Download Data Analysis with Polars in Python torrent

Data Analysis with Polars in Python

Torrent:	Data Analysis with Polars in Python
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
Downloads:	84
Category:	Other /Tutorials
Size:	1.1 GB
Show Files »	[ WebToolTip.com ] Data Analysis with Polars in Python Get Bonus Downloads Here.url (0.2 KB) ~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 (10.0 MB) 4. Extensions for Visual Studio Code.en_US.srt (2.9 KB) 4. Extensions for Visual Studio Code.mp4 (13.0 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 - 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) 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 (8.0 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 (1.0 KB) Datasets Accounting.xlsx (19.1 KB) Electric_Vehicles.json (78.0 MB) Marketing Cost Data marketing_cost_01.csv (0.6 KB) marketing_cost_02.csv (0.5 KB) marketing_cost_03.csv (0.5 KB) marketing_cost_04.csv (0.5 KB) marketing_cost_05.csv (0.6 KB) marketing_cost_06.csv (0.5 KB) marketing_cost_07.csv (0.5 KB) marketing_cost_08.csv (0.5 KB) marketing_cost_09.csv (0.5 KB) marketing_cost_10.csv (0.6 KB) marketing_cost_11.csv (0.5 KB) marketing_cost_12.csv (0.5 KB) marketing_cost_all.csv (6.3 KB) application_feedback.csv (0.5 KB) 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 (38.0 KB) dates.csv (4.3 KB) employees.csv (2.8 KB) employees.ods (39.1 KB) employees.tsv (2.8 KB) fake_PII.csv (0.7 KB) long_form_dates.csv (0.9 KB) performance_data.csv (0.4 KB) properties.csv (22.8 KB) random_dates.csv (0.6 KB) social_media_posts.csv (24.3 KB) start_end_dates.csv (2.2 KB) underwriting.csv (0.5 KB) unix_timestamps.csv (11.7 KB) 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 (3.0 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 (13.0 KB) 16. JSON Normalize.mp4 files
Added:	2026-05-31 16:46:33
Language:	English
Peers:	Seeders : 6 , Leechers : 8
Release name:	Data Analysis with Polars in Python
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