将以下代码：import os import pandas as pd folder_path = "D:/活动生成" file_name = "活动.xlsx" new_file_name = "一口价3.xlsx" activity_file_path = os.path.join(folder_path, file_name) activity_df = pd.read_excel(activity_file_path) discounts = {"6.9折": 0.69, "5折": 0.5, "3.9折": 0.39} new_price_df = pd.DataFrame(columns=["商品编码", "价格"]) for index, row in activity_df.iterrows(): if row["活动"] in discounts: standard_price = row["标准售价"] discount = discounts.get(row["活动"], 1) new_price = round(standard_price * discount, 2) # convert product code to 7 digits product_code = str(row["商品编码"]).zfill(7) new_price_df.loc[index] = [product_code, new_price] new_file_path = os.path.join(folder_path, new_file_name) new_price_df.to_excel(new_file_path, index=False) print("已生成") 生成一个exe文件，并可以让我下载使用

为了将Python代码转换为可执行文件（exe文件），你可以使用PyInstaller库。首先，你需要在命令行中安装PyInstaller库：

pip install pyinstaller

安装完成后，打开命令行，进入代码所在目录，运行以下命令：

pyinstaller --onefile filename.py

其中，`filename.py`是你要打包成可执行文件的Python文件名。执行完这个命令后，PyInstaller将会在同一目录下生成一个`dist`文件夹，里面就是可执行文件。你可以将`dist`文件夹中的`filename.exe`文件发送给用户使用。

需要注意的是，如果你的Python文件中用到了第三方库，那么在生成可执行文件之前，你需要先将这些库打包进来。你可以使用以下命令生成一个包含所有依赖库的可执行文件：

pyinstaller --onefile --add-data "path/to/library;." filename.py

其中，`path/to/library`是你要打包进来的依赖库的路径。如果有多个依赖库，可以多次使用`--add-data`参数。

相关问题

代码：import os import pandas as pd folder_path = "D:/活动生成" file_name = "活动.xlsx" new_file_name = "一口价3.xlsx" activity_file_path = os.path.join(folder_path, file_name) activity_df = pd.read_excel(activity_file_path) discounts = {"6.9折": 0.69, "5折": 0.5, "3.9折": 0.39} new_price_df = pd.DataFrame(columns=["商品编码", "价格"]) for index, row in activity_df.iterrows(): if row["活动"] in discounts: standard_price = row["标准售价"] discount = discounts.get(row["活动"], 1) new_price = round(standard_price * discount, 2) # only save the 7-digit 商品编码 product_code = str(row["商品编码"]) if len(product_code) == 7: new_price_df.loc[index] = [product_code, new_price] new_file_path = os.path.join(folder_path, new_file_name) new_price_df.to_excel(new_file_path, index=False) print("已生成") 没法保存商品编码为0开头的商品编码，例如商品编码为：0311069的商品编码不能保存，我需要将0开头的商品编码能进行计算的同时也保存下来

可以将商品编码转换为字符串后，判断字符串长度是否为7位，如果不足7位，在前面添加相应数量的0，使其长度为7位。修改后的代码如下：

import os
import pandas as pd

folder_path = "D:/活动生成"
file_name = "活动.xlsx"
new_file_name = "一口价3.xlsx"

activity_file_path = os.path.join(folder_path, file_name)
activity_df = pd.read_excel(activity_file_path)

discounts = {"6.9折": 0.69, "5折": 0.5, "3.9折": 0.39}

new_price_df = pd.DataFrame(columns=["商品编码", "价格"])

for index, row in activity_df.iterrows():
    if row["活动"] in discounts:
        standard_price = row["标准售价"]
        discount = discounts.get(row["活动"], 1)
        new_price = round(standard_price * discount, 2)

        # convert product code to 7 digits
        product_code = str(row["商品编码"]).zfill(7)

        new_price_df.loc[index] = [product_code, new_price]

new_file_path = os.path.join(folder_path, new_file_name)
new_price_df.to_excel(new_file_path, index=False)

print("已生成")

这样就可以保存商品编码为0开头的商品编码了。

代码：import os import pandas as pd print("开始计算一口价") folder_path = "D:/一口价生成" file_name = "活动.xlsx" new_file_name = "一口价及升价3.xlsx" activity_file_path = os.path.join(folder_path, file_name) activity_df = pd.read_excel(activity_file_path) discounts = {"6.9折": 0.69, "5折": 0.5, "3.9折": 0.39} new_price_df = pd.DataFrame(columns=["商品编码", "价格"]) for index, row in activity_df.iterrows(): if row["活动"] in discounts: standard_price = row["标准售价"] discount = discounts.get(row["活动"], 1) new_price = round(standard_price * discount, 2) product_code = str(row["商品编码"]).zfill(7) new_price_df.loc[index] = [product_code, new_price] elif isinstance(row["活动"], int) or isinstance(row["活动"], float): product_code = str(row["商品编码"]).zfill(7) new_price = int(row["活动"]) new_price_df.loc[index] = [product_code, new_price] new_file_path = os.path.join(folder_path, new_file_name) new_price_df.to_excel(new_file_path, index=False) new_file_path = os.path.join(folder_path, new_file_name) new_price_df.to_excel(new_file_path, index=False) print("已生成") 将“活动”列中所有数值都以int类型输出了，请修改代码输出类型位：如果是int类型，则输出int类型。是float类型，就输出float类型。，

代码：

import os
import pandas as pd

print("开始计算一口价")

folder_path = "D:/一口价生成"
file_name = "活动.xlsx"
new_file_name = "一口价及升价3.xlsx"

activity_file_path = os.path.join(folder_path, file_name)
activity_df = pd.read_excel(activity_file_path)

discounts = {"6.9折": 0.69, "5折": 0.5, "3.9折": 0.39}

new_price_df = pd.DataFrame(columns=["商品编码", "价格"])

for index, row in activity_df.iterrows():
if row["活动"] in discounts:
standard_price = row["标准售价"]
discount = discounts.get(row["活动"], 1)
new_price = round(standard_price * discount, 2)
product_code = str(row["商品编码"]).zfill(7)
new_price_df.loc[index] = [product_code, new_price]
elif isinstance(row["活动"], int):
product_code = str(row["商品编码"]).zfill(7)
new_price = int(row["活动"])
new_price_df.loc[index] = [product_code, new_price]
elif isinstance(row["活动"], float):
product_code = str(row["商品编码"]).zfill(7)
new_price = float(row["活动"])
new_price_df.loc[index] = [product_code, new_price]

new_file_path = os.path.join(folder_path, new_file_name)
new_price_df.to_excel(new_file_path, index=False)

print("已生成")

修改后的代码中，增加了判断“活动”列中是否为float类型的判断条件，并针对不同类型输出对应类型的数据。