更新时间：2021-06-18 18:59:18
封面
版权信息
About Packt
Why subscribe?
Foreword
About the author
Preface
Section 1: Data Analysis Essentials
Fundamentals of Data Analysis
The evolution of data analysis and why it is important
What makes a good data analyst?
Understanding data types and their significance
Data classifications and data attributes explained
Understanding data literacy
Summary
Further reading
Overview of Python and Installing Jupyter Notebook
Technical requirements
Installing Python and using Jupyter Notebook
Storing and retrieving data files
Hello World! – running your first Python code
Exploring Python packages
Future reading
Getting Started with NumPy
Understanding a Python NumPy array and its importance
Making your first NumPy array
Practical use cases of NumPy and arrays
Creating Your First pandas DataFrame
Techniques for manipulating tabular data
Understanding pandas and DataFrames
Handling essential data formats
Data dictionaries and data types
Creating our first DataFrame
Gathering and Loading Data in Python
Introduction to SQL and relational databases
From SQL to pandas DataFrames
Data about your data explained
The importance of data lineage
Section 2: Solutions for Data Discovery
Visualizing and Working with Time Series Data
Data modeling for results
Anatomy of a chart and data viz best practices
Comparative analysis
The shape of the curve
Exploring Cleaning Refining and Blending Datasets
Retrieving viewing and storing tabular data
Learning how to restrict sort and sift through data
Cleaning refining and purifying data using Python
Combining and binning data
Understanding Joins Relationships and Aggregates
Foundations of join relationships
Join types in action
Explaining data aggregation
Summary statistics and outliers
Plotting Visualization and Storytelling
Explaining distribution analysis
Understanding outliers and trends
Geoanalytical techniques and tips
Finding patterns in data
Section 3: Working with Unstructured Big Data
Exploring Text Data and Unstructured Data
Preparing to work with unstructured data
Tokenization explained
Counting words and exploring results
Normalizing text techniques
Excluding words from analysis
Practical Sentiment Analysis
Why sentiment analysis is important
Elements of an NLP model
Sentiment analysis packages
Sentiment analysis in action
Bringing It All Together
