| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ~Get Your Files Here ! | |||
| 1 - Introduction | |||
| 1. Introduction.en_GB.srt | 2.3 KB | ||
| 1. Introduction.mp4 | 14.3 MB | ||
| 1. Introduction_Resource_Lesson 1 pdf.pdf | 100.1 KB | ||
| 10 - Pandas Exercises | |||
| 2 - NumPy or Numerical Python | |||
| 10. NumPy Logical Operations.en_GB.srt | 5.5 KB | ||
| 10. NumPy Logical Operations.mp4 | 12.3 MB | ||
| 11. NumPy Array Broadcasting.en_GB.srt | 4.4 KB | ||
| 11. NumPy Array Broadcasting.mp4 | 7.8 MB | ||
| 12. NumPy Conditional Indexing.en_GB.srt | 6.1 KB | ||
| 12. NumPy Conditional Indexing.mp4 | 9.1 MB | ||
| 2. NumPy Installation.en_GB.srt | 4.4 KB | ||
| 2. NumPy Installation.mp4 | 14.5 MB | ||
| 3 - NumPy Exercises | |||
| 13. Exercises And Solutions.html | 204.8 B | ||
| 13. Exercises And Solutions_Resource_NumPy Exercises ipynb.bin | 25.1 KB | ||
| 13. Exercises And Solutions_Resource_Numpy Practice pdf.pdf | 144.2 KB | ||
| 14. Exercise 1.en_GB.srt | 7.7 KB | ||
| 14. Exercise 1.mp4 | 18.4 MB | ||
| 15. Exercise 2.en_GB.srt | 6.2 KB | ||
| 15. Exercise 2.mp4 | 39.4 MB | ||
| 16. Exercise 3.en_GB.srt | 3 KB | ||
| 16. Exercise 3.mp4 | 12.6 MB | ||
| 17. Exercise 4.en_GB.srt | 7.1 KB | ||
| 17. Exercise 4.mp4 | 77.4 MB | ||
| 18. Exercise 5.en_GB.srt | 5.6 KB | ||
| 18. Exercise 5.mp4 | 16.9 MB | ||
| 19. Exercise 6.en_GB.srt | 5.2 KB | ||
| 19. Exercise 6.mp4 | 30 MB | ||
| 4 - Data Structure in Pandas | |||
| 20. Pandas Series.en_GB.srt | 9.3 KB | ||
| 20. Pandas Series.mp4 | 43.1 MB | ||
| 21. Series Missing Values.en_GB.srt | 3.7 KB | ||
| 21. Series Missing Values.mp4 | 5.6 MB | ||
| 22. Applying Functions to Series.en_GB.srt | 2.3 KB | ||
| 22. Applying Functions to Series.mp4 | 3.5 MB | ||
| 23. Pandas DataFrames.en_GB.srt | 8.2 KB | ||
| 23. Pandas DataFrames.mp4 | 14.2 MB | ||
| 5 - DataFrame Manipulation | |||
| 24. Columns And Indexes In Pandas.en_GB.srt | 7.6 KB | ||
| 24. Columns And Indexes In Pandas.mp4 | 45.2 MB | ||
| 25. Accessing DataFrames With Loc[] and iLoc[].en_GB.srt | 15.8 KB | ||
| 25. Accessing DataFrames With Loc[] and iLoc[].mp4 | 72 MB | ||
| 26. Accessing Scalars Values In DataFrames at[] And iat[].en_GB.srt | 3.6 KB | ||
| 26. Accessing Scalars Values In DataFrames at[] And iat[].mp4 | 9.7 MB | ||
| 27. Filling And Replacing Values In DataFrames.en_GB.srt | 5.9 KB | ||
| 27. Filling And Replacing Values In DataFrames.mp4 | 26.7 MB | ||
| 28. Arithmetic Operations On DataFrames.en_GB.srt | 5.7 KB | ||
| 28. Arithmetic Operations On DataFrames.mp4 | 16.6 MB | ||
| 29. Concatenating DataFrames.en_GB.srt | 3.5 KB | ||
| 29. Concatenating DataFrames.mp4 | 22.1 MB | ||
| 30. Merging And Joining DataFrames.en_GB.srt | 7.5 KB | ||
| 30. Merging And Joining DataFrames.mp4 | 20.8 MB | ||
| 6 - Advanced Pandas Function | |||
| 31. Recap And Planning This Lesson.en_GB.srt | 1.3 KB | ||
