| 01 - Apache Spark SQL and data analysis.mp4 | 2.5 MB | ||
| 01 - Apache Spark SQL and data analysis.srt | 1.4 KB | ||
| 01 - Exploratory data analysis with DataFrames.mp4 | 16.1 MB | ||
| 01 - Exploratory data analysis with DataFrames.srt | 10.6 KB | ||
| 01 - Install Spark.mp4 | 7.2 MB | ||
| 01 - Install Spark.srt | 7 KB | ||
| 01 - Introduction to DataFrames.mp4 | 3.9 MB | ||
| 01 - Introduction to DataFrames.srt | 4.3 KB | ||
| 01 - Next steps.mp4 | 1.3 MB | ||
| 01 - Next steps.srt | 1.3 KB | ||
| 01 - Querying DataFrames with SQL.mp4 | 9.3 MB | ||
| 01 - Querying DataFrames with SQL.srt | 6.4 KB | ||
| 01 - Set up a Jupyter notebook.mp4 | 2.9 MB | ||
| 01 - Set up a Jupyter notebook.srt | 3.2 KB | ||
| 02 - Exploratory data analysis with Spark SQL.mp4 | 11.1 MB | ||
| 02 - Exploratory data analysis with Spark SQL.srt | 7.2 KB | ||
| 02 - Filtering DataFrames with SQL.mp4 | 12.5 MB | ||
| 02 - Filtering DataFrames with SQL.srt | 8.6 KB | ||
| 02 - Install PySpark.mp4 | 999.6 KB | ||
| 02 - Install PySpark.srt | 1.1 KB | ||
| 02 - Load data into DataFrames CSV Files.mp4 | 17.1 MB | ||
| 02 - Load data into DataFrames CSV Files.srt | 10.8 KB | ||
| 02 - SQL for DataFrames.mp4 | 3.1 MB | ||
| 02 - SQL for DataFrames.srt | 3.5 KB | ||
| 02 - What you should know.mp4 | 641.8 KB | ||
| 02 - What you should know.srt | 1 KB | ||
| 03 - Aggregating Data with SQL.mp4 | 11.2 MB | ||
| 03 - Aggregating Data with SQL.srt | 7.7 KB | ||
| 03 - Load data into DataFrames JSON Files.mp4 | 6 MB | ||
| 03 - Load data into DataFrames JSON Files.srt | 4.9 KB | ||
| 03 - Timeseries analysis with DataFrames.mp4 | 30.1 MB | ||
| 03 - Timeseries analysis with DataFrames.srt | 14.3 KB | ||
| 03 - Using Jupyter notebooks with PySpark.mp4 | 4.7 MB | ||
| 03 - Using Jupyter notebooks with PySpark.srt | 5.1 KB | ||
| 03.01 Loading csv files into dataframes.ipynb | 10.5 KB | ||
| 03.02 Reading JSON Files.ipynb | 6.9 KB | ||
| 03.03 Basic Dataframe Operations.ipynb | 11.6 KB | ||
| 03.04 Filtering using Dataframe API.ipynb | 6 KB | ||
| 03.05 Aggregating using Dataframe API.ipynb | 6.7 KB | ||
| 03.06 Sampling using Dataframe API.ipynb | 6.7 KB | ||
| 03.07 Saving Data from Dataframes.ipynb | 5.4 KB | ||
| 04 - Basic DataFrame operations.mp4 | 7.5 MB | ||
| 04 - Basic DataFrame operations.srt | 5.6 KB | ||
| 04 - Basic machine learning with DataFrames, part 1.mp4 | 18.1 MB | ||
| 04 - Basic machine learning with DataFrames, part 1.srt | 11.6 KB | ||
| 04 - Joining DataFrames with SQL.mp4 | 11.1 MB | ||
| 04 - Joining DataFrames with SQL.srt | 8.3 KB | ||
| 04.01 Querying Dataframes with SQL.ipynb | 7.2 KB | ||
| 04.02 Filtering Dataframes with SQL.ipynb | 10.1 KB | ||
| 04.03 Aggregating Dataframes with SQL.ipynb | 11.5 KB | ||
| 04.04 Joining Dataframes with SQL.ipynb | 8.8 KB | ||
| 04.05 De-duplicating.ipynb | 3.1 KB | ||
| 04.06 Working with NAs.ipynb | 8.9 KB | ||
| 05 - Basic machine learning with DataFrames, part 2.mp4 | 12.5 MB | ||
| 05 - Basic machine learning with DataFrames, part 2.srt | 9.3 KB | ||
| 05 - Eliminating duplicates in DataFrames.mp4 | 8.7 MB | ||
| 05 - Eliminating duplicates in DataFrames.srt | 7.5 KB | ||
| 05 - Filter data with DataFrame API.mp4 | 4.9 MB | ||
| 05 - Filter data with DataFrame API.srt | 3.7 KB | ||
| 05.01 Exploratory Analysis.ipynb | 11.4 KB | ||
| 05.02 Timeseries Analysis .ipynb | 12.8 KB | ||
| 05.03 Machine Learning - Clustering.ipynb | 5.4 KB | ||
| 05.04 Machine Learning - Linear Regression.ipynb | 5.4 KB | ||
| 06 - Aggregate data with DataFrame API.mp4 | 8 MB | ||
| 06 - Aggregate data with DataFrame API.srt | 6.2 KB | ||
| 06 - Working with NA values in DataFrames.mp4 | 11.7 MB | ||
| 06 - Working with NA values in DataFrames.srt | 8 KB | ||
| 07 - Sample data from DataFrames.mp4 | 11.4 MB | ||
| 07 - Sample data from DataFrames.srt | 7.8 KB | ||
| 08 - Save data from DataFrames.mp4 | 7.5 MB | ||
| 08 - Save data from DataFrames.srt | 5.5 KB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| Spark Mac Linux Export Environment Variables | 204.8 B | ||
| Spark Windows Instructions | 716.8 B | ||
| location_temp.csv | 14.2 MB | ||
| server_name.csv | 819.2 B | ||
| utilization.csv | 17.6 MB | ||
| utilization.json | 56.2 MB | ||
| ▲ 96 total files | |||
Introduction to Spark SQL and DataFrames
https://WebToolTip.com
Updated: April 1, 2024
Duration: 1h 54m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 250 MB
Level: Intermediate | Genre: eLearning | Language: English
Explore DataFrames, a widely used data structure in Apache Spark. DataFrames allow Spark developers to perform common data operations, such as filtering and aggregation, as well as advanced data analysis on large collections of distributed data. With the addition of Spark SQL, developers have access to an even more popular and powerful query language than the built-in DataFrames API. In this course, instructor Dan Sullivan shows how to perform basic operations—loading, filtering, and aggregating data in DataFrames—with the API and SQL, as well as more advanced techniques that are easily performed in SQL. In this section of the course, Dan explains how to join data, eliminate duplicates, and deal with null or NA values. The lessons conclude with three in-depth examples of using DataFrames for data science: exploratory data analysis, time series analysis, and machine learning.
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| 3.1 GB | freecoursewb | 1 week | 25 | 24 | |
| 1.2 GB | freecoursewb | 1 week | 15 | 12 | |
| 3.8 GB | freecoursewb | 3 weeks | 4 | 5 | |
| 1.6 GB | freecoursewb | 3 weeks | 5 | 3 | |
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