Python: Data Analysis in the Office

The aim of the course is to demonstrate how the Python programming language can be applied to solve everyday tasks such as data handling, visualization, automation, database management, and forecasting based on existing data. During the training, participants will gain practical knowledge that enables them to complete their daily tasks faster and more efficiently using Python.

The course specifically focuses on office environments and business use cases: participants will learn how to work with Excel files using Python, automate repetitive data processing tasks, create professional visualizations for reports, and send emails automatically. During the training, pandas, matplotlib, seaborn, and other widely used Python libraries will be applied.

In addition to the practical approach, the course emphasizes solving real workplace problems such as data cleaning, reporting, data visualization, and automation. By the end of the course, participants will be able to independently write Python scripts to automate office tasks and perform data analysis activities.

The course is recommended for a wide range of participants:

• Entry-level and practicing IT professionals
• Office professionals who want to automate their workflows
• Professionals working with data management
• Employees involved in analysis and reporting

This course is for you if:

• You work with Excel daily and want to automate your tasks
• You are involved in data analysis
• You regularly create reports
• You perform repetitive data processing tasks
• You want to create data visualizations
• You send emails with attachments
• You work with SQL databases
• You want to make your office work more efficient

The Python - Data Analysis in the Office course offers a range of benefits:

• Increased Productivity: Automate repetitive tasks
• Time Savings: Faster data processing compared to Excel
• Professional Visualization: Create attractive, publishable charts
• Scalability: Handle large volumes of data
• Automation: Automate email sending and report generation
• Practical Knowledge: Immediately applicable in the workplace
• Career Opportunities: Data analysis and automation skills

Data Handling with the pandas Library

• Introduction to pandas
• DataFrame and Series data structures
• Loading data from various sources
• Reading and writing CSV files
• Handling Excel files
• Data transformation
• Filtering and selecting data
• Aggregation and grouping
• Combining data

Data Visualization

• Matplotlib basics
• Creating basic charts
• Scatter plots
• Using Matplotlib
• Visualizing data
• Customizing charts
• Saving charts
• Multiple charts in one figure

Email Automation

• SMTP protocol basics
• Using an SMTP client in Python
• Creating email messages
• Managing recipients
• Formatting email subject and body
• Creating HTML emails
• Handling attachments
• Managing multiple attachments

Database Management

• Overview of SQL basics (SELECT, WHERE, JOIN)
• Connecting to SQL databases (SQLAlchemy)
• PostgreSQL/MySQL connection
• Creating and running queries from Python
• pandas and SQL integration
• Loading data from databases into DataFrames

• Knowledge of Python syntax (variables, data types, operators)
• Use of control structures (if/else, loops)
• Defining and using functions
• Basic Python data structures (lists, dictionaries, tuples)
• File handling in Python (reading and writing files)
• Importing modules and packages
• Basic programming logic and problem solving
• Using Excel in daily work
• Knowledge of file system and folder management

The course assumes that participants are able to write and run Python scripts independently and have practical experience with Excel in an office environment. SQL knowledge is particularly useful for the database management module, but the necessary SQL basics will also be reviewed during the course.