Efficient Data Cleaning Techniques : Dropping rows based upon condition using Pyspark

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🧹 In this video, we cover seven essential methods to clean and filter your datasets, ensuring data quality and accuracy.

1. Learn how to drop NA values from your entire DataFrame.
2. Discover how to drop NA values from specific columns in your DataFrame.
3. Master the art of dropping duplicate rows from your DataFrame.
4. Explore techniques to drop duplicate rows based on specific columns.
5. Understand how to drop duplicate rows, keeping the first occurrence.
6. Learn to drop duplicate rows, retaining the last occurrence.
7. Finally, uncover how to filter rows based on specific conditions using Pandas.

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#DataAnalysis #DataPreprocessing #DataWrangling #TechTutorial
  1. Sriw World of Coding
  2. PySpark
  3. ApacheSpark
  4. Python
  5. BigData
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