Python

Python Matplotlib is the standard library for charts. With a few lines you can draw line, bar and pie charts from lists or pandas DataFrames, label them, style them and save them as PNG files for reports and slides. This chapter builds each chart type step by step using the sales data from the pandas […]

The pandas Excel and CSV functions, read_csv(), read_excel(), to_csv() and to_excel(), move data between files and DataFrames in one line each. This chapter loads a sales file, fixes dates and types on the way in, writes a multi-sheet Excel report with ExcelWriter, combines monthly CSV exports and polishes the workbook with openpyxl. Install pandas and […]

Python classes and objects let you bundle data and the functions that work on it into one named thing. A class is the blueprint (Employee, Invoice, Product); an object is one concrete instance built from it. The __init__ method sets up each new object, self refers to the object being worked on, and methods are […]

This Python cheat sheet puts the syntax from all 48 chapters of the course on one page: variables, strings, collections, control flow, functions, classes, files and pandas basics. Each table shows the statement, a short business-flavoured example and the result, and links to the chapter that explains it. Bookmark it and keep it open while […]

Python pandas is the library for working with tables of data. Its DataFrame holds rows and columns like a spreadsheet, and with a few methods you can filter, sort, group and pivot thousands of rows in seconds. This chapter builds a small sales DataFrame and uses it to learn selection, filtering, new columns, groupby() and […]

Python CSV handling uses the built-in csv module to read and write comma-separated files, the plain-text format that Excel, Google Sheets, banks and almost every business system can export. reader and writer work with lists, DictReader and DictWriter work with dictionaries keyed by column name, and dialect options handle semicolons, quotes and other regional quirks. […]

These Python projects for beginners are ten small, complete programs that each solve a real office task: invoices, deadlines, expenses, exchange rates, a sales chart and an AI meeting summary. Every project is under 30 lines, runs on Python 3.12, prints a result you can check, and lists the course chapters it uses so you […]

Python NumPy is the library for fast numerical work. Its core object, the ndarray, stores numbers of one type in a compact block of memory and lets you calculate on thousands of values with a single expression instead of a loop. NumPy also powers pandas, Matplotlib and most data science tools, so learning it pays […]

Python dictionaries store data as key-value pairs inside curly braces, such as {“name”: “Anita”, “dept”: “Finance”}. You look values up by key instead of by position, which makes a dictionary the natural shape for a record, a lookup table or a set of counts. This chapter covers creating Python dictionaries, reading and updating values, looping, […]

Python file handling means creating, reading, writing, appending and deleting files from your scripts. The built-in open() function and the with statement do the reading and writing, while pathlib handles paths, folders and file operations in a way that works identically on Windows, Mac and Linux. Almost every automation touches a file: a log to […]