标签：elif return 函数 python 用法 str apply import data

1、性别

def xb(x):
if pd.isnull(x):
return "空"
elif int(x[-2])%2 == 1:
return "男"
elif int(x[-2])%2 == 0:
return "女"
else:return "其他"
def f(x):
return x.nunique()

2、省份

def province(x):
if str(x)[0:2] =='11' :
return '北京'
elif str(x)[0:2] =='12' :
return '天津'
elif str(x)[0:2] =='13' :
return '河北'
elif str(x)[0:2] =='14' :
return '山西'
elif str(x)[0:2] =='15' :
return '内蒙古'
elif str(x)[0:2] =='21' :
return '辽宁'
elif str(x)[0:2] =='22' :
return '吉林'
elif str(x)[0:2] =='23' :
return '黑龙江'
elif str(x)[0:2] =='31' :
return '上海'
elif str(x)[0:2] =='32' :
return '江苏'
elif str(x)[0:2] =='33' :
return '浙江'
elif str(x)[0:2] =='34' :
return '安徽'
elif str(x)[0:2] =='35' :
return '福建'
elif str(x)[0:2] =='36' :
return '江西'
elif str(x)[0:2] =='37' :
return '山东'
elif str(x)[0:2] =='41' :
return '河南'
elif str(x)[0:2] =='42' :
return '湖北'
elif str(x)[0:2] =='43' :
return '湖南'
elif str(x)[0:2] =='44' :
return '广东'
elif str(x)[0:2] =='45' :
return '广西'
elif str(x)[0:2] =='46' :
return '海南'
elif str(x)[0:2] =='50' :
return '重庆'
elif str(x)[0:2] =='51' :
return '四川'
elif str(x)[0:2] =='52' :
return '贵州'
elif str(x)[0:2] =='53' :
return '云南'
elif str(x)[0:2] =='54' :
return '西藏'
elif str(x)[0:2] =='61' :
return '陕西'
elif str(x)[0:2] =='62' :
return '甘肃'
elif str(x)[0:2] =='63' :
return '青海'
elif str(x)[0:2] =='64' :
return '宁夏'
else : return '新疆'

3、年龄

import datetime
def ag1(x):
if pd.isnull(x):
return "其他"
else:
birth_year = int(x[6:10])
today_year = datetime.date.today().year
return (today_year - birth_year)
data['年龄']=data['id_card_no'].apply(ag1)

4、邮件自动化

import openpyxl
dst_xlsx = '/data/python_home/cqg/data_model.xlsx'#模板，设置格式。
file_path = '/data/python_home/cqg/youjian.xlsx'#最终写好的模板路径
df=openpyxl.load_workbook(dst_xlsx) # 打开模板
tar = pd.read_excel('/data/python_home/cqg/duibi1.xlsx')#目标数据
tar
dt=pd.read_excel('data_model.xlsx')#打开看一下模板长啥样
dt
fund_list = ['多平台']
for k in range(1):
sheet0 = df.worksheets[k]# sheet页
target_data = pd.read_excel('/data/python_home/cqg/duibi1.xlsx').reset_index().T.reset_index().T.iloc[1:,2:10]
for i in range(len(target_data)):
#print(target_data.iloc[i,:])
for j in range(8):
sheet0.cell(i+3,j+1).value = target_data.iloc[(i,j)] # 写入数据
#sheet0.cell(i+1,j+1).alignment = Alignment(horizontal='center', vertical='center') # 居中对齐
df.save(file_path) # 保存文件
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
import smtplib
from email.mime.image import MIMEImage
import datetime
mail_host = "smtphz.qiye.163.com" #SMTP服务器地址
mail_sender = "[email protected]" #账号
mail_passwd = "Cloud@12@@" #密码

msg = MIMEMultipart('related')
msg["Subject"] = '多平台对比'
msg["From"] = mail_sender #发送人
receiver=['[email protected]']

邮件正文

content = '''
各位好:
'''

import datetime

yesterday = datetime.date.today()-datetime.timedelta(days=1)

msg.attach(MIMEText(content,'plain','utf-8'))

file_path = '/data/python_home/cqg2/数据情况1.xlsx'

