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Hands-on Data Analysis with Pandas (TTPS4878)

4.6 out of 5 rating

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3 Days

18 CPD hours

About this course

This introductory-level course is for anyone in IT interested in on basic exposure to leveraging Python for data science and analytics.


This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current "on-the-job" experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn to: - Understand how data analysts and scientists gather and analyze data - Perform data analysis and data wrangling using Python - Combine, group, and aggregate data from multiple sources - Create data visualizations with pandas, matplotlib, and seaborn - Apply machine learning (ML) algorithms to identify patterns and make predictions - Use Python data science libraries to analyze real-world datasets - Use pandas to solve common data representation and analysis problems - Build Python scripts, modules, and packages for reusable analysis code - Perform efficient data analysis and manipulation tasks using pandas - Apply pandas to different real-world domains with the help of step-by-step demonstrations - Get accustomed to using pandas as an effective data exploration tool.


Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. NOTE: Students heading into real project work right after training might consider a more robust hands-on course with deeper topics and lab coverage for similar subjects, such as the TTPS4873 JumpStart to Python for Data Science


This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets.

Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice
Additional course details:

Nexus Humans Hands-on Data Analysis with Pandas (TTPS4878) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward.

This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts.

Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.

While we feel this is the best course for the ITS Data Analytics course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.

Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Training Insurance Included!

When you organise training, we understand that there is a risk that some people may fall ill, become unavailable. To mitigate the risk we include training insurance for each delegate enrolled on our public schedule, they are welcome to sit on the same Public class within 6 months at no charge, if the case arises.

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Global Schedule

GTR = Guarenteed to Run

08 Jul 24 Enquire Book
15:00 - 23:00Live Online2
09 Oct 24 Enquire Book
15:00 - 23:00Live Online2

20 May 24 Enquire Book
15:00 - 23:00Live Online1
26 Aug 24 Enquire Book
15:00 - 23:00Live Online2
18 Nov 24 Enquire Book
15:00 - 23:00Live Online2

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