Python 大数据思维导图

Python for big data

1 Basic stack

1.1 numpy

1.2 scipy

1.3 pandas

1.3.1 "Python for Data Analysis" by Wes McKinney

1.4 scikits image

1.5 scikits learn

1.6 scikits statsmodels

1.7 nltk

1.8 matplotlib

2 Newer packages

2.1 Numba

2.2 wiseRF

2.3 Blaze

3 Integrated platforms

3.1 Continuum.io

3.1.1 Anaconda

3.1.2 Wakari

3.2 PiCloud

3.2.1 Python + AWS

3.3 wise.io

3.3.1 MLaaS

3.3.1.1 RandomForest

3.4 ipython

3.4.1 Notebook

3.5 Orange

4 Visualization

4.1 matplotlib

4.2 Bokeh

4.2.1 ggplot for python

4.3 Mayavi

4.4 Nodebox

4.5 igraph

4.6 pandas

4.6.1 pandas.tools.rplot

4.7 Google APIs

4.7.1 googleVis

5 Data formats

5.1 Flat text

5.1.1 xreadlines

5.1.2 readLines

5.1.3 pandas

5.1.3.1 read_csv

5.1.3.2 read_fwf

5.1.4 xlrd/xlwt/xlutils

5.2 HDF5

5.2.1 PyTables

5.2.2 h5py

5.3 SQL

5.3.1 SQLAlchemy

5.3.2 pysqlite3

5.3.3 pyodbc

5.3.3.1 Vertica

5.3.3.2 Netezza

5.3.3.3 Teradata

5.4 NoSQL

5.4.1 MongoDB

5.4.1.1 PyMongo

5.4.2 CouchDB

5.4.2.1 couchdb-python

5.4.2.2 couchdbkit

5.5 JSON

5.5.1 Standard library

5.5.1.1 json

5.5.2 simplejson

5.6 XML

5.6.1 Standard library

5.6.1.1 xml

5.7 HBase

5.7.1 HappyBase

6 MapReduce

6.1 Hadoop interface

6.1.1 Hadoop Streaming

6.1.1.1 Hadoopy

6.1.1.2 example

6.1.1.3 dumbo

6.1.1.4 mrjob Used and developed by Yelp

6.1.2 Pydoop

6.1.2.1 uses Hadoop Pipes

6.2 disco Used and developed by Nokia

7 Glue

7.1 rpy2

7.1.1 R

7.2 PySpark

7.2.1 Spark

7.3 ipython

7.3.1 magic

7.3.1.1 R

7.3.1.2 SQL

7.3.1.3 matlab/octave

7.3.1.4 IDL

7.4 Jython

7.4.1 Java

7.5 boto

7.5.1 Amazon Web Services

8 GPU

8.1 NumbaPro

8.2 PyCUDA

9 Parallel

9.1 ipython

9.1.1 ipcluster

9.2 pp

9.3 dispy

10 Efficiency

10.1 Cython

11 Packages

11.1 PyPI

11.1.1 30686 packages

VIA: Python for big data
 转自： http://www.linuxeye.com/news/1756.html