构造附件2，xlsx文件

att2 = MIMEText(open(file_path, 'rb').read(), 'base64', 'utf-8')
att2["Content-Type"] = 'application/octet-stream'
att2.add_header("Content-Disposition",'attachment', filename=file_path)
msg.attach(att2)

s = smtplib.SMTP() #实例化对象
s.connect(mail_host) #连接163邮箱服务器，端口号为465,注意，这里不需要写端口号
s.login(mail_sender, mail_passwd) #登录邮箱
s.sendmail(mail_sender, receiver, msg.as_string())
s.quit()

6、聚合新增一列

zt['借款总次数']=zt.groupby('idcard')['loan_date'].transform('count')

7、将数据拆分并计数

yxjj['reason_code']=yxjj['reason_code'].apply(lambda x:str(x).split(", "))
def hmd(x):
a=0
for i in x:
if i in ['']:
a=a+1
return a

8、日期类型转为字符串

import datetime
now = datetime.datetime.now()
(s,'%Y/%m/%d %H:%M:%S') #先将字符串变成时间，再将时间变为字符串且此时可选择日期格式
将其他类型变成时间类型，不能随意改格式
to_datetime(arg=data['apply_date'],format="%Y-%m-%d")
ZT[i]=ZT[i].apply(lambda x: x.days)
today_year = datetime.date.today().year
字符串变时间类型
data['apply_date']=data['apply_date'].apply(lambda x:dt.datetime.strptime(x,"%Y-%m-%d"))
时间类型变字符串
import datetime as dt
data['apply_date']=data['apply_date'].apply(lambda x:x.strftime('%Y-%m'))

9、画图

画图，柱状图
import matplotlib.pyplot as plt
import numpy as np
import matplotlib as mpl
y=[10,30,14,15,5,5]
name=['10_20','20_30','30_40','40_50','50_60','60_70']
plt.bar(x,y,tick_label=name,width=3)
plt.ylim((0,35))
for x,y in zip(x,y):
plt.text(x,y,y,ha='center',va='bottom')

点图
import matplotlib.pyplot as plt
import matplotlib as mpl
import matplotlib.pyplot as plt
x=[10,3,1,12,14,5,8,9,14,15,21]
y2=[15,31,2,14,15,6,31,20,25,12,12]
plt.scatter(x,y2)
plt.legend()
plt.show()

10循环写入

testxlsx=pd.ExcelWriter('test.xlsx')
for i in plat_360:
for j in range(0,len(needcolumns)):
if needcolumns[j]!='省份':
table=pd.pivot_table(data_cgm_360_copy_dropdup[data_cgm_360_copy_dropdup.plati],index='等级',columns=needcolumns[j],values='phone',aggfunc=f,margins=True)
for z in table.columns:
table[str(z)+'占比']=table[z]/table['All']
table[str(z)+'占比']=table[str(z)+'占比'].apply(lambda x:format(x100,'.2f')+'%')
table.insert(0,'type',value=needcolumns[j])
title[title.index0].style.set_properties({'text-align':'center'}).to_excel(testxlsx,sheet_name=i,startrow=0,index=False)
dengjitable360=pd.pivot_table
(data_cgm_360_copy_dropdup[data_cgm_360_copy_dropdup.plat==i],index='等级',values='phone',aggfunc=f).rename(columns={'phone':'用户数'})
dengjitable360['用户数占比']=dengjitable360['用户数']/dengjitable360['用户数'].sum()
dengjitable360['用户数占比']=dengjitable360['用户数占比'].apply(lambda x:format(x100,'.2f')+'%')
dengjitable360.style.set_properties().to_excel(testxlsx,sheet_name=i,startrow=83)
table.drop(columns='All占比').style.set_properties({'text-align':'center'}).to_excel(testxlsx,sheet_name=i,startrow=j*13+2)
pjnl=pd.pivot_table(data_cgm_360_copy_dropdup[data_cgm_360_copy_dropdup.plati],index='等级',values='年龄',aggfunc=np.mean).rename(columns={'年龄':'平均年龄'})
pjnl.to_excel(testxlsx,sheet_name=i,startrow=15,startcol=16)
else:
table=pd.pivot_table(data_cgm_360_copy_dropdup[data_cgm_360_copy_dropdup.plati],index='等级',columns=needcolumns[j],values='phone',aggfunc=f,margins=True)
table.insert(0,'type',value=needcolumns[j])
table.style.set_properties().to_excel(testxlsx,sheet_name=i,startrow=69)
setsheetwidth=testxlsx.sheets[i]
setsheetwidth.set_column('A:Q',16)
textxlsx.save()

