Data Analysis with Python & Pandas Online Course
Data Analysis with Python and Pandas Online Courses in Zimbabwe
2KO offers an online computer course called Data Analysis with Python and Pandas. 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. 2KO Africa offers IT consulting, technical IT services and top-of-the-range IT training on multiple platforms. Our best-of-breed computer courses are presented as instructor led classes or as online internet-based elearning. 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.
Curriculum
Introduction to the Course
Course Introduction
Getting pandas and fundamentals
Introduction to Pandas
Section introduction
Creating and Navigating a Dataframe
Slices, head and tail
Indexing
Visualizing The Data
Converting To Python List Or Pandas Series
Section Conclusion
IO Tools
Section introduction
Read Csv And To Csv
io operations
Read_hdf and to_hdf
Read Json And To Json
Read Pickle And To Pickle
Section Conclusion
Pandas Operations
Section introduction
Column Manipulation (Operatings on columns, creating new ones)
Column and Dataframe logical categorization
Statistical Functions Against Data
Moving and rolling statistics
Rolling apply
Section Outro
Handling for Missing Data / Outliers
Section Intro
drop na
Filling Forward And Backward Na
detecting outliers
Section Conclusion
Combining Dataframes
Section Introduction
Concatenation
Appending data frames
Merging dataframes
Joining dataframes
Section Conclusion
Advanced Operations
Section Introduction
Basic Sorting
Sorting by multiple rules
Resampling basics time and how (mean, sum etc)
Resampling to ohlc
Correlation and Covariance Part 1
Correlation and Covariance Part 2
Mapping custom functions
Graphing percent change of income groups
Buffering basics
Buffering Into And Out Of Hdf5
Section Conclusion
Working with Databases
Section Introduction
Writing to reading from database into a data frame
Resampling data and preparing graph
Finishing Manipulation And Graph
Section and course Conclusion
Certificate Exam Access