A number of scripts describing use of various data analysis tools in python and their implementation on different case scenarios
The sequence for following the scripts instruction wise is as follows:
- Getting started with ndarrays
- Handling DataTypes for ndarrays
- Basic Operations on Arrays
- Universal Functions
- Simple example using Numpy vectorization
- numpy.where
- Basic Array Statistical Methods
- Methods for Boolean Arrays
- Numpy Sorting
- Set Logic Methods
- File Operations with Numpy Arrays
- Operations of Linear Algebra
- Numpy Random Number Generation
- Implementation Random Walks (Case Scenario Implementation)
- Getting Started with Pandas Series
- Getting Started with Pandas DataFrames
- Handling Pandas Index Objects
- Index Object Methods
- Reindexing
- Dropping Entries from Axis
- Indexing, Selecting and Filtering Operations
- Arithmetic and Data Alignment
- Apply Methods for DataFrames
- Sorting and Ranking
- Axis Indexes with Duplicate Values
- Computing Descriptive Statistics
- Unique Values, Value Counts and Membership
- Handling Missing Data Operations
- Hierarchical Indexing
- Reordering and Sorting Levels
- Applying Summary Statistics to Levels
- Using DataFrame Columns as a Hierarchical Form
- Reading Data from CSV Files
- Reading CSV Files in Pieces
- Writing Data to CSV Files
- Using the CSV Module
- Using JSON Module