$180k Databricks Engineers Mastered This One Method!
Date formats driving you crazy?
Are you using PySpark to do your data cleansing?
Databricks and PySpark have great functions to handle various data formats... Watch now to learn how to keep your date values clean and improve the integrity of your data!
In this video, I'll show you how to handle messy date formats in Databricks using PySpark, covering:
✅ Parsing and transforming standard date formats (YYYY-MM-DD, MM/DD/YYYY)
✅ Converting Unix Epoch time into readable dates
✅ Cleaning text-based dates like 'Oct 25th'
✅ Fixing Excel serial dates effortlessly
💡 BONUS: Stick around to the end to learn the trick for dealing with dates stored as integers!
Whether you're working on distributed pipelines or fine-tuning your data processing scripts, this tutorial will make handling dates a breeze in PySpark.
📺 Watch now to take your PySpark and Databricks skills to the next level!
💬 Have you faced messy date formats before? Share your toughest example in the comments, and I might feature it in a future video.
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Date Formats with PySpark and Databricks Chapters:
0:00 Dates from users can be frustrating!
0:35 What Data Quality Issues Will We Cover?
1:21 Why do consistent date formats matter?
3:17 Into to Databricks Notebooks!
4:27 Importing your python libraries and functions into your Databricks Notebook
4:40 What PySpark Functions Are Needed for Date Cleansing
5:37 Creating a SparkSession in Databricks with PySpark | What is a SparkSession and Why do I need it?
6:28 Starting Easy Formatting US dates to ISO Standard in Databricks with PySpark
7:18 Sidequest: What is the difference between df.show() vs display(df)
9:20 Adding columns in a dataframe with PySpark and formatting dates for visual representation
11:43 What is Unix Epoch Time (1706303400) and how to make it a date/time using PySpark!
14:20 Handling Partial and String / Text dates in Databricks with PySpark
18:05 What are Excel (Serial) Dates (45678) and how to get them into a date format using Python!
22:52 Date Formatting Best Practices in Data Engineering
25:08 What other date formats you might run into?
25:50 How can I help you?
26:36 Resuming Friday Night Live Sessions!
#Databricks #PySpark #DataEngineering #DateFormats #BigData #Python