更新时间：2021-07-09 19:04:29
封面
版权信息
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Chapter 1. Getting Started with Python Libraries
Installing Python 3
Using IPython as a shell
Reading manual pages
Jupyter Notebook
NumPy arrays
A simple application
Where to find help and references
Listing modules inside the Python libraries
Visualizing data using Matplotlib
Summary
Chapter 2. NumPy Arrays
The NumPy array object
Creating a multidimensional array
Selecting NumPy array elements
NumPy numerical types
One-dimensional slicing and indexing
Manipulating array shapes
Creating array views and copies
Fancy indexing
Indexing with a list of locations
Indexing NumPy arrays with Booleans
Broadcasting NumPy arrays
References
Chapter 3. The Pandas Primer
Installing and exploring Pandas
The Pandas DataFrames
The Pandas Series
Querying data in Pandas
Statistics with Pandas DataFrames
Data aggregation with Pandas DataFrames
Concatenating and appending DataFrames
Joining DataFrames
Handling missing values
Dealing with dates
Pivot tables
Chapter 4. Statistics and Linear Algebra
Basic descriptive statistics with NumPy
Linear algebra with NumPy
Finding eigenvalues and eigenvectors with NumPy
NumPy random numbers
Creating a NumPy masked array
Chapter 5. Retrieving Processing and Storing Data
Writing CSV files with NumPy and Pandas
The binary .npy and pickle formats
Storing data with PyTables
Reading and writing Pandas DataFrames to HDF5 stores
Reading and writing to Excel with Pandas
Using REST web services and JSON
Reading and writing JSON with Pandas
Parsing RSS and Atom feeds
Parsing HTML with Beautiful Soup
Reference
Chapter 6. Data Visualization
The matplotlib subpackages
Basic matplotlib plots
Logarithmic plots
Scatter plots
Legends and annotations
Three-dimensional plots
Plotting in Pandas
Lag plots
Autocorrelation plots
Plot.ly
Chapter 7. Signal Processing and Time Series
The statsmodels modules
Moving averages
Window functions
Defining cointegration
Autocorrelation
Autoregressive models
ARMA models
Generating periodic signals
Fourier analysis
Spectral analysis
Filtering
Chapter 8. Working with Databases
Lightweight access with sqlite3
Accessing databases from Pandas
SQLAlchemy
Pony ORM
Dataset - databases for lazy people
PyMongo and MongoDB
Storing data in Redis
Storing data in memcache
