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[DesireCourse.Net] Udemy - Complete Data Wrangling & Data Visualisation With Python

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视频 2023-1-31 22:37 2024-12-22 11:56 171 2.95 GB 51
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文件列表
  1. 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/1. Welcome to the Course.mp412.43MB
  2. 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/3. Python Data Science Environment.mp4105.06MB
  3. 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/4. For Mac Users.mp450.07MB
  4. 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/5. Introduction to IPythonJupyter.mp4102.69MB
  5. 1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/6. ipython in Browser.mp440.48MB
  6. 2. Read in Data From Different Sources With Pandas/1. What are Pandas.mp485.04MB
  7. 2. Read in Data From Different Sources With Pandas/2. Read CSV Data.mp453.86MB
  8. 2. Read in Data From Different Sources With Pandas/3. Read Excel Data.mp442.4MB
  9. 2. Read in Data From Different Sources With Pandas/4. Read in HTML Data.mp4129.55MB
  10. 3. Data Cleaning/1. Remove NA Values.mp455.95MB
  11. 3. Data Cleaning/2. Missing Values in a Real Dataset.mp436.88MB
  12. 3. Data Cleaning/3. Data Imputation.mp456.41MB
  13. 3. Data Cleaning/4. Imputing Qualitative Values.mp420.97MB
  14. 3. Data Cleaning/5. Theory Behind k-NN Algorithm.mp496.2MB
  15. 3. Data Cleaning/6. Use k-NN for Data Imputation.mp444.22MB
  16. 4. Basic Data Wrangling/1. Basic Principles.mp426.51MB
  17. 4. Basic Data Wrangling/2. Preliminary Data Explorations.mp464.53MB
  18. 4. Basic Data Wrangling/3. Basic Data Handling With Conditional Statements.mp449.41MB
  19. 4. Basic Data Wrangling/4. Drop ColumnRow.mp447.63MB
  20. 4. Basic Data Wrangling/5. Change Column Name.mp425.18MB
  21. 4. Basic Data Wrangling/6. Change the Column Type.mp422.67MB
  22. 4. Basic Data Wrangling/7. Explore Date Related Data.mp425.13MB
  23. 4. Basic Data Wrangling/8. Simple Date Related Computations.mp425.27MB
  24. 5. More Data Wrangling/1. Data Grouping.mp497.86MB
  25. 5. More Data Wrangling/2. Data Subsetting and Indexing.mp4101.98MB
  26. 5. More Data Wrangling/3. More Data Subsetting.mp469.37MB
  27. 5. More Data Wrangling/4. Extract Information From Strings.mp438.29MB
  28. 5. More Data Wrangling/5. (Fuzzy) String Matching.mp418.6MB
  29. 5. More Data Wrangling/6. Ranking & Sorting.mp482.31MB
  30. 5. More Data Wrangling/7. Concatenate.mp470.05MB
  31. 5. More Data Wrangling/8. Merging and Joining.mp496.84MB
  32. 6. Feature Selection and Transformation/1. Correlation Analysis.mp456.42MB
  33. 6. Feature Selection and Transformation/2. Using Correlation to Decide Which Features to Retain.mp434.15MB
  34. 6. Feature Selection and Transformation/3. Univariate Feature Selection.mp439.17MB
  35. 6. Feature Selection and Transformation/4. Recursive Feature Elimination (RFE).mp436.53MB
  36. 6. Feature Selection and Transformation/5. Theory Behind PCA.mp423.87MB
  37. 6. Feature Selection and Transformation/6. Implement PCA.mp426.72MB
  38. 6. Feature Selection and Transformation/7. Data Standardisation.mp432.47MB
  39. 6. Feature Selection and Transformation/8. Create a New Feature.mp439.97MB
  40. 7. Theory Behind Data Visualisation/1. What is Data Visualisation.mp468.35MB
  41. 7. Theory Behind Data Visualisation/2. Some Theoretical Principles Behind Data Visualisation.mp466.11MB
  42. 8. Most Common Data Visualizations/1. Histograms-Visualize the Distribution of Continuous Numerical Variables.mp499.1MB
  43. 8. Most Common Data Visualizations/2. Boxplots-Visualize the Distribution of Continuous Numerical Variables.mp440.52MB
  44. 8. Most Common Data Visualizations/3. Scatter plot-Relationship Between Two Numerical Variables.mp4106.83MB
  45. 8. Most Common Data Visualizations/4. Barplot.mp4170.67MB
  46. 8. Most Common Data Visualizations/5. Pie Chart.mp437.88MB
  47. 8. Most Common Data Visualizations/6. Line Charts.mp4116.79MB
  48. 8. Most Common Data Visualizations/7. More Line Charts.mp418.94MB
  49. 8. Most Common Data Visualizations/8. Some More Plot Types.mp475.99MB
  50. 8. Most Common Data Visualizations/9. And Some More.mp478.5MB
  51. 9. Miscallaneous Information/1. Using Colabs as an Online Jupyter Notebook.mp454.82MB
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