How to fix errors when reading Excel data in Python?

When reading Excel data in Python, common error situations include the following:

1. Module import error: Before reading an Excel file, it is necessary to import the relevant modules, such as pandas, xlrd, etc. If there is an error indicating that the module does not exist, you can install the corresponding module using the pip install command, or check for any spelling errors.
2. Incorrect file path: When reading an Excel file, you need to provide the correct file path. If an error message indicates that the file does not exist, you can check if the file path is correct, or use an absolute path to access the file.
3. If the Sheet doesn’t exist: If the Sheet you want to read in the Excel file does not exist, an error will be prompted indicating that the Sheet does not exist. You can specify the name of the Sheet to be read by using the sheet_name parameter in pd.read_excel.
4. Encoding error: When reading an Excel file, it is necessary to specify the correct encoding format. If an error message indicating an encoding error appears, you can try using different encoding formats such as utf-8, gbk, etc.
5. Error in data type: The data in Excel may contain different data types such as strings, integers, and floating-point numbers. If the data types do not match, an error will be prompted indicating a data type error. You can specify the data type through the dtype parameter, or convert the data type after reading the data.
6. Dealing with missing values: Data in Excel may contain missing values, such as empty cells. If the missing values are not handled, errors will occur when reading the data. Missing values can be addressed using the dropna() function or the fillna() function.

Specific solutions can be implemented based on the specific error messages. If the problem still cannot be resolved, providing the error messages and relevant code can help better address the issue.