[FreeCourseSite Com] Udemy - Data Analysis With Pandas And Python

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[FreeCourseSite com] Udemy - Data Analysis with Pandas and Python

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[FreeCourseSite com] Udemy - Data Analysis with Pandas and Python.torrent
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eBooks
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6a8404d24c7097caf190ee9590a491c99e9ba88d
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2.3 GB in 99 files
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Uploaded on 06-02-2018 by our crawler pet called "Spidey".
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Description



Udemy - Data Analysis with Pandas and Python

Welcome to the most comprehensive Pandas course available on Udemy! An excellent choice for both beginners and experts looking to expand their knowledge on one of the most popular Python libraries in the world!

For more Udemy Courses: https://freecoursesite.com

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Files in this torrent

FILENAMESIZE
1. Installation and Setup/1. Introduction to the Course.mp434 MB
1. Installation and Setup/1.1 pandas.zip.zip684.7 KB
1. Installation and Setup/10. Windows - Access the Command Prompt and Update Anaconda Libraries.mp419.1 MB
1. Installation and Setup/11. Windows - Unpack Course Materials + The Startdown and Shutdown Process.mp415.5 MB
1. Installation and Setup/12. Intro to the Jupyter Notebook Interface.mp49.3 MB
1. Installation and Setup/13. Cell Types and Cell Modes.mp411.7 MB
1. Installation and Setup/14. Code Cell Execution.mp48.2 MB
1. Installation and Setup/15. Popular Keyboard Shortcuts.mp46.3 MB
1. Installation and Setup/16. Import Libraries into Jupyter Notebook.mp411.5 MB
1. Installation and Setup/17. Python Crash Course, Part 1 - Data Types and Variables.mp412 MB
1. Installation and Setup/18. Python Crash Course, Part 2 - Lists.mp49 MB
1. Installation and Setup/19. Python Crash Course, Part 3 - Dictionaries.mp47.2 MB
1. Installation and Setup/2. Completed Course Files.html948 B
1. Installation and Setup/2.1 CompletedCourseFiles.zip.zip363.3 KB
1. Installation and Setup/20. Python Crash Course, Part 4 - Operators.mp47.9 MB
1. Installation and Setup/21. Python Crash Course, Part 5 - Functions.mp410.1 MB
1. Installation and Setup/3. Mac OS - Download the Anaconda Distribution.mp47.9 MB
1. Installation and Setup/4. Mac OS - Install Anaconda Distribution.mp418.1 MB
1. Installation and Setup/5. Mac OS - Access the Terminal.mp46.4 MB
1. Installation and Setup/6. Mac OS - Update Anaconda Libraries.mp435.3 MB
1. Installation and Setup/7. Mac OS - Unpack Course Materials + The Startdown and Shutdown Process.mp422.2 MB
1. Installation and Setup/8. Windows - Download the Anaconda Distribution.mp47.6 MB
1. Installation and Setup/9. Windows - Install Anaconda Distribution.mp415.2 MB
10. Working with Dates and Times/1. Intro to the Working with Dates and Times Module.mp46.3 MB
10. Working with Dates and Times/10. Install pandas-datareader Library.mp45.9 MB
10. Working with Dates and Times/11. Import Financial Data Set with pandas_datareader Library.mp425.5 MB
10. Working with Dates and Times/12. Selecting Rows from a DataFrame with a DateTimeIndex.mp418.3 MB
10. Working with Dates and Times/13. Timestamp Object Attributes.mp419.6 MB
10. Working with Dates and Times/14. The .truncate() Method.mp49 MB
10. Working with Dates and Times/15. pd.DateOffset Objects.mp425.6 MB
10. Working with Dates and Times/16. More Fun with pd.DateOffset Objects.mp431.9 MB
10. Working with Dates and Times/17. The pandas Timedelta Object.mp415.4 MB
10. Working with Dates and Times/18. Timedeltas in a Dataset.mp419.6 MB
10. Working with Dates and Times/2. Review of Python's datetime Module.mp416.7 MB
10. Working with Dates and Times/3. The pandas Timestamp Object.mp412.8 MB
10. Working with Dates and Times/4. The pandas DateTimeIndex Object.mp49.7 MB
