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Data Analysis with Polars in Python

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Data Analysis with Polars in Python (Size: 1.1 GB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - Getting Started
  1. Welcome to the Course!.en_US.srt 1.4 KB
  1. Welcome to the Course!.mp4 1.8 MB
  2. Installing Python.en_US.srt 4.3 KB
  2. Installing Python.mp4 31.9 MB
  3. Installing Visual Studio Code.en_US.srt 2.8 KB
  3. Installing Visual Studio Code.mp4 10 MB
  4. Extensions for Visual Studio Code.en_US.srt 2.9 KB
  4. Extensions for Visual Studio Code.mp4 13 MB
  5. Download Course Materials.html 7.2 KB
  Course Materials
  02 - DataFrame Inputs & Outputs
  Notebooks
  01 - Installing Polars.ipynb 1.2 KB
  02- Read CSV.ipynb 41.3 KB
  03 - Manipulation & Selection
  Notebooks
  01 - Select.ipynb 23.8 KB
  02 - Filter.ipynb 17.8 KB
  03 -Slicing & Sampling.ipynb 44.2 KB
  04 - Frame SQL.ipynb 8.5 KB
  04 - Joining DataFrames
  Notebooks
  01 - Inner Join.ipynb 14.7 KB
  02 - Anti Joins.ipynb 10.8 KB
  03 - Left Join.ipynb 15.4 KB
  05 - Aggregating DataFrames
  Notebooks
  01 - Min & Max.ipynb 11.4 KB
  02 - Mean, Median & Mode.ipynb 12.8 KB
  03 - Sum.ipynb 8 KB
  04 - Quantiles.ipynb 14.1 KB
  06 - Date & Time Functions
  Notebooks
  01 - business_day_count.ipynb 1.3 KB
  02 - add_business_days.ipynb 2.3 KB
  03 - Handling Time Zones.ipynb 102.5 KB
  04 - Handing Epoch Timestamps.ipynb 13.3 KB
  05 - Year Expressions.ipynb 9.6 KB
  06 - Month Expressions.ipynb 20.4 KB
  07 - String Expressions
  Notebooks
  01 - Regular Expressions (regex).ipynb 37.4 KB
  02 - Find & Replace.ipynb 11.5 KB
  03 - Date & Time Conversions.ipynb 49.1 KB
  08 - Computation Expressions
  Notebooks
  01 - Hashing Sensitive Data.ipynb 23.9 KB
  02 - Rank.ipynb 35.5 KB
  Archived - Python Fundamentals
  Notebooks
  01 - Data Types.ipynb 4.4 KB
  02 - Data Structures.ipynb 2.4 KB
  03 - Casting Methods.ipynb 3.8 KB
  04 - Mathematical Operators.ipynb 4.5 KB
  05 - Comparison Operators.ipynb 3.8 KB
  06 - Logical Operators.ipynb 3.2 KB
  07 - Membership Operators.ipynb 2.4 KB
  08 - If Statements.ipynb 1 KB
  Datasets
  Accounting.xlsx 19.1 KB
  Electric_Vehicles.json 78 MB
  Marketing Cost Data
  2 - Inputs & Outputs
  10. Write Database.en_US.srt 6.5 KB
  10. Write Database.mp4 23.5 MB
  11. Read Database.en_US.srt 3.9 KB
  11. Read Database.mp4 20.6 MB
  12. Read Excel.en_US.srt 3 KB
  12. Read Excel.mp4 7.5 MB
  13. From Pandas.en_US.srt 1.6 KB
  13. From Pandas.mp4 4.1 MB
  14. To Pandas.en_US.srt 2.4 KB
  14. To Pandas.mp4 9.8 MB
  15. Read ODS.en_US.srt 8.1 KB
  15. Read ODS.mp4 35.8 MB
  16. JSON Normalize.en_US.srt 13 KB
  16. JSON Normalize.mp4 43.7 MB
  17. Scan CSV (LazyFrames).en_US.srt 6 KB
  17. Scan CSV (LazyFrames).mp4 11.2 MB
  18. Reading Multiple CSV Files.en_US.srt 6 KB