11、四种分箱

cut

sx['kh_loanterm']=pd.cut(sx['kh_loanterm'],bins=[3,6,9,12,15,np.inf],right=False,
labels=['A_3','B_6','C_9','D_12','E_15'])

占位符

def 朴道_海纳综合指数V2_申请命中网络贷款类机构数_trans(x):
# 朴道_海纳综合指数V2_申请命中网络贷款类机构数连续型特征的分箱转换函数
inf = np.inf
bins = [-inf, 0.5, 1.5, 2.5, 13.5, inf]
for i in range(len(bins)-1):
start = bins[i]
end = bins[i+1]
if start < x <= end:
return "{0}({1}, {2}]".format(i+1, start, end) # 分箱字符串格式： i(start, end]
return '0_nan'
fksx1[i]=fksx1[i].cat.add_categories(['空值'])

占位符升级

def kh_jld_ApplyTime_hour_bin(x):
values=[4,8,12,18,23]
index=['A','B','C','D']
for i in range(len(values)-1):
if values[i]<x<=values[i+1]:
return '{0}_({1},{2}]'.format(index[i],values[i],values[i+1])
return 'G_未知'

qcut

for i in coll:
sx[i]=pd.qcut(sx[sx[i]>=0][i],q=5,duplicates='drop')
sx[i]=sx[i].astype('str')
sx[i].replace('nan',np.nan,inplace=True)
sx[i].fillna(sx2[i],inplace=True)

12、把时间变为周

mysql专用：

周日开始
concat(str_to_date(concat(yearweek(apply_date), ' Sunday'), '%X%V %W'),"~",date_add(str_to_date(concat(yearweek(apply_date), ' Sunday'), '%X%V %W'),interval 6 day)) AS APPLY_WEE
周一开始
concat(str_to_date(concat(yearweek(apply_date,1),'Monday'),'%x%v %W'),"~",date_add(str_to_date(concat(yearweek(apply_date,1),'Monday'),'%x%v %W'),interval 6 day)) AS APPLY_WEEK

Python函数：

周一开始
import datetime as dt
def get_monday_to_sunday(today):
today = dt.datetime.strptime(str(today), "%Y-%m-%d")
monday = dt.datetime.strftime(today - dt.timedelta(today.weekday()), "%Y-%m-%d")
monday_ = dt.datetime.strptime(monday, "%Y-%m-%d")
sunday = dt.datetime.strftime(monday_ + dt.timedelta(monday_.weekday() + 6), "%Y-%m-%d")
monday1=str(monday)
sunday1=str(sunday)
return monday1+"~"+sunday1

数仓专用

周一开始

concat(DATE_ADD(NEXT_DAY(放款日期,'星期天'),-6),"~",NEXT_DAY(放款日期,'星期天')) week

13、KS和IV（pycard）

KS循环

testks=pd.ExcelWriter('test1.xlsx')
columns_df=pd.DataFrame(mx2.columns)
for i,j in enumerate(mx2.columns):
result=toad.metrics.KS_bucket(mx[j],mx['target'],bucket=10,method='quantile').sort_index()
result.to_excel(testks,sheet_name='kskn',startrow=14*i+1,index=False)
testks.save()
testks.close()

