Data Analysis with Python and Pandas

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Learn the basics of Pandas, an industry-standard Python library that provides a collection of tools for data manipulation and analysis.

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Course Overview

Learn how to interpret data using Python. In this course you will learn the basics of Python along with various types of data. You will also learn how to prepare data for analysis, create meaningful data visualizations, perform simple statistical analyses, predict future trends from data, and many more.

Course Outline

Course Introduction
Getting Pandas and Fundamentals
Section Conclusion
Section introduction
Creating and Navigating a Dataframe
Slices, head and tail
Indexing
Visualizing The Data
Converting To Python List Or Pandas Series
Section Conclusion
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
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
Section Intro
drop na
Filling Forward And Backward Na
detecting outliers
Section Conclusion
Section Introduction
Concatenation
Appending data frames
Merging dataframes
Joining dataframes
Section Conclusion
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
Section Introduction
Writing to reading from database into a data frame
Resampling data and preparing graph
Finishing Manipulation And Graph
Section and course Conclusion

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