Data Analysis and Visualization using Python Libraries and Streamlit Training Logo

Data Analysis and Visualization using Python Libraries and Streamlit Training

Live Online & Classroom Enterprise Training

Data Analysis and Visualization using Python and Streamlit covers data processing with libraries like Pandas, NumPy, and Matplotlib, alongside interactive web app development with Streamlit. It enables users to create dynamic, shareable data dashboards with minimal coding.

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What is Data Analysis and Visualization using Python Libraries and Streamlit Training about?

This course provides hands-on training in data analysis and visualization using Python’s powerful libraries, including Pandas, Matplotlib, Seaborn, and Plotly. Participants will also learn how to build interactive web applications for data visualization using Streamlit, enabling them to present insights effectively. 

What are the objectives of Data Analysis and Visualization using Python Libraries and Streamlit Training ?

  • Perform data manipulation and analysis using Pandas.
  • Create static and interactive visualizations using Matplotlib, Seaborn, and Plotly.
  • Develop interactive data dashboards using Streamlit.
  • Process and clean datasets for effective visualization.
  • Deploy Streamlit apps for real-time data interaction.
  • Use advanced visualization techniques to communicate insights.

Who is Data Analysis and Visualization using Python Libraries and Streamlit Training for?

  • Data analysts and scientists
  • Python developers interested in data visualization
  • Business professionals and decision-makers
  • Researchers and students working with data 

What are the prerequisites for Data Analysis and Visualization using Python Libraries and Streamlit Training?

  • Basic understanding of Python programming
  • Familiarity with fundamental statistics and data concepts is beneficial

Available Training Modes

Live Online Training

2 Days

Self-Paced Training

20 Hours

Course Outline Expand All

Expand All

  • Overview of data analysis and visualization
  • Introduction to Pandas for data manipulation
  • Handling missing data and data preprocessing
  • Creating static visualizations with Matplotlib
  • Enhancing visual aesthetics using Seaborn
  • Customizing plots and working with different chart types
  • Introduction to Plotly for interactive charts
  • Building dynamic visualizations with hover effects
  • Creating animated and multi-dimensional plots
  • Setting up a Streamlit environment
  • Creating a simple Streamlit application
  • Adding widgets and interactive elements
  • Connecting data sources to Streamlit
  • Implementing user-driven filters and selectors
  • Deploying Streamlit apps on cloud platforms
  • Time series analysis and visualization
  • Geospatial visualizations with Folium and Plotly
  • Case study: Building a complete data analysis and visualization project
  • Integrating Streamlit with machine learning models
  • Deploying Streamlit applications on AWS, Heroku, or Streamlit Cloud
  • Best practices for performance optimization

Who is the instructor for this training?

The trainer for this Data Analysis and Visualization using Python Libraries and Streamlit Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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