Loading the toolbox

The Pici class from the pici package gives access to all functionality related to loading and analyzing peer innovation communities.

In [ ]:

Copied!

from pici import Pici
from pici import Pici

Instantiating the Pici class will set up all communities currently available in the library.

When defining a cache_dir directory, pici will try to load all data from files instead of collecting new data from the web.
You can limit the loaded data by setting the start and/or end parameters, passing, for example '2017' or '2017-01' or '2017-01-25' etc.
When using the cache, you can further limit loaded data with the cache_nrows parameter. For example, setting cache_nrwos=500 would only load the first 500 rows of the cache.

In [3]:

Copied!





p = Pici(
    cache_dir='../../cache',
    cache_nrows=1000,
    # start='2017-01-01',
    # end='2019-01-01',
)
p = Pici(
    cache_dir='../../cache',
    cache_nrows=1000,
    # start='2017-01-01',
    # end='2019-01-01',
)

This has loaded three communities:

In [4]:

Copied!

p.communities
p.communities

Out[4]:

{'OpenEnergyMonitor': <pici.communities.discourse.DiscourseCommunity at 0x2a7ab126d60>,
 'OpenStreetMap': <pici.communities.osm.OSMCommunity at 0x2a7c2999c10>,
 'PreciousPlastic': <pici.communities.preciousplastic.PPCommunity at 0x2a7c2999400>}

You can now access the communities individually:

In [5]:

Copied!

osm = p.communities['OpenStreetMap']
osm = p.communities['OpenStreetMap']

In [6]:

Copied!

contributors_per_month = osm.metrics.contributors_per_interval(interval='1M').data
contributors_per_month = osm.metrics.contributors_per_interval(interval='1M').data

In [7]:

Copied!

contributors_per_month.plot()
contributors_per_month.plot()

Out[7]:

<AxesSubplot:xlabel='date'>

Or generate reports for all communities collectively:

In [8]:

Copied!

summary = p.reports.summary()
summary = p.reports.summary()

In [9]:

Copied!

summary.results.T
summary.results.T

Out[9]:

community_name	OpenEnergyMonitor	OpenStreetMap	PreciousPlastic
sum posts per topic	1000.000000	1000.000000	1000.000000
min posts per topic	14.000000	1.000000	1.000000
mean posts per topic	58.823529	3.690037	10.869565
number of posts	1000.000000	1000.000000	1000.000000
var number of posts per 1M	432.467030	71.450564	186.734177
std number of posts per 1d	1.936793	0.773700	1.321718
var number of posts per 1d	3.751166	0.598612	1.746939
sum number of posts per 1d	1000.000000	1000.000000	1000.000000
sum number of posts per 1M	1000.000000	1000.000000	1000.000000
min number of posts per 1M	0.000000	0.000000	0.000000
mean number of posts per 1M	17.241379	5.813953	12.500000
std posts per topic	45.913281	2.613330	20.679244
max number of posts per 1M	102.000000	38.000000	76.000000
max posts per topic	176.000000	21.000000	122.000000
min number of posts per 1d	0.000000	0.000000	0.000000
var posts per topic	2108.029412	6.829493	427.631151
mean number of posts per 1d	0.582751	0.192604	0.416840
max number of posts per 1d	43.000000	12.000000	19.000000
std number of posts per 1M	20.795842	8.452844	13.665071