PySpark Transformations and Actions | show, count, collect, distinct, withColumn, filter, groupby
In this video, I will show you how to apply basic transformations and actions on a Spark dataframe. We will explore show, count, collect, distinct, withColumn, withColumnRenamed, filter, groupby, lit, when.
Below are the contents of this video:
1. Get distinct values in a column
2. Create new constant columns
3. Create new columns housing conditions
4. Filter data based on a rule
5. Groupby and aggregate columns
6. Rename columns in a DF
7. Rename columns using alias after aggregation
8. Collect the output of a dataframe
9. Show top N rows
10. Count number of rows in a DF
Link to the playlist "Getting started with PySpark" : • Getting started with PySpark
Link to "Setting up the PySpark environment on Google Colab" video: • Setting up the PySpark environment on Goog...
Link to the GitHub repo: https://github.com/Abhishekmamidi123/...
Check out my "Data Science guide for freshers and enthusiasts" playlist: • My path to becoming a Data Scientist | Abh...
I have put my 3 years of learning experience into this playlist.
Contents of this video:
00:00 - Contents of this video
01:59 - Setting up the PySpark environment
02:19 - Initialize Spark Session object
02:28 - Read data from UCI
02:57 - show()
03:24 - count()
03:44 - collect()
05:25 - distinct()
06:37 - withColumn()
09:10 - withColumnRenamed()
10:11 - filter()
12:24 - groupby()
14:19 - Summary and Subscribe :)
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