| 31. Recap And Planning This Lesson.mp4 | 5.5 MB | ||
| 32. Pivot Tables.en_GB.srt | 7.9 KB | ||
| 32. Pivot Tables.mp4 | 43.2 MB | ||
| 33. GroupBy In DataFrames.en_GB.srt | 3.6 KB | ||
| 33. GroupBy In DataFrames.mp4 | 13.1 MB | ||
| 34. Binning Values And The Cut Function.en_GB.srt | 5.7 KB | ||
| 34. Binning Values And The Cut Function.mp4 | 18 MB | ||
| 35. MultiLevel Indexing In DataFrames.en_GB.srt | 5.4 KB | ||
| 35. MultiLevel Indexing In DataFrames.mp4 | 16 MB | ||
| 36. Filling Missing Values.en_GB.srt | 8.7 KB | ||
| 36. Filling Missing Values.mp4 | 30.4 MB | ||
| 7 - Time and Time Series in Pandas | |||
| 37. Date Time In Python.en_GB.srt | 6 KB | ||
| 37. Date Time In Python.mp4 | 10.9 MB | ||
| 38. Time Zones And Time Deltas In Python.en_GB.srt | 5.8 KB | ||
| 38. Time Zones And Time Deltas In Python.mp4 | 19.2 MB | ||
| 39. Rolling And Shift Functions.en_GB.srt | 5.6 KB | ||
| 39. Rolling And Shift Functions.mp4 | 11.5 MB | ||
| 8 - Reading and Writing Data with Pandas | |||
| 40. Reading And Writing Files With Pandas.en_GB.srt | 3.7 KB | ||
| 40. Reading And Writing Files With Pandas.mp4 | 6 MB | ||
| 9 - Data Visualization with Pandas | |||
| 41. Plotting Graphs Bars And Histograms.en_GB.srt | 11.3 KB | ||
| 41. Plotting Graphs Bars And Histograms.mp4 | 54.8 MB | ||
| 42. Boxplots.en_GB.srt | 5.3 KB | ||
| 42. Boxplots.mp4 | 11.4 MB | ||
| 43. Area Plots.en_GB.srt | 2.3 KB | ||
| 43. Area Plots.mp4 | 4.4 MB | ||
| 44. Scatter Points.en_GB.srt | 3.9 KB | ||
| 44. Scatter Points.mp4 | 9.1 MB | ||
| 45. Pie Charts.en_GB.srt | 4.2 KB | ||
| 45. Pie Charts.mp4 | 16.4 MB | ||
| 46. Conclusion.en_GB.srt | 921.6 B | ||
| 46. Conclusion.mp4 | 1 MB | ||
| 3. NumPy Basic Functions.en_GB.srt | 10.2 KB | ||
| 3. NumPy Basic Functions.mp4 | 28.9 MB | ||
| 4. NumPy Slicing.en_GB.srt | 8.8 KB | ||
| 4. NumPy Slicing.mp4 | 14.2 MB | ||
| 5. NumPy Multidimentional Arrays.en_GB.srt | 5.4 KB | ||
| 5. NumPy Multidimentional Arrays.mp4 | 9.8 MB | ||
| 6. NumPy DTypes.en_GB.srt | 4.3 KB | ||
| 6. NumPy DTypes.mp4 | 11 MB | ||
| 7. NumPy Structured Arrays.en_GB.srt | 5.7 KB | ||
| 7. NumPy Structured Arrays.mp4 | 8.6 MB | ||
| 8. NumPy Reading And Writing Data Files.en_GB.srt | 10.2 KB | ||
| 8. NumPy Reading And Writing Data Files.mp4 | 14.9 MB | ||
| 9. NumPy Arithmetic Operations.en_GB.srt | 4.6 KB | ||
| 9. NumPy Arithmetic Operations.mp4 | 6 MB | ||
| 47. Pandas Exercises.html | 204.8 B | ||
| 47. Pandas Exercises_Resource_01 Pandas Exercises pdf.pdf | 309.6 KB | ||
| 47. Pandas Exercises_Resource_EURUSD FOREX csv.csv | 470.1 KB | ||
| 47. Pandas Exercises_Resource_oil spill csv.csv | 225.5 KB | ||
| 48. Exercise 1 Financial Data Analysis.en_GB.srt | 9.7 KB | ||
| 48. Exercise 1 Financial Data Analysis.mp4 | 92.2 MB | ||
| 48. Exercise 1 Financial Data Analysis_Resource_Pandas 01 ipynb.bin | 1.3 KB | ||
| 49. Exercise 2 Stacked BarPlots In Pandas.en_GB.srt | 6.5 KB | ||
