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Stoneriverelearning – Data Analysis with Python and Pandas
Stoneriverelearning – Data Analysis with Python and Pandas

Stoneriverelearning – Data Analysis with Python and Pandas

Stoneriverelearning – Master Python Interactively With PyGame: Ultimate Bootcamp(Max) Stoneriverelearning – Master Python Interactively With PyGame: Ultimate Bootcamp(Max)
Stoneriverelearning – Python Programming for Beginners Stoneriverelearning – Python Programming for Beginners

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Stoneriverelearning – Data Analysis with Python and Pandas

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Description

Python programmers are some of the most sought-after employees in the tech world, and Python itself is fast becoming one of the most popular programming languages. One of the best applications of Python however is data analysis; which also happens to be something that employers can’t get enough of. Gaining skills in one or the other is a guaranteed way to boost your employability – but put the two together and you’ll be unstoppable!

Become and expert data analyser

  • Learn efficient python data analysis
  • Manipulate data sets quickly and easily
  • Master python data mining
  • Gain a skillset in Python that can be used for various other applications

Python data analytics made Simple

This course contains 51 lectures and 6 hours of content, specially created for those with an interest in data analysis, programming, or the Python programming language. Once you have Python installed and are familiar with the language, you’ll be all set to go.

The course begins with covering the fundamentals of Pandas (the library of data structures you’ll be using) before delving into the most important functions you’ll need for data analysis; creating and navigating data frames, indexing, visualising, and so on. Next, you’ll get into the more intricate operations run in conjunction with Pandas including data manipulation, logical categorising, statistical functions and applications, and more. Missing data, combining data, working with databases, and advanced operations like resampling, correlation, mapping and buffering will also be covered.

By the end of this course, you’ll have not only have grasped the fundamental concepts of data analysis, but through using Python to analyse and manipulate your data, you’ll have gained a highly specific and much in demand skill set that you can put to a variety of practical used for just about any business in the world.

Tools Used

Python: Python is a general purpose programming language with a focus on readability and concise code, making it a great language for new coders to learn. Learning Python gives a solid foundation for learning more advanced coding languages, and allows for a wide variety of applications.

Pandas: Pandas is a free, open source library that provides high-performance, easy to use data structures and data analysis tools for Python; specifically, numerical tables and time series. If your project involves lots of numerical data, Pandas is for you.

NumPy: Like Pandas, NumPy is another library of high level mathematical functions. The difference with NumPy however is that was specifically created as an extension to the Python programming language, intended to support large multi-dimensional arrays and matrices.

Course Curriculum

Introduction to the Course
  •  
    Start

    Course Introduction (4:11)

  •  
    Start

    Getting Pandas and Fundamentals (9:08)

  •  
    Start

    Section Conclusion (2:41)

Introduction to Pandas
  •  
    Start

    Section introduction (0:48)

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    Start

    Creating and Navigating a Dataframe (8:34)

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    Start

    Slices, head and tail (7:59)

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    Start

    Indexing (7:27)

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    Start

    Visualizing The Data (9:19)

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    Start

    Converting To Python List Or Pandas Series (4:15)

  •  
    Start

    Section Conclusion (1:38)

IO Tools
  •  
    Start

    Section introduction (2:12)

  •  
    Start

    Read Csv And To Csv (9:26)

  •  
    Start

    io operations (5:23)

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    Start

    Read_hdf and to_hdf (8:25)

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    Start

    Read Json And To Json (9:54)

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    Start

    Read Pickle And To Pickle (11:41)

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    Start

    Section Conclusion (3:52)

 

Pandas Operations
  •  
    Start

    Section introduction (2:04)

  •  
    Start

    Column Manipulation (Operatings on columns, creating new ones) (7:27)

  •  
    Start

    Column and Dataframe logical categorization (7:12)

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    Start

    Statistical Functions Against Data (7:34)

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    Start

    Moving and rolling statistics (10:00)

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    Start

    Rolling apply (8:54)

  •  
    Start

    Section Outro (3:17)

Handling for Missing Data / Outliers
  •  
    Start

    Section Intro (3:13)

  •  
    Start

    drop na (6:48)

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    Start

    Filling Forward And Backward Na (11:09)

  •  
    Start

    detecting outliers (12:38)

  •  
    Start

    Section Conclusion (5:17)

Combining Dataframes
  •  
    Start

    Section Introduction (3:53)

  •  
    Start

    Concatenation (9:17)

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    Start

    Appending data frames (7:06)

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    Start

    Merging dataframes (9:43)

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    Start

    Joining dataframes (9:40)

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    Start

    Section Conclusion (4:29)

Advanced Operations
  •  
    Start

    Section Introduction (2:48)

  •  
    Start

    Basic Sorting (8:56)

  •  
    Start

    Sorting by multiple rules (8:34)

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    Start

    Resampling basics time and how (mean, sum etc) (10:03)

  •  
    Start

    Resampling to ohlc (7:12)

  •  
    Start

    Correlation and Covariance Part 1 (10:03)

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    Start

    Correlation and Covariance Part 2 (11:56)

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    Start

    Mapping custom functions (9:23)

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    Start

    Graphing percent change of income groups (7:23)

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    Start

    Buffering basics (10:12)

  •  
    Start

    Buffering Into And Out Of Hdf5 (10:03)

  •  
    Start

    Section Conclusion (3:00)

Working with Databases
  •  
    Preview

    Section Introduction (1:00)

  •  
    Preview

    Writing to reading from database into a data frame (10:24)

  •  
    Preview

    Resampling data and preparing graph (7:54)

  •  
    Preview

    Finishing Manipulation And Graph (9:32)

  •  
    Preview

    Section and course Conclusion (5:27)

We guarantee that all our online courses will meet or exceed your expectations. If you are not 100% satisfied with a course – for any reason at all – simply request a full refund.
That’s our promise to you. We hate games, gimmicks and tricks as much as you do. We guarantee no hassles if you want a refund, so ahead and order with confidence. You have absolutely nothing to lose.

“I’m not far in with this yet but am learning much and enjoy the way i am learning.”

– Arahj Barapti

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