🔥

Author: kevinschaich

README.md

@@ -1,27 +1,21 @@
-# PySpark Cheat Sheet
-
-🐍 📄 A quick reference guide to the most commonly used patterns and functions in PySpark SQL.
-
-## Table of Contents
-
-- [PySpark Cheat Sheet](#pyspark-cheat-sheet)
- - [Table of Contents](#table-of-contents)
- - [Common Patterns](#common-patterns)
- - [Importing Functions & Types](#importing-functions--types)
- - [Filtering](#filtering)
- - [Joins](#joins)
- - [Creating New Columns](#creating-new-columns)
- - [Coalescing Values](#coalescing-values)
- - [Casting, Nulls & Duplicates](#casting-nulls--duplicates)
- - [Column Operations](#column-operations)
- - [String Operations](#string-operations)
- - [String Filters](#string-filters)
- - [String Functions](#string-functions)
- - [Number Operations](#number-operations)
- - [Array Operations](#array-operations)
- - [Aggregation Operations](#aggregation-operations)
- - [Repartitioning](#repartitioning)
- - [UDFs (User Defined Functions)](#udfs-user-defined-functions)
+#### Table of Contents
+
+- [Common Patterns](#common-patterns)
+ - [Importing Functions & Types](#importing-functions--types)
+ - [Filtering](#filtering)
+ - [Joins](#joins)
+ - [Creating New Columns](#creating-new-columns)
+ - [Coalescing Values](#coalescing-values)
+ - [Casting, Nulls & Duplicates](#casting-nulls--duplicates)
+- [Column Operations](#column-operations)
+- [String Operations](#string-operations)
+ - [String Filters](#string-filters)
+ - [String Functions](#string-functions)
+- [Number Operations](#number-operations)
+- [Array Operations](#array-operations)
+- [Aggregation Operations](#aggregation-operations)
+- [Repartitioning](#repartitioning)
+- [UDFs (User Defined Functions)](#udfs-user-defined-functions)
 
 If you can't find what you're looking for, check out the [PySpark Official Documentation](https://spark.apache.org/docs/latest/api/python/pyspark.sql.html) and add it here!
 
@@ -226,7 +220,7 @@ df = df.groupBy('gender').agg(F.max('age').alias('max_age_by_gender'))
 df = df.groupBy('age').agg(F.collect_set('name').alias('person_names'))
 ```
 
-#### Repartitioning
+## Repartitioning
 
 ```python
 # Repartition – df.repartition(num_output_partitions)