[FreeCoursesOnline.Me] [Packt] Data Wrangling with Python 3.x [FCO]
File List
- 02.Working with Data from Excel and PDF Files/0202.Importing and Parsing Excel Files – Part 2.mp4 205.7 MB
- 02.Working with Data from Excel and PDF Files/0204.Manipulating PDF Files in Python – Part 2.mp4 126.7 MB
- 02.Working with Data from Excel and PDF Files/0203.Manipulating PDF Files in Python – Part 1.mp4 125.3 MB
- 07.Let the Visualizations Tell the Story/0704.Visualizations in Python – Part 2.mp4 95.7 MB
- 01.Gathering and Parsing Data/0102.Installing Anaconda Navigator on WindowsLinux.mp4 53.5 MB
- 01.Gathering and Parsing Data/0106.Scraping Data from Public Web – Part 2.mp4 49.4 MB
- 07.Let the Visualizations Tell the Story/0705.Exploring an Online Visualization Tool (RAWGraphs).mp4 36.7 MB
- 04.Cleaning Structured Data/0407.Dealing with Missing Values.mp4 33.6 MB
- 03.Storing Data in Persistent Storage/0302.Storing Data in SQLite Databases.mp4 33.4 MB
- 04.Cleaning Structured Data/0406.MergingConcatenatingJoining DataFrames.mp4 31.5 MB
- 01.Gathering and Parsing Data/0101.The Course Overview.mp4 30.8 MB
- 05.More Data Cleaning and Transformation/0504.RescaleStandardize Column Values.mp4 29.4 MB
- 01.Gathering and Parsing Data/0103.Importing and Parsing CSV in Python.mp4 28.5 MB
- 04.Cleaning Structured Data/0405.Indexing DataFrame to Retrieve Specific Columns and Rows.mp4 28.2 MB
- 05.More Data Cleaning and Transformation/0505.Common Cleaning Operations.mp4 27.8 MB
- 03.Storing Data in Persistent Storage/0304.Storing Data in Elasticsearch.mp4 27.5 MB
- 04.Cleaning Structured Data/0403.RenamingAddingRemoving the DataFrame Columns.mp4 26.7 MB
- 07.Let the Visualizations Tell the Story/0703.Visualizations in Python – Part 1.mp4 26.3 MB
- 04.Cleaning Structured Data/0404.Dropping Duplicate Rows.mp4 26.2 MB
- 04.Cleaning Structured Data/0402.ViewingInspecting DataFrames.mp4 26.0 MB
- 05.More Data Cleaning and Transformation/0501.Filtering and Sorting of DataFrame.mp4 25.9 MB
- 03.Storing Data in Persistent Storage/0303.Storing Data in MongoDB.mp4 25.2 MB
- 06.Performing Statistical Analysis/0603.Split-Apply-Combine (Performing Group By Operation).mp4 24.4 MB
- 05.More Data Cleaning and Transformation/0502.EncodingMapping Existing Values – Part 1.mp4 23.5 MB
- 06.Performing Statistical Analysis/0604.Descriptive Statistics Using Python – Part 1.mp4 23.0 MB
- 01.Gathering and Parsing Data/0104.Importing and Parsing JSON in Python.mp4 22.8 MB
- 06.Performing Statistical Analysis/0605.Descriptive Statistics Using Python – Part 2.mp4 22.3 MB
- 05.More Data Cleaning and Transformation/0506.Exporting Datasets for Future Use.mp4 22.1 MB
- 01.Gathering and Parsing Data/0105.Scraping Data from Public Web – Part 1.mp4 20.9 MB
- 02.Working with Data from Excel and PDF Files/0201.Importing and Parsing Excel Files – Part 1.mp4 20.3 MB
- 05.More Data Cleaning and Transformation/0503.EncodingMapping Existing Values – Part 2.mp4 18.8 MB
- 03.Storing Data in Persistent Storage/0301.Difference between Relational and Non-Relational Databases.mp4 14.7 MB
- 04.Cleaning Structured Data/0401.The Most Important Step in Data Analysis.mp4 11.9 MB
- 07.Let the Visualizations Tell the Story/0702.Cool Visualization of Real-World Datasets of World Population Evolution.mp4 7.1 MB
- 03.Storing Data in Persistent Storage/0305.Comparative Study of Databases for Storage.mp4 5.0 MB
- 06.Performing Statistical Analysis/0602.Types of Column NamesFeaturesAttributes in Structured Data.mp4 4.4 MB
- 07.Let the Visualizations Tell the Story/0701.Using Visualizations.mp4 3.8 MB
- 06.Performing Statistical Analysis/0601.Different Uses of Packages (Pandas, NumPy, SciPy, and Matplotlib).mp4 3.1 MB
- Exercise Files/exercise_files.zip 966.1 KB
- FreeCoursesOnline.Me.html 108.3 KB
- FreeTutorials.Eu.html 102.2 KB
- Discuss.FreeTutorials.Eu.html 31.3 KB
- [TGx]Downloaded from torrentgalaxy.org.txt 524 bytes
- How you can help Team-FTU.txt 259 bytes
- Torrent Downloaded From GloDls.to.txt 84 bytes
Download Torrent
Related Resources
Copyright Infringement
If the content above is not authorized, please contact us via anywarmservice[AT]gmail.com. Remember to include the full url in your complaint.