`vp.features.velocity`

Trailing-window counts, sum and distinct count (catalog/velocity.viv).

Part of the distribution vipyr; it runs from a checkout of the repository. Planned on PyPI as pip install vipyr.

Signature

vp.features.velocity(df=None, n=500)

Parameters

df : pandas.DataFrame, default None: The event table, rows in any order; None makes a synthetic one of n rows.
n : int, default 500: Rows of the synthetic table when df is None. Range: >= 1.

Returns

A frozen VelocityResult. Iterating it gives the fields below in order; it also has params, tests, log and check().

frame : pandas.DataFrame: The features, one row per input row, in the input's order and index: sum_24h, distinct_24h.

column of frame	definition
`sum_24h`	`amount` summed over the 24-hour window, left to right in canonical order
`distinct_24h`	distinct merchants in the 24-hour window

Raises

TypeError: An argument of the wrong type, or an unknown keyword.
vipyr.VivBuildError: An ImportError: no C compiler, or the program's C does not build.

Examples

import vipyr as vp
r = vp.features.velocity()                  # a synthetic table; pass df= for yours
print(r.frame.head())
assert r.check()

   n_1h  n_24h  sum_24h  distinct_24h
0     0      0     0.00             0
1     0      1    99.35             1
2     0      1     5.70             1
3     0      2    42.11             2
4     0      0     0.00             0

Each example ran as written when these pages were generated, and the output shown is what it printed.

Checked against

Reference: catalog.velocity_reference: a pandas groupby().apply() with a Python loop per row, equal bit for bit; vipyr.check_point_in_time: no feature reads a row after its own time

Source

Viv: catalog/velocity.viv
Viv: catalog/catalog.py
The defs it reaches and the calls between them: map of the code