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[ CourseBoat com ] Linkedin - PostgreSQL - Advanced Queries
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Bonus Resources.txt
Ex_Files_PostgreSQL_Advanced_Queries
Exercise Files
Chapter 0
two_trees_database.txt
Chapter 1
aggregate_function_complete.txt
boolean_complete.txt
challenge_one_complete.txt
cube_complete.txt
filters_complete.txt
group_by_complete.txt
people_heights.txt
rollup_complete.txt
standard_deviation_complete.txt
Chapter 2
challenge_two_complete.txt
locations_complete.txt
moving_average_complete.txt
order_window_complete.txt
over_complete.txt
partition_complete.txt
window_complete.txt
Chapter 3
challenge_three_complete.txt
median_complete.txt
mode_complete.txt
quartile_complete.txt
range_complete.txt
Chapter 4
challenge_four_complete.txt
cumulative_distribution_complete.txt
rank_hypothetical_complete.txt
rank_percentile_complete.txt
rank_window_complete.txt
Chapter 5
case_complete.txt
coalesce_complete.txt
nullif_complete.txt
Chapter 6
cast_complete.txt
challenge_five_complete.txt
in_function_complete.txt
lead_lag_complete.txt
row_numbers_complete.txt
series_complete.txt
[1] Introduction
[1] Gain additional insights from your PostgreSQL data.mp4
[1] Gain additional insights from your PostgreSQL data.srt
[2] What you should know.mp4
[2] What you should know.srt
[3] Using the exercise files.mp4
[3] Using the exercise files.srt
[2] 1. Obtain Summary Statistics by Grouping Rows
[1] Using GROUP BY to aggregate data rows.mp4
[1] Using GROUP BY to aggregate data rows.srt
[2] Obtain general-purpose aggregate statistics.mp4
[2] Obtain general-purpose aggregate statistics.srt
[3] Evaluate columns with Boolean aggregates.mp4
[3] Evaluate columns with Boolean aggregates.srt
[4] Find the standard deviation and variance of a dataset.mp4
[4] Find the standard deviation and variance of a dataset.srt
[5] Include overall aggregates with ROLLUP.mp4
[5] Include overall aggregates with ROLLUP.srt
[6] Return all possible combinations of groups with CUBE.mp4
[6] Return all possible combinations of groups with CUBE.srt
[7] Segmenting groups with aggregate filters.mp4
[7] Segmenting groups with aggregate filters.srt
[8] Challenge Group statistics.mp4
[8] Challenge Group statistics.srt
[9] Solution Group statistics.mp4
[9] Solution Group statistics.srt
[3] 2. Use Window Functions to Perform Calculations across Row Sets
[1] Create a window function with an OVER clause.mp4
[1] Create a window function with an OVER clause.srt
[2] Partition rows within a window.mp4
[2] Partition rows within a window.srt
[3] Streamline partition queries with a WINDOW clause.mp4
[3] Streamline partition queries with a WINDOW clause.srt
[4] Ordering data within a partition.mp4
[4] Ordering data within a partition.srt
[5] Calculate a moving average with a sliding window.mp4
[5] Calculate a moving average with a sliding window.srt
[6] Return values at specific locations within a window.mp4
[6] Return values at specific locations within a window.srt
[7] Challenge Leverage window functions.mp4
[7] Challenge Leverage window functions.srt
[8] Solution Leverage window functions.mp4
[8] Solution Leverage window functions.srt
[4] 3. Statistics Based on Sorted Data within Groups
[1] Calculate the median value of a dataset.mp4
[1] Calculate the median value of a dataset.srt
[2] Calculate the first and third quartiles of a dataset.mp4
[2] Calculate the first and third quartiles of a dataset.srt
[3] Find the most frequent value within a dataset with MODE.mp4
[3] Find the most frequent value within a dataset with MODE.srt
[4] Determine the range of values within a dataset.mp4
[4] Determine the range of values within a dataset.srt
[5] Challenge Retrieve statistics of a dataset with groups.mp4
[5] Challenge Retrieve statistics of a dataset with groups.srt
[6] Solution Retrieve statistics of a dataset with groups.mp4
[6] Solution Retrieve statistics of a dataset with groups.srt
[5] 4. Ranking Data with Windows and Hypothetical Sets
[1] Rank rows with a window function.mp4
[1] Rank rows with a window function.srt
[2] Find a hypothetical rank.mp4
[2] Find a hypothetical rank.srt
[3] View top performers with percentile ranks.mp4
[3] View top performers with percentile ranks.srt
[4] Evaluate probability with cumulative distribution.mp4
[4] Evaluate probability with cumulative distribution.srt
[5] Challenge Evaluate rankings within a dataset.mp4
[5] Challenge Evaluate rankings within a dataset.srt
[6] Solution Evaluate rankings within a dataset.mp4
[6] Solution Evaluate rankings within a dataset.srt
[6] 5. Define Output Values with Conditional Expressions
[1] Define values with CASE statements.mp4
[1] Define values with CASE statements.srt
[2] Merge columns with COALESCE.mp4
[2] Merge columns with COALESCE.srt
[3] Convert values to null with NULLIF.mp4
[3] Convert values to null with NULLIF.srt
[7] 6. Additional Querying Techniques for Common Problems
[1] Output row numbers with query results.mp4
[1] Output row numbers with query results.srt
[2] Cast values to a different data type.mp4
[2] Cast values to a different data type.srt
[3] Move rows within a result with LEAD and LAG.mp4
[3] Move rows within a result with LEAD and LAG.srt
[4] Use an IN function with a subquery.mp4
[4] Use an IN function with a subquery.srt
[5] Define WHERE criteria with a series.mp4
[5] Define WHERE criteria with a series.srt
[6] Challenge Calculations across rows.mp4
[6] Challenge Calculations across rows.srt
[7] Solution Calculations across rows.mp4
[7] Solution Calculations across rows.srt
[8] Conclusion
[1] Next steps.mp4
[1] Next steps.srt
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