Meggie  Flatley

Meggie Flatley


NumPy And Pandas Interface To Big Data

Blaze translates a subset of modified NumPy and Pandas-like syntax to databases and other computing systems. Blaze allows Python users a familiar interface to query data living in other data storage systems.


We point blaze to a simple dataset in a foreign database (PostgreSQL). Instantly we see results as we would see them in a Pandas DataFrame.

>>> import blaze as bz
>>> iris = bz.Data('postgresql://localhost::iris')
>>> iris
    sepal_length  sepal_width  petal_length  petal_width      species
0            5.1          3.5           1.4          0.2  Iris-setosa
1            4.9          3.0           1.4          0.2  Iris-setosa
2            4.7          3.2           1.3          0.2  Iris-setosa
3            4.6          3.1           1.5          0.2  Iris-setosa

These results occur immediately. Blaze does not pull data out of Postgres, instead it translates your Python commands into SQL (or others.)

>>> iris.species.distinct()
0      Iris-setosa
1  Iris-versicolor
2   Iris-virginica

>>>, smallest=iris.petal_length.min(),
...                      largest=iris.petal_length.max())
           species  largest  smallest
0      Iris-setosa      1.9       1.0
1  Iris-versicolor      5.1       3.0
2   Iris-virginica      6.9       4.5

This same example would have worked with a wide range of databases, on-disk text or binary files, or remote data.

What Blaze is not

Blaze does not perform computation. It relies on other systems like SQL, Spark, or Pandas to do the actual number crunching. It is not a replacement for any of these systems.

Blaze does not implement the entire NumPy/Pandas API, nor does it interact with libraries intended to work with NumPy/Pandas. This is the cost of using more and larger data systems.

Blaze is a good way to inspect data living in a large database, perform a small but powerful set of operations to query that data, and then transform your results into a format suitable for your favorite Python tools.

In the Abstract

Blaze separates the computations that we want to perform:

>>> accounts = Symbol('accounts', 'var * {id: int, name: string, amount: int}')

>>> deadbeats = accounts[accounts.amount < 0].name

From the representation of data

>>> L = [[1, 'Alice',   100],
...      [2, 'Bob',    -200],
...      [3, 'Charlie', 300],
...      [4, 'Denis',   400],
...      [5, 'Edith',  -500]]

Blaze enables users to solve data-oriented problems

>>> list(compute(deadbeats, L))
['Bob', 'Edith']

But the separation of expression from data allows us to switch between different backends.

Here we solve the same problem using Pandas instead of Pure Python.

>>> df = DataFrame(L, columns=['id', 'name', 'amount'])

>>> compute(deadbeats, df)
1      Bob
4    Edith
Name: name, dtype: object

Blaze doesn't compute these results, Blaze intelligently drives other projects to compute them instead. These projects range from simple Pure Python iterators to powerful distributed Spark clusters. Blaze is built to be extended to new systems as they evolve.

Getting Started

Blaze is available on conda or on PyPI

conda install blaze
pip install blaze

Development builds are accessible

conda install blaze -c blaze
pip install --upgrade

You may want to view the docs, the tutorial, some blogposts, or the mailing list archives.

Development setup

The quickest way to install all Blaze dependencies with conda is as follows

conda install blaze spark -c blaze -c anaconda-cluster -y
conda remove odo blaze blaze-core datashape -y

After running these commands, clone odo, blaze, and datashape from GitHub directly. These three projects release together. Run python develop to make development installations of each.


Released under BSD license. See LICENSE.txt for details.

Blaze development is sponsored by Continuum Analytics.

Author: blaze
Source Code:
License: View license

#pandas #numpy 

What is GEEK

Buddha Community

NumPy And Pandas Interface To Big Data
 iOS App Dev

iOS App Dev


Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Big Data Consulting Services | Big Data Development Experts USA

Big Data Consulting Services

Traditional data processing application has limitations of its own in terms of processing the large chunk of complex data and this is where the big data processing application comes into play. Big data processing app can easily process complex and large information with their advanced capabilities.

Want to develop a Big Data Processing Application?

WebClues Infotech with its years of experience and serving 350+ clients since our inception is the agency to trust for the Big Data Processing Application development services. With a team that is skilled in the latest technologies, there can be no one better for fulfilling your development requirements.

Want to know more about our Big Data Processing App development services?


Share your requirements

View Portfolio

#big data consulting services #big data development experts usa #big data analytics services #big data services #best big data analytics solution provider #big data services and consulting

Silly mistakes that can cost ‘Big’ in Big Data Analytics

Big Data has played a major role in defining the expansion of businesses of all kinds as it helps the companies to understand their audience and devise their business techniques in accordance with the requirement.

The importance of ‘Data’ has been spoken very highly in the modern-day business. Thus, while using big data analysis, the companies must keep away from these minor mistakes otherwise it could have a major impact on their performances. Big Data analysis can be the silver bullet that can answer your questions and help your business to scale newer heights.

Read More: Silly mistakes that can cost ‘Big’ in Big Data Analytics

#top big data analytics companies #best big data service providers #big data for business #big data technology #big data mistakes #big data analytics

Big Data can be The ‘Big’ boon for The Modern Age Businesses

The rapid growth of technology has led to many people opting for online services, and thus the collection and maintenance of data becomes a significant factor for any company. Big data analytics service providers can help the companies get a massive edge over their competitors as they would manage the data well and allow the businesses to make better business decisions. It will provide you with a combination of increased customer experience, revenue, and reduced cost and thus will create a win-win situation for your business. Big data technologies will be your perfect ally in excelling in the cut-throat business environment and come out with flying colors.

Read More: Big Data can be The ‘Big’ boon for The Modern Age Businesses

#big data analytics service providers #top big data analytics companies #impact of big data on businesses #best big data consulting firms #big data #big data for businesses

Top Microsoft big data solutions Companies | Best Microsoft big data Developers

An extensively researched list of top Microsoft big data analytics and solution with ratings & reviews to help find the best Microsoft big data solutions development companies around the world.
An exclusive list of Microsoft Big Data consulting and solution providers, after examining various factors of expert big data analytics firms and found the equivalent matches that boast the ace qualities with proven fineness in data analytics. For business growth and enterprise acceleration getting inputs from the whole data of the organization have become necessary, thus we bring to you the most trustworthy Microsoft Big Data consultants and solutions providers for your assistance.
Let’s take a look at the List of Best Microsoft big data solutions Companies.

#microsoft big data solutions development companies #microsoft big data analytics and solution #microsoft big data consultants #microsoft big data developers #microsoft big data #microsoft big data solution providers