Data Analysis and Visualization with Python
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This course is an introduction to Data Analysis & Visualization using Python. In this course you will get to know different libraries like numpy, pandas, matplotlib, seaborn, plotly, folium etc. and see how to use them to analyze a dataset. At the end of the course you will build an "Exploratory Data Analysis" project on a real-world data.
Numerical Computing with Numpy
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- Arrays, vectors, and matrices in Numpy
- Array operations, slicing, and broadcasting
- Reading from and writing to CSV files
Exploring Numpy Functions
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- Explore the Numpy documentation website
- Demonstrate usage 5 numpy array operations
- Publish a Jupyter notebook with explanations
Analyzing Tabular Data with Pandas
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- Querying, filtering, and sorting data frames
- Grouping and aggregation for data summarization
- Merging and joining data from multiple sources
Pandas Data Analysis Practice
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- Query and sort data from data frames
- Group, merge, and aggregate data frames
- Fix missing and invalid values in data
Visualization with Matplotlib & Seaborn
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- Basic visualizations with Matplotlib
- Advanced visualizations with Seaborn
- Tips for customizing and styling charts
Interactive Visualization with Plotly & Folium
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- Creating interactive graphs with Plotly
- Markers, 3D charts, and animation
- Plotting on maps using Folium
Data Analysis & Visualization Practice
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- Querying and filtering pandas data frames
- Static charts with Matplotlib & Seaborn
- Interactive charts with Plotly & Folium
Exploratory Data Analysis Case Study
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- Data preparation and cleaning with Pandas
- Open-ended exploratory analysis & visualization
- Asking and answering interesting questions
Project 2 - Exploratory Data Analysis
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- Find a large real-world dataset using online sources
- Clean, process & analyze dataset using Pandas
- Visualize the data, ask & answer relevant questions
Advanced Data Analysis Techniques Preview
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- Downloading and processing large datasets
- Categorical data and datatype-specific methods
- Dataframe concatenation, merging, and joins