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种子名称： [FreeCourseSite.com] Udemy - Pandas with Python Tutorial
文件类型： 视频
文件数目： 59个文件
文件大小： 2.59 GB
收录时间： 2019-7-7 18:02
已经下载： 3次
资源热度： 93
最近下载： 2024-11-16 00:20

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[FreeCourseSite.com] Udemy - Pandas with Python Tutorial.torrent

1. Introduction/1. Introduction to Pandas with Python.mp437.11MB

2. Data Set/1. Understanding Jupiter Environment.mp420.94MB

2. Data Set/2. Reading the Data Set.mp459.03MB

2. Data Set/3. Series and Data Frame.mp420.68MB

2. Data Set/4. Operations in Data Set.mp425.47MB

2. Data Set/5. More on Panda Functions.mp447.2MB

2. Data Set/6. Column Names and Operation.mp478.68MB

2. Data Set/7. Removing Columns and Rows.mp421.43MB

2. Data Set/8. Sorting Data Frame.mp429.27MB

2. Data Set/9. Filtering Data.mp458.98MB

3. Data Analysis/1. Filter Multiple Criteria.mp450.97MB

3. Data Analysis/10. Plotting series in Pandas.mp422.46MB

3. Data Analysis/11. Dealing with Null Values.mp435.56MB

3. Data Analysis/12. Uses of Index.mp449.22MB

3. Data Analysis/13. Column in Index.mp452.23MB

3. Data Analysis/14. Output of Data.mp447.9MB

3. Data Analysis/15. Functions of iX Method.mp470.98MB

3. Data Analysis/16. InPlace Parameter.mp434.42MB

3. Data Analysis/17. Inspecting the Space.mp431.44MB

3. Data Analysis/18. Reducing the Space.mp469.87MB

3. Data Analysis/19. Using in Country Series.mp427.93MB

3. Data Analysis/2. Selective Columns and Rows.mp417.86MB

3. Data Analysis/20. Creating Manual Data Frame.mp432.66MB

3. Data Analysis/21. Random Sampling with Pandas.mp431.36MB

3. Data Analysis/22. Concept of Dummy Coding.mp482.49MB

3. Data Analysis/23. Creating Dummified Values.mp482.44MB

3. Data Analysis/24. Duplicates in Data Frame.mp448.64MB

3. Data Analysis/25. Functions for Date and Time.mp468.9MB

3. Data Analysis/26. Setting with Copy Warning.mp437.7MB

3. Data Analysis/27. Example on Copy Warning.mp435.34MB

3. Data Analysis/28. Changing the Display Option.mp439.66MB

3. Data Analysis/29. Formatting the Data.mp453.04MB

3. Data Analysis/3. Data Frame and Series.mp411.16MB

3. Data Analysis/30. Tricks for Display Options.mp439.82MB

3. Data Analysis/31. Data with Rows and Columns.mp441.09MB

3. Data Analysis/32. Converting Data Frame.mp418.45MB

3. Data Analysis/4. Axis Parameter.mp428.86MB

3. Data Analysis/5. String Methods in Pandas.mp428.94MB

3. Data Analysis/6. Changing the Data Types.mp431.5MB

3. Data Analysis/7. Example of Data Type Change.mp427.59MB

3. Data Analysis/8. Group by Functions.mp430.97MB

3. Data Analysis/9. Functions on Series.mp430.77MB

4. Azure Data Lake/1. Introduction to Azure Data Lake.mp447.42MB

4. Azure Data Lake/10. More on Crosstab.mp467.57MB

4. Azure Data Lake/11. More Options with Crosstab.mp480.08MB

4. Azure Data Lake/12. Functions of Pivot.mp429.92MB

4. Azure Data Lake/13. Pivot Table Method.mp462.54MB

4. Azure Data Lake/14. Example on Pivot Table.mp488.07MB

4. Azure Data Lake/15. Data Frame to CSV File.mp457.34MB

4. Azure Data Lake/16. Using Excel Functions.mp458.7MB

4. Azure Data Lake/2. Merging Data Frames.mp470.34MB

4. Azure Data Lake/3. Shaping a Data Frame.mp454.88MB

4. Azure Data Lake/4. Filling NA Values.mp424.74MB

4. Azure Data Lake/5. Importing Time Series Data.mp459.66MB

4. Azure Data Lake/6. Working with Interpolate Method.mp467.93MB

4. Azure Data Lake/7. Stacking and Unstacking.mp480.79MB

4. Azure Data Lake/8. Stacking and Unstacking for 3 Levels.mp433.77MB

4. Azure Data Lake/9. Concept of Crosstab.mp450.41MB

5. Summary/1. Summary on Pandas.mp49.03MB