Mirror Mirror Study Session 3

Hyunwoo summarized the content up through chapter 3.3, and learned the basic methods for handling Excel workbooks with Python.

The core tools branched into two approaches.

• Reading and writing Excel files with xlrd, xlwt
• Simplifying dataframe-style processing with pandas

For a single worksheet, input/output was handled using functions like add_sheet(), write(), and open_workbook(), and date formats were handled with datetime.date() and xldate_as_tuple(). Using pandas made the work much more convenient with read_excel() and ExcelWriter(), and row filtering could be handled with conditional expressions, isin(), and regular expressions (re.compile()). Column selection was organized around using iloc() or loc().

When dealing with multiple worksheets, they confirmed methods for either reading everything at once with sheetname=None, or selectively reading only the needed sheets with sheet_by_index() and sheet_by_name(). In the advanced session, Hoseong showed the process of designing pseudo code first, pointing out that it's important to practice organizing code logically before moving on to actual implementation.

Although it had only been 2 weeks since starting to learn Python, compared to past experience handling Excel and CSV with C++, the efficiency and simplicity of Python really stood out. However, it was noted that since the new tools were so convenient, a process of getting used to them was still needed, and that the usefulness of studying data analysis would only really sink in with more practice.

They studied together until late and ate pizza too, but since the atmosphere felt unfamiliar and awkward, not much was eaten. The session wrapped up with the thought that next time, things could feel more familiar and they could spend more time together.