Explored Data Manipulation and Visualization Techniques

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📅 2023-07-13 — Session: Explored Data Manipulation and Visualization Techniques

🕒 23:05–23:45
🏷️ Labels: Python, Pandas, Data Visualization, Clustering, Data Manipulation
📂 Project: Dev

Session Goal

The goal of this session was to explore various data manipulation and visualization techniques using Python, specifically focusing on pandas and [[data visualization]] libraries like Seaborn and Matplotlib.

Key Activities

  • DataFrame Conversion: Learned how to convert a MultiIndex DataFrame to a regular DataFrame using reset_index and to_frame methods.
  • Data Reshaping: Utilized pivot_table() and unstack() methods for reshaping data from long to wide formats.
  • Correlation Matrix Visualization: Created correlation matrix heatmaps using Seaborn and Matplotlib, and explored transposing matrices for visualization.
  • Hierarchical Clustering: Implemented hierarchical clustering on a correlation matrix, including visualization with dendrograms and PCA.
  • Data Concatenation: Demonstrated concatenating DataFrame columns into a single string using pandas apply function.

Achievements

  • Successfully implemented various data manipulation techniques to reshape and visualize data.
  • Enhanced understanding of hierarchical clustering and PCA for exploratory data analysis.

Pending Tasks

  • Further exploration of dimensionality reduction techniques and their applications in different datasets.
  • Investigate additional [[data visualization]] methods for complex datasets.

Graph View

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