pd.read_access怎么用

`pd.read_access`这个函数似乎不存在。可能您想要使用`pd.read_excel`函数来读取Microsoft Access数据库文件（.mdb/.accdb）中的数据。您可以使用以下代码读取Access文件：

import pandas as pd

# 读取Access文件
path_to_db = r'path/to/your/access/file.mdb' # 或者 '.accdb'
conn_str = f"Driver={{Microsoft Access Driver (*.mdb, *.accdb)}};DBQ={path_to_db}"
df = pd.read_sql("SELECT * FROM YourTableName", conn_str)

其中，`path_to_db`是Access数据库文件的路径，`YourTableName`是您想要读取的表的名称。如果需要，您还可以使用SQL语句来处理数据，例如：

# 使用SQL语句读取数据
df = pd.read_sql("SELECT Column1, Column2 FROM YourTableName WHERE Column3 > 10", conn_str)

这将只选择"YourTableName"表中"Column1"和"Column2"列，并且其中"Column3"列的值大于10。

相关问题

from pytorch_tabnet.tab_model import TabNetRegressor import pandas as pd df = pd.read_csv('demo.csv', encoding="GB18030") df.head()

Sorry, as an AI language model, I don't have access to the local files. Can you provide more information about the demo.csv file, like the columns it contains, and the purpose of the code?

temp_df = pd.read_csv(file)

I'm sorry, as an AI language model, I don't have access to your file. Can you please provide more context and information about your file and what you are trying to achieve?