Course Content
Gaining Insights with Data Visualization
Gaining Insights with Data Visualization
Heat Maps
Heatmaps are graphical representations of data where the individual values contained in a matrix are represented as colors. The color scale used in the heatmap indicates the magnitude of the values at each position in the matrix.
Heatmaps are often used to visualize patterns and correlations in data. For example, a heatmap could illustrate the relationship between two variables, such as temperature and humidity in a given location over time. It might show that as the temperature increases, the humidity also tends to increase, indicating a strong correlation between the two variables.
Additionally, heatmaps can be tailored with various color scales to enhance visual clarity and highlight specific trends more effectively.
Task
- Create a DataFrame with the following columns: 'a', 'b', 'c', 'd', 'e'.
- Use the appropriate function to create a heatmap.
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Heatmaps are graphical representations of data where the individual values contained in a matrix are represented as colors. The color scale used in the heatmap indicates the magnitude of the values at each position in the matrix.
Heatmaps are often used to visualize patterns and correlations in data. For example, a heatmap could illustrate the relationship between two variables, such as temperature and humidity in a given location over time. It might show that as the temperature increases, the humidity also tends to increase, indicating a strong correlation between the two variables.
Additionally, heatmaps can be tailored with various color scales to enhance visual clarity and highlight specific trends more effectively.
Task
- Create a DataFrame with the following columns: 'a', 'b', 'c', 'd', 'e'.
- Use the appropriate function to create a heatmap.
Switch to desktop for real-world practiceContinue from where you are using one of the options below