Description
Training objective: Enable participants to acquire intermediate-level skills in Python for data handling, preparation, and exploration, allowing them to source data from various sources, clean and prepare it, and process it for further analysis.
Objectifs pédagogiques
- Work with Pandas and NumPy for data manipulation and cleaning.
- Source and import data from databases using SQLAlchemy.
- Acquire data through web scraping using BeautifulSoup.
- Prepare and integrate datasets for analysis by performing cleaning and initial exploration.
Public concerné
Professionals with foundational Python knowledge, particularly those looking to develop skills in data handling, cleaning, and preparation for data analysis.
Prérequis
Completion of Python - Basic or equivalent knowledge of Python fundamentals, including basic data structures, control flow, functions, and file handling.
Déroulé du programme
1
Introduction to Pandas DataFrames (2.5 hours)
5h
- Creating and manipulating DataFrames
- Common operations: filtering, sorting, grouping
- Data selection, indexing, and slicing
- Practical exercise: Importing datasets and performing data manipulation tasks, such as selecting columns, filtering rows, and grouping data
2
NumPy arrays for data manipulation (1.5 hours)
5h
- Introduction to NumPy arrays for numerical operations
- Basic operations, reshaping, and indexing in NumPy
- Practical exercise: Using NumPy arrays to perform calculations and transformations on datasets
3
Advanced data cleaning techniques (2 hours)
2h
- Handling missing data: filling and removing
- Removing duplicates and managing inconsistent data
- Data transformation: renaming, merging, and concatenating
- Practical exercise: Cleaning a messy dataset by applying transformations, handling missing values, and standardizing formats
4
Database interaction with SQLAlchemy (2.5 hours)
5h
- Connecting to databases using SQLAlchemy
- Basic SQL queries (SELECT, JOIN, etc.) in Python
- Importing data from databases into Pandas for further processing
- Practical exercise: Connecting to a sample database, running queries, and loading data into Pandas for analysis
5
Web scraping with BeautifulSoup (2.5 hours)
5h
- Setting up BeautifulSoup for web scraping
- Selecting and extracting HTML elements (tags, classes, attributes)
- Ethical considerations in web scraping
- Practical exercise: Scraping data from a sample webpage, extracting tables, and loading them into a Pandas DataFrame
6
Data integration and exploration (1 hour)
1h
- Combining data from various sources: merging and concatenating DataFrames
- Initial data exploration: summary statistics, visual checks, and outlier detection
- Practical exercise: Integrating multiple datasets from different sources and performing initial exploration for analysis readiness
Informations
Durée
2 jour(s)
12h
Tarif
Sur demande
