依据报错在原代吗格式的基础上解决问题（anaconda）(数据分析)
代码：
import pandas as pd
import numpy as np
from sklearn.preprocessing import StandardScaler
carddata = pd.read_csv('E:/数据分析/credit_card.csv', engine='python')
# 筛选逾期但是不是瑕疵户的数据
exp1 = (carddata['逾期'] == 1) & (carddata['瑕疵户'] == 2)
# 筛选呆账但是不是瑕疵户的数据
exp2 = (carddata['呆账'] == 1) & (carddata['瑕疵户'] == 2)
# 筛选有强制停卡记录但是不是瑕疵户的数据
exp3 = (carddata['强制停卡记录'] == 1) & (carddata['瑕疵户'] == 2)
# 筛选退票但是不是瑕疵户的数据
exp4 = (carddata['退票'] == 1) & (carddata['瑕疵户'] == 2)
# 筛选有拒收记录但是不是瑕疵户的数据
exp5 = (carddata['拒往记录'] == 1) & (carddata['瑕疵户'] == 2)
# 筛选有呆账但是没有拒收记录的数据
exp6 = (carddata['呆账'] == 1) & (carddata['拒往记录'] == 2)
# 筛选有强制停卡记录但是没有拒收记录的数据
exp7 = (carddata['强制停卡记录'] == 1) & (carddata['拒往记录'] == 2)
# 筛选退票但是没有拒收记录的数据
exp8 = (carddata['退票'] == 1) & (carddata['拒往记录'] == 2)
# 筛选频率为5但是月刷卡额大于1的数据
exp9 = (carddata['频率'] == 5) & (carddata['月刷卡额'] > 1)
# 筛选异常数据
Final = carddata.loc[(exp1 | exp2 | exp3 | exp4 | exp5 | exp6 | exp7 | exp8 | exp9).apply(lambda x:not(x)), :]
Final.reset_index(inplace = True)
# 个人月收入（万元）
PersonalMonthIncome = [0, 1, 2, 3, 4, 5, 6, 7, 8]
for i in range(8):
Final.loc[Final['个人月收入'] == i + 1, '个人月收入'] = PersonalMonthIncome[i]
# 根据5 、6的情况计算个人月收入和家庭月收入的比值，确定家庭月收入为未知的情况
FamilyMonthIncome = [2, 4, 6, 8, 10, 12]
m = (Final.loc[: , '家庭月收入'] == 5)
Final.loc[m, '家庭月收入'] = FamilyMonthIncome[4]
ratio5 = Final.loc[m, '个人月收入'] / Final.loc[m, '家庭月收入']
m1 = Final.loc[: , '家庭月收入'] == 6
Final.loc[m1, '家庭月收入'] = FamilyMonthIncome[5]
ratio6 = Final.loc[m1, '个人月收入'] / Final.loc[m1, '家庭月收入']
# 家庭月收入（万元）
FamilyMonthIncome = [2, 4, 6, 8, 10, 15]
Final.loc[Final['家庭月收入'] == 0, '家庭月收入'] = 6
for i in range(6):
m2 = Final.loc[: , '家庭月收入'] == i + 1
Final.loc[m2, '家庭月收入'] = FamilyMonthIncome[i]
# 月刷卡额（万元）
MonthCardPay = [2, 4, 6, 8, 10, 15, 20, 25]
for i in range(8):
m = Final.loc[: , '月刷卡额'] == i + 1
Final.loc[m, '月刷卡额'] = MonthCardPay[i]
# 个人月开销（万元）
PersonalMonthOutcome = [1, 2, 3, 4, 6]
for i in range(5):
m = Final['个人月开销'] == i + 1
Final.loc[m, '个人月开销'] = PersonalMonthOutcome[i]
# 属性值为1（是）的记为1分，属性值为2（否）的记为0分
def GetScore(x):
if x == 2 :
a = 0
else:
a = 1
return(a)
BuguserSocre = Final['瑕疵户'].apply(GetScore)
OverdueScore = Final['逾期'].apply(GetScore)
BaddebtScore = Final['呆账'].apply(GetScore)
CardstopedScore = Final['强制停卡记录'].apply(GetScore)
BounceScore = Final['退票'].apply(GetScore)
RefuseScore = Final['拒往记录'].apply(GetScore)
Final['历史信用风险'] = (BuguserSocre + OverdueScore * 2 + BaddebtScore * 3
+ CardstopedScore * 3 + BounceScore * 3 + RefuseScore * 3)
# 月刷卡额/个人月收入
CardpayPersonal = Final['月刷卡额'] / Final['个人月收入']
# 月刷卡额/家庭月收入
CardpayFamily = Final['月刷卡额'] / Final['家庭月收入']
EconomicScore = []
for i in range(Final.shape[0]):
if CardpayPersonal[i] <= 1:
if Final.loc[i, '借款余额'] == 1:
EconomicScore.append(1)
else:
EconomicScore.append(0)
if CardpayPersonal[i] > 1:
if CardpayFamily[i] <= 1:
if Final.loc[i, '借款余额'] == 1:
EconomicScore.append(2)
else:
EconomicScore.append(1)
if CardpayFamily[i] > 1:
if Final.loc[i, '借款余额'] == 1:
EconomicScore.append(4)
else:
EconomicScore.append(2)
# 个人月开销/月刷卡额
OutcomeCardpay = Final['个人月开销'] / Final['月刷卡额']
OutcomeCardpayScore = []
for i in range(Final.shape[0]):
if(OutcomeCardpay[i] <= 1):
OutcomeCardpayScore.append(1)
else:
OutcomeCardpayScore.append(0)
Final['经济风险情况'] = np.array(EconomicScore) + np.array(OutcomeCardpayScore)
# 判断用户是否具有稳定的收入
HouseScore = []
for i in range(Final.shape[0]):
if 3 <= Final.loc[i, '住家'] <= 5:
HouseScore.append(0)
else:
HouseScore.append(1)
JobScore = []
for i in range(Final.shape[0]):
if(Final.loc[i, '职业'] <= 7 | Final.loc[i, '职业'] == 19 |
Final.loc[i, '职业'] == 21):
JobScore.append(2)
if(Final.loc[i, '职业'] >= 8 & Final.loc[i, '职业'] <= 11):
JobScore.append(1)
if(Final.loc[i, '职业'] <= 18 & Final.loc[i, '职业'] >= 12 |
Final.loc[i, '职业'] == 20 | Final.loc[i, '职业'] == 22):
JobScore.append(0)
AgeScore = []
for i in range(Final.shape[0]):
if Final.loc[i, '年龄'] <= 2:
AgeScore.append(1)
else:
AgeScore.append(0)
Final['收入风险情况'] = np.array(HouseScore) + np.array(JobScore) + np.array(AgeScore)
StdScaler = StandardScaler().fit(Final[['历史信用风险', '经济风险情况', '收入风险情况']])
ScoreModel = StdScaler.transform(Final[['历史信用风险', '经济风险情况', '收入风险情况']])
报错：
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1765: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
isetter(loc, value)
<ipython-input-1-2640bc12058d>:78: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
Final['历史信用风险'] = (BuguserSocre + OverdueScore * 2 + BaddebtScore * 3
<ipython-input-1-2640bc12058d>:116: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
Final['经济风险情况'] = np.array(EconomicScore) + np.array(OutcomeCardpayScore)
<ipython-input-1-2640bc12058d>:145: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
Final['收入风险情况'] = np.array(HouseScore) + np.array(JobScore) + np.array(AgeScore)