  18. Reading Multiple CSV Files.mp4 23.4 MB
  19. Write Database (SQL Server).en_US.srt 6.4 KB
  19. Write Database (SQL Server).mp4 17.2 MB
  20. Schemas.en_US.srt 17 KB
  20. Schemas.mp4 59.7 MB
  21. LazyFrame Query Optimization.mp4 24.6 MB
  3 - Manipulation & Selection
  22. Select.en_US.srt 8.4 KB
  22. Select.mp4 22.8 MB
  23. Filter.en_US.srt 2.7 KB
  23. Filter.mp4 8.1 MB
  24. Slicing & Sampling.en_US.srt 5.9 KB
  24. Slicing & Sampling.mp4 34.1 MB
  25. Frame SQL.en_US.srt 6.8 KB
  25. Frame SQL.mp4 13.9 MB
  4 - Joining & Appending to DataFrames
  26. Inner Joins.en_US.srt 3.5 KB
  26. Inner Joins.mp4 11.1 MB
  27. Anti Joins.en_US.srt 2.9 KB
  27. Anti Joins.mp4 8.1 MB
  28. Left Joins.en_US.srt 5.1 KB
  28. Left Joins.mp4 10.8 MB
  5 - Aggregation Expressions
  29. Min & Max.en_US.srt 4.1 KB
  29. Min & Max.mp4 11.3 MB
  30. Mean, Median, & Mode.en_US.srt 4.6 KB
  30. Mean, Median, & Mode.mp4 13.2 MB
  31. Sum.en_US.srt 2.1 KB
  31. Sum.mp4 5.3 MB
  32. Quantiles.en_US.srt 4.3 KB
  32. Quantiles.mp4 13 MB
  6 - Date & Time Expressions
  33. Business Day Count.en_US.srt 4.5 KB
  33. Business Day Count.mp4 11.5 MB
  34. Add Business Days.en_US.srt 9.4 KB
  34. Add Business Days.mp4 37.6 MB
  35. Handling Time Zones.en_US.srt 18.2 KB
  35. Handling Time Zones.mp4 120.3 MB
  36. Handling Epoch Timestamps.en_US.srt 6.9 KB
  36. Handling Epoch Timestamps.mp4 27 MB
  37. Year Expressions.en_US.srt 4.6 KB
  37. Year Expressions.mp4 14.5 MB
  38. Month Expressions.en_US.srt 9 KB
  38. Month Expressions.mp4 42.3 MB
  7 - String Expressions
  39. Regular Expressions (RegEx).en_US.srt 12.7 KB
  39. Regular Expressions (RegEx).mp4 60.7 MB
  40. Find & Replace.mp4 28.1 MB
  41. Date & Time Conversions.en_US.srt 9.5 KB
  41. Date & Time Conversions.mp4 32.6 MB
  8 - Computation Expressions
  42. Hashing Sensitive Data.en_US.srt 6.9 KB
  42. Hashing Sensitive Data.mp4 19 MB
  43. Rank.en_US.srt 5.5 KB
  43. Rank.mp4 23.4 MB
  9 - Archived - Python Fundamentals
  1. Data Types int.html 3.2 KB
  10. Mathematical Operators Addition.html 3.4 KB
  11. Mathematical Operators Subtraction.html 3.4 KB
  12. Mathematical Operators Multiplication.html 3.4 KB
  13. Mathematical Operators Division.html 3.4 KB
  14. Mathematical Operators Modulo.html 3.2 KB
  15. Mathematical Operators Exponentiation.html 3.4 KB
  16. Comparison Operators Equal.html 3.4 KB
  17. Comparison Operators Not Equal.html 3.4 KB
  18. Logical Operators.html 3.6 KB
  19. If Statements.html 3.3 KB
  2. Data Types float.html 3.3 KB
  3. Data Types str.html 3.2 KB
  4. Data Types NoneType.html 3.3 KB
  44. Data Types.en_US.srt 2.9 KB
  44. Data Types.mp4 3.7 MB
  45. Data Structures.en_US.srt 3.1 KB
  45. Data Structures.mp4 4.1 MB
  46. Casting.en_US.srt 5 KB
  46. Casting.mp4 9.2 MB
  47. Mathematical Operators.en_US.srt 4.5 KB
  47. Mathematical Operators.mp4 12.7 MB