| 49. Exercise 2 Stacked BarPlots In Pandas.mp4 | 49.1 MB | ||
| 49. Exercise 2 Stacked BarPlots In Pandas_Resource_Pandas 02 ipynb.bin | 13.2 KB | ||
| 50. Exercise 3 Dinner With Friends.en_GB.srt | 13.7 KB | ||
| 50. Exercise 3 Dinner With Friends.mp4 | 60 MB | ||
| 50. Exercise 3 Dinner With Friends_Resource_Pandas 03 ipynb.bin | 55.3 KB | ||
| 51. Exercise 4 Oil spill in water Data cleaning example.en_GB.srt | 10 KB | ||
| 51. Exercise 4 Oil spill in water Data cleaning example.mp4 | 94 MB | ||
| 51. Exercise 4 Oil spill in water Data cleaning example_Resource_oil spill csv.csv | 225.5 KB | ||
| 51. Exercise 4 Oil spill in water Data cleaning example_Resource_oil spill ipynb.bin | 3.7 KB | ||
| 52. Exercise 5 Financial Trading Analysis Prediction.en_GB.srt | 18.6 KB | ||
| 52. Exercise 5 Financial Trading Analysis Prediction.mp4 | 154.4 MB | ||
| 52. Exercise 5 Financial Trading Analysis Prediction_Resource_02 EURUSD Analysis ipynb.bin | 63.2 KB | ||
| 52. Exercise 5 Financial Trading Analysis Prediction_Resource_EURUSD FOREX csv.csv | 470.1 KB | ||
| 53. Exercise 6 Financial Trading analyzing the engulfing candles.en_GB.srt | 11 KB | ||
| 53. Exercise 6 Financial Trading analyzing the engulfing candles.mp4 | 75.4 MB | ||
| 53. Exercise 6 Financial Trading analyzing the engulfing candles_Resource_02 EURUSD Analysis ipynb.bin | 63.2 KB | ||
| 53. Exercise 6 Financial Trading analyzing the engulfing candles_Resource_EURUSD FOREX csv.csv | 470.1 KB |
Data Analysis With Pandas And NumPy In Python
https://WebToolTip.com
Last updated 8/2024
Created by Dr Ziad Francis
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English + subtitle | Duration: 53 Lectures ( 4h 46m ) | Size: 1.4 GB
NumPy and Pandas for Data Analysis and Financial Applications, Examples in Trading Market Analysis
What you'll learn
Data manipulation: working with data, filter, sort, and transform large datasets
Data analysis: perform a wide range of data analysis tasks, including aggregating data, performing statistical calculations
Data visualization: create a variety of visualizations to help understand data and communicate findings
Data wrangling: cleaning and preparing data for analysis, handling missing data, merge datasets, and reshape data
Requirements
Python basics, for loops, condition statements, python containers; lists, sets, tuples and dictionnaries.
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
|
Udemy - Renew Your Power Bi Data Analyst Certification (Pl-300 Exam) Posted by
freecoursewb in Other
|
2.5 GB | freecoursewb | 2 days | 6 | 6 |
| 1.3 GB | freecoursewb | 2 days | 0 | 0 | |
| 3.8 GB | freecoursewb | 1 week | 47 | 23 | |
| 2.6 GB | freecoursewb | 1 week | 17 | 7 | |
|
Udemy - Data Structures and Algorithms and LeetCode - CPP and Python Posted by
freecoursewb in Other
|
633.7 MB | freecoursewb | 1 week | 16 | 4 |
All Comments