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Copyright (c) 2019 The Python Packaging Authority

The package is used for risk control modeling in Python. It mainly provides some basic and commonly data analysis methods for partners who want to learn Python data analysis or machine learning in the Internet financial industry. It also contains a large number of solutions to the problems encountered by the authors in their daily work. I hope you can actively use it. If you have any questions, please contact me at hsliu_em@126.com.

riskcontrol

riskcontrol

Riskcontrol is used for risk control modeling in Python.

It provides intuitive tools for

  • feature information-value (iv)
  • plot bad rate of bins based on decision tree
  • ks plot
  • feature info describe for external data validation(contain missing analysis)
  • two feature heat map for cross analysis
  • logistic credit card
  • gps near geohash coding

install

pip install riskcontrol

Usage

import riskcontrol as rc
import pandas as pd

data = pd.read_csv('test.csv')
rc.feature_miss_ana(data) # data analysis report
col col_type iv all_n all_bad_rate miss_pect miss_bad_rate notnull_bad_rate zero_pect zero_bad_rate mode_v mode_pect mode_bad_rate risk_monotonicity
ios float64 0.0273 10000 0.027867225 0 0.0278 0.528996 0.054911 0 0.528996 0.054911
sex_m float64 0.0486 10000 0.027867225 0 0.0278 0.276689 0.032552 1 0.723311 0.053726
d.age float64 0.0408 10000 0.027867225 0 0.0278 0 22 0.095423 0.053391
d.income float64 0.0302 10000 0.027867225 0 0.0278 0 100000 0.147488 0.041681
edu float64 0.0367 10000 0.027867225 0 0.0278 0.828286 0.051514 0 0.828286 0.051514
d.freeram float64 0.0087 10000 0.027867225 0 0.0278 0 482864 0.000104 0.125
joblevel float64 0.0411 10000 0.027867225 0 0.0278 0.084128 0.03028 4 0.383198 0.056743
rc.split_box_plot_new(data, col_name) # bins bad rate plot

aaa

rc.create_geohash(latitude, longitude, radius, precision)

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