10. Working with Dates and Times/5. The pd.to_datetime() Method.mp422.9 MB
10. Working with Dates and Times/6. Create Range of Dates with the pd.date_range() Method, Part 1.mp419.7 MB
10. Working with Dates and Times/7. Create Range of Dates with the pd.date_range() Method, Part 2.mp418.5 MB
10. Working with Dates and Times/8. Create Range of Dates with the pd.date_range() Method, Part 3.mp416.3 MB
10. Working with Dates and Times/9. The .dt Accessor.mp413.7 MB
11. Panels/1. Intro to the Module + Fetch Panel Dataset from Google Finance.mp413.7 MB
11. Panels/10. The .swapaxes() Method.mp49.7 MB
11. Panels/11. A Review of the Panels Module.html131 B
11. Panels/2. The Axes of a Panel Object.mp416.3 MB
11. Panels/3. Panel Attributes.mp410.5 MB
11. Panels/4. Use Bracket Notation to Extract a DataFrame from a Panel.mp48.3 MB
11. Panels/5. Extracting with the .loc, .iloc, and .ix Methods.mp413.5 MB
11. Panels/6. Convert Panel to a MultiIndex DataFrame (and Vice Versa).mp48.7 MB
11. Panels/7. The .major_xs() Method.mp412.1 MB
11. Panels/8. The .minor_xs() Method.mp413.6 MB
11. Panels/9. Transpose a Panel with the .transpose() Method.mp415.7 MB
12. Input and Output/1. Intro to the Input and Output Module.mp42.8 MB
12. Input and Output/2. Feed pd.read_csv() Method a URL Argument.mp47.6 MB
12. Input and Output/3. Quick Object Conversions.mp411.4 MB
12. Input and Output/4. Export DataFrame to CSV File with the .to_csv() Method.mp410.7 MB
12. Input and Output/5. Install xlrd and openpyxl Libraries to Read and Write Excel Files.mp46 MB
12. Input and Output/6. Import Excel File into pandas.mp419.1 MB
12. Input and Output/7. Export Excel File.mp417.8 MB
12. Input and Output/8. Input and Output.html131 B
13. Visualization/1. Intro to Visualization Module.mp47.3 MB
13. Visualization/2. The .plot() Method.mp419 MB
13. Visualization/3. Modifying Aesthetics with Templates.mp412.1 MB
13. Visualization/4. Bar Graphs.mp412.3 MB
13. Visualization/5. Pie Charts.mp49.9 MB
13. Visualization/6. Histograms.mp412.2 MB
13. Visualization/7. Visualization.html131 B
14. Options and Settings/1. Introduction to the Options and Settings Module.mp43.3 MB
14. Options and Settings/2. Changing pandas Options with Attributes and Dot Syntax.mp419.8 MB
14. Options and Settings/3. Changing pandas Options with Methods.mp413.9 MB
14. Options and Settings/4. The precision Option.mp46.1 MB
15. Conclusion/1. Conclusion.mp43 MB
2. Series/1. Create Jupyter Notebook for the Series Module.mp43.8 MB
2. Series/10. More Series Attributes.mp411.7 MB
2. Series/11. The .sort_values() Method.mp410.8 MB
2. Series/11.1 Official pandas Documentation.html145 B
2. Series/12. The inplace Parameter.mp49.4 MB
2. Series/13. The .sort_index() Method.mp48.6 MB
2. Series/13.1 Official pandas Documentation.html144 B
2. Series/14. Python's in Keyword.mp47.3 MB
2. Series/15. Extract Series Values by Index Position.mp48.9 MB
2. Series/16. Extract Series Values by Index Label.mp413.7 MB
2. Series/17. The .get() Method on a Series.mp49.6 MB
2. Series/18. Math Methods on Series Objects.mp410.2 MB
2. Series/19. The .idxmax() and .idxmin() Methods.mp45.8 MB
2. Series/2. Create A Series Object from a Python List.mp418.1 MB
2. Series/20. The .value_counts() Method.mp46.7 MB
2. Series/21. The .apply() Method.mp412.3 MB
2. Series/22. The .map() Method.mp413.1 MB
2. Series/23. A Review of the Series Module.html131 B
2. Series/3. Create A Series Object from a Python Dictionary.mp45.2 MB
2. Series/4. Intro to Attributes.mp412.9 MB
2. Series/5. Intro to Methods.mp47.9 MB
2. Series/6. Parameters and Arguments.mp418.3 MB
2. Series/7. Import Series with the .read_csv() Method.mp421.1 MB
2. Series/8. The .head() and .tail() Methods.mp46.5 MB
2. Series/8.1 Official pandas Documentation.html138 B
2. Series/9. Python Built-In Functions.mp49.9 MB
3. DataFrames I/1. Intro to DataFrames I Module.mp417.6 MB

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