Is NaN a float?

[snippsat]

In context of Pandas and NumPy, NaN(Not a Number) is considered a float as they follow IEEE 754 floating-point standard.
Pandas has of course different ways to deal with NaN values.

import pandas as pd
import json
pd.set_option('display.expand_frame_repr', False)

data = {
    '客户编码': [11820122.0, 11820123.0, 11820124.0],
    '客户名称': ['WILLOWOOD FZE （Free Zone Establishment）', 'AgroChem Inc', 'Green Fields'],
    '国家': ['美国', '巴西', '南非'],
    '网址': [pd.NA, 'www.agrochem.com', 'www.greenfields.co.za'],
    '联系人': [pd.NA, 'John Doe', 'Jane Smith'],
    '邮箱': [pd.NA, '[email protected]', '[email protected]'],
    '电话': [pd.NA, '555-1234', '555-5678'],
    '公司地址': [pd.NA, '123 AgroChem Road, Brazil', '789 Green Fields Ave, South Africa'],
    '主要产品': [pd.NA, 'Fertilizers', 'Pesticides']
}

df = pd.DataFrame(data)
# Filter out rows where the '邮箱' (email) column is NaN
df_filtered = df.dropna(subset=['邮箱'])

# Save the customer list to a JSON file
customer_list = df_filtered[['客户编码', '客户名称', '联系人', '邮箱']].to_dict(orient='records')
with open('customers.json', 'w', encoding='utf-8') as fp:
    json.dump(customer_list, fp, ensure_ascii=False, indent=4)

print(f'Customers with email addresses have been saved to {fp.name}')

Output:
[
    {
        "客户编码": 11820123.0,
        "客户名称": "AgroChem Inc",
        "联系人": "John Doe",
        "邮箱": "[email protected]"
    },
    {
        "客户编码": 11820124.0,
        "客户名称": "Green Fields",
        "联系人": "Jane Smith",
        "邮箱": "[email protected]"
    }
]