Skip to main content

A dependency-free library to quickly make ascii histograms from data.

Project description

text_histogram

PyPI version Number of PyPI downloads

Histograms are great for exploring data, but numpy and matplotlib are heavy and overkill for quick analysis. They also can’t be easily used on remote servers over ssh. Don’t even get me started on installing them.

Bit.ly’s data_hacks histogram.py is great but difficult to use from python code directly (it requires an optparse.OptionParser to pass histogram options). This is histogram.py repackaged for convenient script use.

>>> from text_histogram import histogram
>>> import random
>>> histogram([random.gauss(50, 20) for _ in xrange(100)])
# NumSamples = 100; Min = 1.42; Max = 87.36
# Mean = 51.848095; Variance = 332.055832; SD = 18.222399; Median 53.239251
# each ∎ represents a count of 1
    1.4221 -    10.0159 [     3]: ∎∎∎
   10.0159 -    18.6098 [     3]: ∎∎∎
   18.6098 -    27.2036 [     6]: ∎∎∎∎∎∎
   27.2036 -    35.7974 [     4]: ∎∎∎∎
   35.7974 -    44.3913 [    17]: ∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎
   44.3913 -    52.9851 [    16]: ∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎
   52.9851 -    61.5789 [    17]: ∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎
   61.5789 -    70.1728 [    20]: ∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎∎
   70.1728 -    78.7666 [     8]: ∎∎∎∎∎∎∎∎
   78.7666 -    87.3604 [     6]: ∎∎∎∎∎∎

Installation

$ pip install text_histogram

Source: https://github.com/Kobold/text_histogram

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

text_histogram-0.0.7.tar.gz (4.4 kB view hashes)

Uploaded Source

Built Distribution

text_histogram-0.0.7-py2-none-any.whl (6.4 kB view hashes)

Uploaded Python 2

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page