  48. Comparison Operators.en_US.srt 3.7 KB
  48. Comparison Operators.mp4 7.1 MB
  49. Logical Operators.en_US.srt 4.7 KB
  49. Logical Operators.mp4 8.6 MB
  5. Data Structures Lists.html 3.3 KB
  50. Membership Operators.en_US.srt 4.3 KB
  50. Membership Operators.mp4 12.8 MB
  51. If Statements.en_US.srt 3.8 KB
  51. If Statements.mp4 7.6 MB
  6. Data Structures Tuples.html 3.3 KB
  7. Data Structures Dictionaries.html 3.4 KB
  8. Data Structures Sets.html 3.3 KB
  9. Casting int to str.html 3.5 KB
  6. Installing Polars.en_US.srt 1.1 KB
  6. Installing Polars.mp4 2 MB
  7. Read CSV.en_US.srt 9.2 KB
  7. Read CSV.mp4 36.8 MB
  8. Write CSV - Part 1.en_US.srt 3.7 KB
  8. Write CSV - Part 1.mp4 13.5 MB
  9. Write CSV - Part 2.en_US.srt 6.1 KB
  9. Write CSV - Part 2.mp4 23.9 MB
  application_feedback.csv 512 B
  call_center_data.csv 18.8 KB
  credit_card_transactions.csv 1.5 MB
  customer_reviews.csv 20.6 KB
  daily_aggregate_sales_2024.csv 38 KB
  dates.csv 4.3 KB
  employees.csv 2.8 KB
  employees.ods 39.1 KB
  employees.tsv 2.8 KB
  fake_PII.csv 716.8 B
  long_form_dates.csv 921.6 B
  marketing_cost_01.csv 614.4 B
  marketing_cost_02.csv 512 B
  marketing_cost_03.csv 512 B
  marketing_cost_04.csv 512 B
  marketing_cost_05.csv 614.4 B
  marketing_cost_06.csv 512 B
  marketing_cost_07.csv 512 B
  marketing_cost_08.csv 512 B
  marketing_cost_09.csv 512 B
  marketing_cost_10.csv 614.4 B
  marketing_cost_11.csv 512 B
  marketing_cost_12.csv 512 B
  marketing_cost_all.csv 6.3 KB
  performance_data.csv 409.6 B
  properties.csv 22.8 KB
  random_dates.csv 614.4 B
  social_media_posts.csv 24.3 KB
  start_end_dates.csv 2.2 KB
  underwriting.csv 512 B
  unix_timestamps.csv 11.7 KB
  03 - Write CSV Part 1.ipynb 12.9 KB
  04 - Write CSV Part 2.ipynb 12.9 KB
  05 - Write Database.ipynb 8.5 KB
  06 - Read Database.ipynb 22.5 KB
  07- Read Excel.ipynb 8.6 KB
  08 - from_pandas.ipynb 1.5 KB
  09 - to_pandas.ipynb 17.1 KB
  10 - Read ODS.ipynb 40.4 KB
  11 - json_normalize.ipynb 55.3 KB
  12 - Scan CSV.ipynb 4.1 KB
  13 - Reading Multiple CSV Files.ipynb 6.7 KB
  14 - Write Database (SQL Server).ipynb 5.7 KB
  15 - Schemas.ipynb 23.5 KB
  16 - LazyFrame Query Optimization.ipynb 26.7 KB

Description


Data Analysis with Polars in Python
https://WebToolTip.com
Last updated 11/2024

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch

Language: English + subtitle | Duration: 4h 2m | Size: 1.04 GB
Master Data Manipulation with Polars - The High Performance DataFrame Library
What you'll learn

How to Read CSV Files into Polars DataFrames

How to Push Data from Polars into a Database

How to Read Excel Files into Polars DataFrames

How to Aggregate Data

How to Join DataFrames

How to Take Advantage of Polars' Superior Processing Speed
Requirements

No Prior Experience Required

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