Using bandicoot

bandicoot indicators are divided in four modules (individual, spatial, network, and recharge).

They can also be computed at once using bandicoot.utils.all(). network indicators will only be returned if the user was loaded in read_csv() using the option network=True.

Summary

As described in Quick start, bandicoot returns by default the mean and std or the value of indicators.

When the indicator is a timeseries, for example in the case of call_duration(), bandicoot can also return the median, min, max, kurtosis, and skewness using summary=extended or the full timeserie using summary=None. Note that, by default, bandicoot returns a list of lists with one list for every week.

>>> bc.individual.call_duration(B, summary='extended')
{
    "allweek": {
        "allday": {
            "call": {
                "mean": {
                    "mean": 487.37072353402834,
                    "std": 45.45198877486552
                },
                "std": {
                    "mean": 290.83801983951815,
                    "std": 16.80049312510362
                },
                "median": {
                    "mean": 496.65,
                    "std": 89.55251252756675
                },
                "skewness": {
                    "mean": -0.020629629074944145,
                    "std": 0.316056976875559
                },
                "kurtosis": {
                    "mean": 1.831122766069137,
                    "std": 0.2258792542370957
                },
                "min": {
                    "mean": 17.3,
                    "std": 23.48212085821892
                },
                "max": {
                    "mean": 974.6,
                    "std": 18.369540005128055
                }
            }
        }
    }
}
>>> bc.individual.call_duration(B, summary=None)
{
    "allweek": {
        "allday": {
            "call": [
                [ 84, 209, 279, 279, 416, 441, 800, 860, 940], ... [ 8, 57, 127, 317, 536, 601, 619, 702, 769, 791, 792, 858, 867, 886, 932, 947]
            ]
        }
    }
}
>>> bc.individual.call_duration(B, summary=None, groupby=None)
{
    "allweek": {
        "allday": {
            "call": [ 84, 209, 279, 279, 416, 441, 800, 860, 940, ..., 8, 57, 127, 317, 536, 601, 619, 702, 769, 791, 792, 858, 867, 886, 932, 947]
        }
    }
}
summary single value timeserie
default value mean, std
extended value mean, std, median, min, max, kurtosis, skewness
None value the full distribution

Interaction type

Calls and texts

The individual and network indicators can be computed on records of type call, text, or callandtext (which includes both calls and texts).

For example, active_days() returns, by default, the number of days a user has been active overall:

>>> bc.individual.active_days(B)
{
     "allweek": {
         "allday": {
             "callandtext": {
                 "mean": 5.4,
                 "std": 2.33238075793812
             }
         }
     }
 }

This behavior can be changed using the interaction keyword which takes a list:

>>> bc.individual.active_days(B, interaction=['callandtext','call','text'])
{
     "allweek": {
         "allday": {
             "callandtext": {
                 "mean": 5.4,
                 "std": 2.33238075793812
             },
             "call": {
                 "mean": 5.4,
                 "std": 2.33238075793812
             },
             "text": {
                 "mean": 5.4,
                 "std": 2.33238075793812
             }
         }
     }
 }

If an interaction type is specified and there are no records of that type, bandicoot will return None for that indicator:

>>> B.has_text
False
>>> bc.individual.number_of_contacts(B, interaction=['call','text'])
{
    "allweek": {
        "allday": {
            "call": {
                "mean": 31.9,
                "std": 10.681292056675542
            },
            "text": {
                "mean": None,
                "std": None
            }
        }
    }
}

GPS locations

bandicoot also supports fine-grained mobility traces, with records of interaction type gps. GPS records are used only for spatial indicators. We provide tools to:

  1. automatically cluster GPS records around stops locations,
  2. map the antenna of call and text records to the new stop locations.

See cluster_and_update() and fix_location() for more information.

Splits (days and hours)

  • split_week=True causes records from weekdays and weekends to be considered separately and reported along with the allweek values.
  • split_day=True causes records from daytime and nightime to be considered separately and reported along with the allday values.

(By default, "night" is defined as 7 p.m. to 7 a.m.)

>>> bc.individual.active_days(B, split_week=True)
{
    "allweek": {
        "allday": {
            "callandtext": {
                "mean": 5.4,
                "std": 2.33238075793812
            }
        }
    },
    "weekday": {
        "allday": {
            "callandtext": {
                "mean": 4.333333333333333,
                "std": 1.3333333333333333
            }
        }
    },
    "weekend": {
        "allday": {
            "callandtext": {
                "mean": 1.875,
                "std": 0.33071891388307384
            }
        }
    }
}

This output implies that the user B is active approximately 1.875 days (out of 2) each weekend while 5.4 days (out of 7) for the all week.