[FTUForum.com] [UDEMY] Complete Data Wrangling & Data Visualisation With Python [FTU]

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[FTUForum.com] [UDEMY] Complete Data Wrangling & Data Visualisation With Python [FTU]

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种子哈希：34d0d57c99cfce36d09c211173af421f5fc833ff
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收录时间：2021-03-07
最近下载：2026-06-09
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文件列表

  • 8. Most Common Data Visualizations/4. Barplot.mp4 179.0 MB
  • 2. Read in Data From Different Sources With Pandas/4. Read in HTML Data.mp4 135.8 MB
  • 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/2.1 Data and Code.zip.zip 129.3 MB
  • 8. Most Common Data Visualizations/6. Line Charts.mp4 122.5 MB
  • 8. Most Common Data Visualizations/3. Scatter plot-Relationship Between Two Numerical Variables.mp4 112.0 MB
  • 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/3. Python Data Science Environment.mp4 110.2 MB
  • 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/5. Introduction to IPythonJupyter.mp4 107.7 MB
  • 5. More Data Wrangling/2. Data Subsetting and Indexing.mp4 106.9 MB
  • 8. Most Common Data Visualizations/1. Histograms-Visualize the Distribution of Continuous Numerical Variables.mp4 103.9 MB
  • 5. More Data Wrangling/1. Data Grouping.mp4 102.6 MB
  • 5. More Data Wrangling/8. Merging and Joining.mp4 101.5 MB
  • 3. Data Cleaning/5. Theory Behind k-NN Algorithm.mp4 100.9 MB
  • 2. Read in Data From Different Sources With Pandas/1. What are Pandas.mp4 89.2 MB
  • 5. More Data Wrangling/6. Ranking & Sorting.mp4 86.3 MB
  • 8. Most Common Data Visualizations/9. And Some More.mp4 82.3 MB
  • 8. Most Common Data Visualizations/8. Some More Plot Types.mp4 79.7 MB
  • 5. More Data Wrangling/7. Concatenate.mp4 73.5 MB
  • 5. More Data Wrangling/3. More Data Subsetting.mp4 72.7 MB
  • 7. Theory Behind Data Visualisation/1. What is Data Visualisation.mp4 71.7 MB
  • 7. Theory Behind Data Visualisation/2. Some Theoretical Principles Behind Data Visualisation.mp4 69.3 MB
  • 4. Basic Data Wrangling/2. Preliminary Data Explorations.mp4 67.7 MB
  • 6. Feature Selection and Transformation/1. Correlation Analysis.mp4 59.2 MB
  • 3. Data Cleaning/3. Data Imputation.mp4 59.1 MB
  • 3. Data Cleaning/1. Remove NA Values.mp4 58.7 MB
  • 9. Miscallaneous Information/1. Using Colabs as an Online Jupyter Notebook.mp4 57.5 MB
  • 2. Read in Data From Different Sources With Pandas/2. Read CSV Data.mp4 56.5 MB
  • 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/4. For Mac Users.mp4 52.5 MB
  • 4. Basic Data Wrangling/3. Basic Data Handling With Conditional Statements.mp4 51.8 MB
  • 4. Basic Data Wrangling/4. Drop ColumnRow.mp4 49.9 MB
  • 3. Data Cleaning/6. Use k-NN for Data Imputation.mp4 46.4 MB
  • 2. Read in Data From Different Sources With Pandas/3. Read Excel Data.mp4 44.5 MB
  • 8. Most Common Data Visualizations/2. Boxplots-Visualize the Distribution of Continuous Numerical Variables.mp4 42.5 MB
  • 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/6. ipython in Browser.mp4 42.4 MB
  • 6. Feature Selection and Transformation/8. Create a New Feature.mp4 41.9 MB
  • 6. Feature Selection and Transformation/3. Univariate Feature Selection.mp4 41.1 MB
  • 5. More Data Wrangling/4. Extract Information From Strings.mp4 40.2 MB
  • 8. Most Common Data Visualizations/5. Pie Chart.mp4 39.7 MB
  • 3. Data Cleaning/2. Missing Values in a Real Dataset.mp4 38.7 MB
  • 6. Feature Selection and Transformation/4. Recursive Feature Elimination (RFE).mp4 38.3 MB
  • 6. Feature Selection and Transformation/2. Using Correlation to Decide Which Features to Retain.mp4 35.8 MB
  • 6. Feature Selection and Transformation/7. Data Standardisation.mp4 34.0 MB
  • 6. Feature Selection and Transformation/6. Implement PCA.mp4 28.0 MB
  • 4. Basic Data Wrangling/1. Basic Principles.mp4 27.8 MB
  • 4. Basic Data Wrangling/8. Simple Date Related Computations.mp4 26.5 MB
  • 4. Basic Data Wrangling/5. Change Column Name.mp4 26.4 MB
  • 4. Basic Data Wrangling/7. Explore Date Related Data.mp4 26.3 MB
  • 6. Feature Selection and Transformation/5. Theory Behind PCA.mp4 25.0 MB
  • 4. Basic Data Wrangling/6. Change the Column Type.mp4 23.8 MB
  • 3. Data Cleaning/4. Imputing Qualitative Values.mp4 22.0 MB
  • 8. Most Common Data Visualizations/7. More Line Charts.mp4 19.9 MB
  • 5. More Data Wrangling/5. (Fuzzy) String Matching.mp4 19.5 MB
  • 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/1. Welcome to the Course.mp4 13.0 MB
  • 8. Most Common Data Visualizations/4. Barplot.vtt 23.1 kB
