如何使用pandas替换csv文件中的NaN值，然后将其存储到MySQL中？

import pandas as pd
import numpy as np
import pymysql
from sqlalchemy import create_engine

df = pd.read_csv('your_file.csv')
df = df.fillna(value=np.nan)  # 将所有NaN值替换为np.nan

host = 'your_host'
port = your_port
user = 'your_username'
password = 'your_password'
database = 'your_database'

conn = pymysql.connect(host=host, port=port, user=user, password=password, database=database)

table_name = 'your_table_name'

# 创建引擎
engine = create_engine(f'mysql+pymysql://{user}:{password}@{host}:{port}/{database}')

# 将DataFrame写入MySQL数据库
df.to_sql(name=table_name, con=engine, if_exists='replace', index=False)

conn.close()

import pandas as pd
import numpy as np
import pymysql
from sqlalchemy import create_engine

# 读取CSV文件并替换NaN值
df = pd.read_csv('your_file.csv')
df = df.fillna(value=np.nan)  # 将所有NaN值替换为np.nan

# 连接到MySQL数据库
host = 'your_host'
port = your_port
user = 'your_username'
password = 'your_password'
database = 'your_database'

conn = pymysql.connect(host=host, port=port, user=user, password=password, database=database)

# 创建数据库表（如果需要）
table_name = 'your_table_name'

# 创建引擎
engine = create_engine(f'mysql+pymysql://{user}:{password}@{host}:{port}/{database}')

# 将DataFrame写入MySQL数据库
df.to_sql(name=table_name, con=engine, if_exists='replace', index=False)

# 关闭数据库连接
conn.close()