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用faker模拟数据+随机种子

%config ZMQInteractiveShell.ast_node_interactivity='all' 
%pprint
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导入工具包​

import pandas as pd
from faker import Faker

创建实例,设置本地化​

fake = Faker('zh_CN')

创建模拟个人数据函数,设定随机种子​

def generate_user(i):
    fake.random.seed(i)
    return dict(name=fake.name(),password=fake.password(length=10),company=fake.company(),job=fake.job(),birthday=fake.date_of_birth(minimum_age=0, maximum_age=120),
                telephone=fake.phone_number(),
                address=fake.address())

生成客户模拟数据列表, 用dataframe呈现​

users = []
for i in range(5):
    users.append(generate_user(i))
df = pd.DataFrame(users)
df

png

验证随机种子设定是否成功​

users = []
for i in range(8):
    users.append(generate_user(i))
df = pd.DataFrame(users)
df

png

导出数据,生成csv文件​

df.to_csv('./fakedata.csv')

查看博客资料

资料索引​

  1. 用faker模拟数据

  2. faker官网

  3. 标准provides

  4. 第三方provides