Overview
Data Analysis has been around for a long time. But up until a few years ago, developers practiced it using expensive, closed-source tools like Tableau. But recently, Python, SQL, and other open libraries have changed Data Analysis forever.
In the Data Analysis with Python, you'll learn the fundamentals of data analysis with Python. By the end of this certification, you'll know how to read data from sources like CSVs and SQL, and how to use libraries like Numpy, Pandas, Matplotlib, and Seaborn to process and visualize data.
Course Content
- Why Python for Data Analysis?
- Essential Python Libraries
- Installation and Setup
- IPython Basics
- IPython HTML Notebook
- Tips for Productive Code Development Using IPython
- The NumPy ndarray: A Multidimensional Array Object
- Universal Functions: Fast Element-wise Array Functions
- Data Processing Using Arrays
- File Input and Output with Arrays
- Linear Algebra
- Random Number Generation
- Introduction to pandas Data Structures
- Essential Functionality
- Summarizing and Computing Descriptive Statistics
- Handling Missing Data
- Hierarchical Indexing
- Other pandas Topics
- Reading Text Files in Pieces
- Writing Data Out to Text Format
- Manually Working with Delimited Formats
- JSON Data
- XML and HTML: Web Scraping
- Binary Data Formats
- Interacting with HTML and Web APIs
- Interacting with Databases
- Combining and Merging Data Sets
- Reshaping and Pivoting
- Data Transformation
- String Manipulation
- A Brief matplotlib API Primer
- - Figures and Subplots
- - Colors, Markers, and Line Styles
- - Ticks, Labels, and Legends
- Plotting Functions in pandas
- - Line Plots
- - Bar Plots
- - Histograms and Density Plots
- - Scatter Plots
- Plotting Maps: Visualizing Haiti Earthquake Crisis Data
- Python Visualization Tool Ecosystem
- The Future of Visualization Tools?
- GroupBy Mechanics
- Data Aggregation
- Group-wise Operations and Transformations
- Pivot Tables and Cross-Tabulation
- Mean, Median & Mode
- Descriptive and Frequency distribution
- Skewness & Kurtosis
- Correlation
- Regression
- Chi square test
- One sample t test
- Paired sample t test
- Independent sample t test
- One way ANOVA
- Date and Time Data Types and Tools
- Time Series Basics
- Date Ranges, Frequencies, and Shifting
- Time Zone Handling
- Periods and Period Arithmetic
- Resampling and Frequency Conversion
- Time Series Plotting
- Moving Window Functions
- Performance and Memory Usage Notes
- ndarray Object Internals
- Advanced Array Manipulation
- Broadcasting
- Advanced ufunc Usage
- Structured and Record Arrays
- More About Sorting
- NumPy Matrix Class
- Advanced Array Input and Output
- Performance Tips
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