Forecastability Analysis
This is a tool to implement forecastability analysis, including calculating:
- Frequency
- Stability
- Periodicity
- Percent of Products that single customer occupies over 50% demands
Input Data
| columname | type | note |
|---|---|---|
| date | string | yyyy-mm-dd or yyyy/mm/dd |
| sku_code | string | code of SKU |
| customer_code | string | code of customer |
| qty | float | demand quantity |
Usage:
import forecastability
fa = forecastability.Forecastability(data, tm="date")
# calculate frequency
fa.frequency()
# calculate stability
fa.stability()
# calculate periodicity
fa.periodicity()
# calculate single customer percent
fa.single_customer_percent()
# render forecastability report
fa.render("forecastability_report.html")
Reference:
[1] 时间周期序列周期性挖掘
[3] Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: principles and practice. OTexts.
Metadata
Release files for forecastability 0.0.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| forecastability-0.0.6.tar.gz | 7.3 kB | Details |
Release files / forecastability-0.0.6.tar.gz
| Download URL | forecastability-0.0.6.tar.gz |
|---|---|
| Size | 7.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
d47cf75ab1cb0cfd86d450ca763ce2b8f449ff5ef9e7e4f8badbd7a1ae36bb82
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| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/49.1.0 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.6.6
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