  • 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/5. Introduction to IPythonJupyter.vtt 17.6 kB
  • 8. Most Common Data Visualizations/3. Scatter plot-Relationship Between Two Numerical Variables.vtt 12.4 kB
  • 8. Most Common Data Visualizations/6. Line Charts.vtt 12.3 kB
  • 8. Most Common Data Visualizations/1. Histograms-Visualize the Distribution of Continuous Numerical Variables.vtt 12.0 kB
  • 2. Read in Data From Different Sources With Pandas/4. Read in HTML Data.vtt 11.4 kB
  • 5. More Data Wrangling/8. Merging and Joining.vtt 11.0 kB
  • 8. Most Common Data Visualizations/8. Some More Plot Types.vtt 10.8 kB
  • 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/3. Python Data Science Environment.vtt 10.4 kB
  • 7. Theory Behind Data Visualisation/1. What is Data Visualisation.vtt 10.1 kB
  • 2. Read in Data From Different Sources With Pandas/1. What are Pandas.vtt 10.0 kB
  • 3. Data Cleaning/3. Data Imputation.vtt 9.2 kB
  • 6. Feature Selection and Transformation/1. Correlation Analysis.vtt 8.8 kB
  • 5. More Data Wrangling/1. Data Grouping.vtt 8.5 kB
  • 8. Most Common Data Visualizations/9. And Some More.vtt 8.5 kB
  • 5. More Data Wrangling/3. More Data Subsetting.vtt 8.2 kB
  • 5. More Data Wrangling/7. Concatenate.vtt 8.1 kB
  • 4. Basic Data Wrangling/2. Preliminary Data Explorations.vtt 8.0 kB
  • 5. More Data Wrangling/2. Data Subsetting and Indexing.vtt 8.0 kB
  • 5. More Data Wrangling/6. Ranking & Sorting.vtt 7.6 kB
  • 7. Theory Behind Data Visualisation/2. Some Theoretical Principles Behind Data Visualisation.vtt 7.3 kB
  • 3. Data Cleaning/5. Theory Behind k-NN Algorithm.vtt 6.7 kB
  • 9. Miscallaneous Information/1. Using Colabs as an Online Jupyter Notebook.vtt 6.7 kB
  • 3. Data Cleaning/1. Remove NA Values.vtt 6.6 kB
  • 3. Data Cleaning/2. Missing Values in a Real Dataset.vtt 6.5 kB
  • 3. Data Cleaning/6. Use k-NN for Data Imputation.vtt 6.2 kB
  • 8. Most Common Data Visualizations/5. Pie Chart.vtt 6.0 kB
  • 6. Feature Selection and Transformation/8. Create a New Feature.vtt 5.9 kB
  • 2. Read in Data From Different Sources With Pandas/2. Read CSV Data.vtt 5.8 kB
  • 8. Most Common Data Visualizations/2. Boxplots-Visualize the Distribution of Continuous Numerical Variables.vtt 5.6 kB
  • 6. Feature Selection and Transformation/2. Using Correlation to Decide Which Features to Retain.vtt 5.2 kB
  • 4. Basic Data Wrangling/1. Basic Principles.vtt 4.7 kB
  • 6. Feature Selection and Transformation/3. Univariate Feature Selection.vtt 4.7 kB
  • 4. Basic Data Wrangling/4. Drop ColumnRow.vtt 4.4 kB
  • 5. More Data Wrangling/4. Extract Information From Strings.vtt 4.3 kB
  • 6. Feature Selection and Transformation/7. Data Standardisation.vtt 4.2 kB
  • 4. Basic Data Wrangling/3. Basic Data Handling With Conditional Statements.vtt 4.2 kB
  • 6. Feature Selection and Transformation/6. Implement PCA.vtt 4.2 kB
  • 6. Feature Selection and Transformation/4. Recursive Feature Elimination (RFE).vtt 4.2 kB
  • 4. Basic Data Wrangling/6. Change the Column Type.vtt 4.0 kB
  • 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/4. For Mac Users.vtt 3.9 kB
  • 4. Basic Data Wrangling/8. Simple Date Related Computations.vtt 3.9 kB
  • 4. Basic Data Wrangling/7. Explore Date Related Data.vtt 3.7 kB
  • 4. Basic Data Wrangling/5. Change Column Name.vtt 3.7 kB
  • 2. Read in Data From Different Sources With Pandas/3. Read Excel Data.vtt 3.6 kB
  • 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/6. ipython in Browser.vtt 3.5 kB
  • 3. Data Cleaning/4. Imputing Qualitative Values.vtt 3.4 kB
  • 6. Feature Selection and Transformation/5. Theory Behind PCA.vtt 3.0 kB
  • 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/1. Welcome to the Course.vtt 2.9 kB
  • 5. More Data Wrangling/5. (Fuzzy) String Matching.vtt 2.8 kB
  • 8. Most Common Data Visualizations/7. More Line Charts.vtt 2.3 kB
  • 0. Websites you may like/1. (FreeTutorials.Us) Download Udemy Paid Courses For Free.url 328 Bytes
  • 0. Websites you may like/5. (Discuss.FTUForum.com) FTU Discussion Forum.url 294 Bytes
  • 0. Websites you may like/2. (FreeCoursesOnline.Me) Download Udacity, Masterclass, Lynda, PHLearn, Pluralsight Free.url 286 Bytes
  • 0. Websites you may like/4. (FTUApps.com) Download Cracked Developers Applications For Free.url 239 Bytes
  • 0. Websites you may like/How you can help Team-FTU.txt 237 Bytes
  • 0. Websites you may like/3. (NulledPremium.com) Download Cracked Website Themes, Plugins, Scripts And Stock Images.url 163 Bytes
  • 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/2. Data & Script For the Course.html 123 Bytes

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