for 循环中Faker 库的exec() 方法调用| Python

问题描述

使用Faker 库；我正在 Jupyter Notebooks 中模拟数据集。

import numpy as np
import pandas as pd

from faker import Faker
fake = Faker()

import random

np.random.seed(42)


def example_dataset_simulation(samples):
    df = pd.DataFrame(index=np.arange(samples))
    
    df['ID'] = [str(i) for i in range(1,samples+1)]
    df['Prefix'] = [fake.prefix_male() for _ in range(samples)]
    df['Forename'] = [fake.first_name_male() for _ in range(samples)]
    df['Surname'] = [fake.last_name_nonbinary() for _ in range(samples)]
    
    return df


df = example_dataset_simulation(500)
df

输出成功。每次生成唯一的数据集。

现在，我希望能够更改函数以添加 n 列数，作为传递名为 cols 的可变整数。

---

所需的循环代码：

list = [["Prefix","fake.prefix_male()"],["Forename","fake.first_name_male()"],["Surname","fake.last_name_nonbinary()"],["Suffix","fake.suffix_male()"],["dob","fake.date()"],["e-mail","fake.company_email()"],["Telephone","fake.phone_number()"]]

def example_dataset_simulation(samples,cols):
   df = pd.DataFrame(index=np.arange(samples))
   
   df['Prefix'] = [fake.prefix_male() for _ in range(samples)]  # once
   
   for col_name,method in list[:cols-1]:
       df[str(col_name)] = [eval(method) for _ in range(samples)]  # cols-1
   
   return df

输出：

500 rows × 3 columns

解决方法

eval() 正是我想要的。

list = [["Prefix","fake.prefix_male()"],["Forename","fake.first_name_male()"],["Surname","fake.last_name_nonbinary()"],["Suffix","fake.suffix_male()"],["DOB","fake.date()"],["e-mail","fake.company_email()"],["Telephone","fake.phone_number()"]]

def example_dataset_simulation(samples,cols):
    df = pd.DataFrame(index=np.arange(samples))
    
    df['Prefix'] = [fake.prefix_male() for _ in range(samples)]  # once
    
    for col_name,method in list[:cols]:
        df[str(col_name)] = [eval(method) for _ in range(samples)]  # cols-1
    
    return df

df = example_dataset_simulation(500,6)
df
>>> 500 rows × 6 columns