Use error_text_from_code() to get the respective error message.Īs we have already pointed out in another tutorial, all SQLite data types are represented by just five Python types, as indicated in the following table: Python Type Int, 1 stands for True, 0 stands for False. ![]() The following table lists all data types that can be stored in a cell, and the corresponding Python type of the cell value: Type Constant In xlrd, cells are represented by a object, whose type is ctype, and whose value is value. Much like SQLite, Excel stores the data type along with the value of a cell. After installing all required packages, both libraries can be used in a Python module with the appropriate import statements: Take a look at the official documentation for a complete guide on using pip. The -m option of this command executes the pip script and passes some arguments to it. Where pythonexec is the name of the executable file for the Python interpreter, e.g. You can install them using the following commands: pythonexec -m pip install pandas Since both pandas and xlrd are third-party libraries, we have to integrate them in our Python environment. In order to make the algorithms in the case studies more readable, we’re going to define two classes, namely ExcelDocument and ExcelSheet. Case Study 2: An Excel Sheet with Named Rangesīefore trying to read data from an Excel sheet with Python, we have to introduce the pandas and xlrd libraries.Representing an Excel Sheet with the ExcelSheet Class.Representing an Excel Document with the ExcelDocument Class. ![]() ![]() Since data can be stored in different ways in an Excel sheet, we will address three case studies: a plain Excel sheet, an Excel sheet with named ranges, and pivot tables. We will use the sqlite3 standard module, and the pandas and xrld third-party libraries. The aim of this tutorial is to extract data from an Excel sheet and load the data into an SQLite database using Python.
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