- Learn on Mobile/PC/Tablet
- Quizzes and Real Projects
- Lifetime Course Certificate
- Instructor Chat Support
- Cancel Plan Anytime
This plan includes
- Instant access to 11,000+ online courses
- Play & Pause Course Videos
- HD Video Recorded Lectures
- Learn on Mobile/PC/Tablet
- Quizzes and Real Projects
- Lifetime Course Certificate
- Instructor Chat Support
- Cancel Plan Anytime
What you'll learn?
- What you will learn :
- SparkSession and imports
- Spark DataFrame and its characteristics
- Syntax and example
- Print results
- Understanding the data
- Number of records
- Columns in dataFrame
- Describe a DataFrame
- Schema of a DataFrame
- Create a new column
- Arithmetic operations on Data
- Change column data type
- Create a column with integer as constant
- Rounding of digits
- Sorting operation
- Drop columns
- Rename columns
- Create a column with string as constant
- Conditional Statements
- Changing case of a column
- Filter operations
- Grouping and aggregations
Course Overview
This course will prepare you for a real world Data Engineer role (basics)!
Learn to code PySpark like a real world developer. Here our major focus will be on Practical applications of PySpark and bridge the gap between academic knowledge and practical skill.
In this course we will get to know and apply few of the most essential and basic functions in PySpark, that are used frequently in scripting for any project based on PySpark.
About PySpark:
Learn the latest Big Data Technology - Spark! And learn to use it with one of the most popular programming languages, Python!
One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Spark! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Spark to solve their big data problems!
Spark can perform up to 100x faster than Hadoop MapReduce, which has caused an explosion in demand for this skill! Because the Spark 2.0 DataFrame framework is so new, you now have the ability to quickly become one of the most knowledgeable people in the job market!
What you will learn :
-
SparkSession and imports
-
Spark DataFrame and its characteristics
-
Syntax and example
-
Print results
-
Understanding the data
-
Number of records
-
Columns in dataFrame
-
Describe a DataFrame
-
Schema of a DataFrame
-
Create a new column
-
Arithmetic operations on Data
-
Change column data type
-
Create a column with integer as constant
-
Apply what we know
-
Rounding of digits
-
Sorting operation
-
Drop columns
-
Rename columns
-
Create a column with string as constant
-
Conditional Statements
-
Changing case of a column
-
Filter operations
-
Grouping and aggregations
Prerequisites :
-
Some basic programming skills (Not Mandatory)
-
Will to implement theoretical knowledge in practical.
Who this course is for:
-
Beginners who want to learn Big Data or experienced people who want to transition to a Big Data role
-
Big data beginners who want to learn how to code in the real world
-
Aspiring candidates for data engineering role
Pre-requisites
- Some basic programming skills (Not Mandatory).
- Will to implement theoretical knowledge in practical.
Target Audience
- Beginners who want to learn Big Data or experienced people who want to transition to a Big Data role
- Big data beginners who want to learn how to code in the real world
- Aspiring candidates for data engineering role
Curriculum 24 Lectures
-
Section 1 : Unpublished Section
- Lecture 2 :
- 02 - SparkSession and Imports
- Lecture 3 :
- 03 - Spark DataFrame and its characteristics
- Lecture 4 :
- Syntax and example
- Lecture 5 :
- Print operation
- Lecture 6 :
- Understanding the data
- Lecture 7 :
- Number of records in DataFrame
- Lecture 8 :
- Columns present in DataFrame
- Lecture 9 :
- Summary of a DataFrame
- Lecture 10 :
- Get schema of a DataFrame
- Lecture 11 :
- Create a new column in a dataframe
- Lecture 12 :
- Arithmetic operations on columns
- Lecture 13 :
- Change column Data Types by casting
- Lecture 14 :
- Create a column with integer constant
- Lecture 15 :
- Application of the learnings
- Lecture 16 :
- Rounding operations using bround
- Lecture 17 :
- Sorting operation
- Lecture 18 :
- Drop columns of a dataframe
- Lecture 19 :
- Rename a column
- Lecture 20 :
- Create a column with String constant
- Lecture 21 :
- Conditional Statements
- Lecture 22 :
- Changing Case of a column
- Lecture 23 :
- Filter operations
- Lecture 24 :
- Grouping and Aggegrations
Our learners work at
Frequently Asked Questions
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