Practical Data Analysis Using Jupyter Notebook
更新时间：2021-06-18 18:59:18
最新章节：Leave a review - let other readers know what you think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
Summary
Future reading
Getting Started with NumPy
Technical requirements
Understanding a Python NumPy array and its importance
Making your first NumPy array
Practical use cases of NumPy and arrays
Summary
Further reading
Creating Your First pandas DataFrame
Technical requirements
Techniques for manipulating tabular data
Understanding pandas and DataFrames
Handling essential data formats
Data dictionaries and data types
Creating our first DataFrame
Summary
Further reading
Gathering and Loading Data in Python
Technical requirements
Introduction to SQL and relational databases
From SQL to pandas DataFrames
Data about your data explained
The importance of data lineage
Summary
Further reading
Section 2: Solutions for Data Discovery
Visualizing and Working with Time Series Data
Technical requirements
Data modeling for results
Anatomy of a chart and data viz best practices
Comparative analysis
The shape of the curve
Summary
Further reading
Exploring Cleaning Refining and Blending Datasets
Technical requirements
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
Summary
Further reading
Understanding Joins Relationships and Aggregates
Technical requirements
Foundations of join relationships
Join types in action
Explaining data aggregation
Summary statistics and outliers
Summary
Further reading
Plotting Visualization and Storytelling
Technical requirements
Explaining distribution analysis
Understanding outliers and trends
Geoanalytical techniques and tips
Finding patterns in data
Summary
Further reading
Section 3: Working with Unstructured Big Data
Exploring Text Data and Unstructured Data
Technical requirements
Preparing to work with unstructured data
Tokenization explained
Counting words and exploring results
Normalizing text techniques
Excluding words from analysis
Summary
Further reading
Practical Sentiment Analysis
Technical requirements
Why sentiment analysis is important
Elements of an NLP model
Sentiment analysis packages
Sentiment analysis in action
Summary
Further reading
Bringing It All Together
Technical requirements
Discovering real-world datasets
Reporting results
The Capstone project
Summary
Further reading
Works Cited
Other Books You May Enjoy
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更新时间：2021-06-18 18:59:18