分箱加结果

data_sd = ZT3
import pycard as pc
num_iv_woedf = pd.DataFrame()
clf = pc.NumBin()
for i in coll:
if data_sd[i].isnull().sum()/len(data_sd)<1:
clf.fit(data_sd[i] ,data_sd['dpd30+'])
num_iv_woedf = num_iv_woedf.append(clf.woe_df_)

原始分箱

import toad
import scorecardpy as sc
str(x).strip()
toad.detector.detect()
toad.metrics.KS_bucket(x,y,bucket=10,method = 'quantile')
bins = sc.woebin(y2, y="target")#y2是数据，里面的目标列用target
sc.woebin_plot(bins)
breaks_adj = {'xy':[1，2，3，4]}
bins_adj = sc.woebin(y2, y="target",breaks_list=breaks_adj)
sc.woebin_plot(bins_adj)

bins_result= pd.DataFrame()
for value in bins.values():
bins_result=bins_result.append(value)
bins_result.to_excel("IV.xlsx")

14异常展示

展示异常

import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签
plt.rcParams['axes.unicode_minus']=False #用来正常显示负号

15、第一行设为列名

import numpy as np
array = np.array(zt1)
list = array.tolist()
list = list[0]
zt1.columns = list

16、加密

sha256加密

import hashlib
def sha256_jiami(x):
'''
Parameters
----------
x : string
需要加密的字符串.

Returns
-------
字符窜加密后的字符

'''
sha256 = hashlib.sha256()
sha256.update(x.encode('utf-8'))
return sha256.hexdigest()

target_01['phone_sha256'] = target_01['Phone'].apply(sha256_jiami)

MD5加密

import hashlib
def md5_jiami(x):
Jpwd = hashlib.md5()
Jpwd.update(x.encode('utf-8'))
return Jpwd.hexdigest()
zt1['手机号']=zt1['手机号'].apply(md5_jiami)

17、计算PSI

HX1['本月-训练集']=HX1.apply(lambda x:(x.本月-x.训练集)*math.log(x.本月/x.训练集),axis=1)
HX1.loc['Row_sum'] = HX1.iloc[:,1:].apply(lambda x: x.sum())

18、pycard分析

for i in ['dpd1+']:
for j in kncol:
tmp_data = pc.cross_woe(kn[j],kn[i]).reset_index()
tmp_data.insert(0,'type',value=i)
tmp_data.rename({j:'区间'},axis=1,inplace=True)
data_iv = data_iv.append(tmp_data)
data_iv

标签：elif,return,函数,python,用法,str,apply,import,data
From： https://www.cnblogs.com/chenqianguan/p/18078559

python一些函数用法

1、性别

2、省份

3、年龄

4、邮件自动化

邮件正文

import datetime

yesterday = datetime.date.today()-datetime.timedelta(days=1)

构造附件2，xlsx文件

6、聚合新增一列

7、将数据拆分并计数

8、日期类型转为字符串

9、画图

10循环写入

11、四种分箱

cut

占位符

占位符升级

qcut

12、把时间变为周

mysql专用：

Python函数：

数仓专用

周一开始

13、KS和IV（pycard）

KS循环

分箱加结果

原始分箱

14异常展示

展示异常

15、第一行设为列名

16、加密

sha256加密

MD5加密

17、计算PSI

18、pycard分析

相关文章

赞助商

阅读排行

python一些函数用法

1、性别

2、省份

3、年龄

4、邮件自动化

邮件正文

import datetime

yesterday = datetime.date.today()-datetime.timedelta(days=1)

构造附件2，xlsx文件

6、聚合新增一列

7、将数据拆分并计数

8、日期类型转为字符串

9、画图

10循环写入

11、四种分箱

cut

占位符

占位符升级

qcut

12、把时间变为周

mysql专用：

Python函数 ：

数仓专用

周一开始

13、KS和IV（pycard）

KS循环

分箱加结果

原始分箱

14异常展示

展示异常

15、第一行设为列名

16、加密

sha256加密

MD5加密

17、计算PSI

18、pycard分析

相关文章

赞助商

阅读排行

Python函数：