Vizly: AI-powered data analysis

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Notebook

Book1.xlsx yearwise fdi, ex,im, forex.xlsx

Missing file

please perform the hierarchical cluster analysis

To perform hierarchical cluster analysis, we need to follow these steps:
  1. Data Preprocessing: Ensure the data is clean and suitable for clustering.
  2. Normalization: Normalize the data to ensure each feature contributes equally to the distance calculations.
  3. Distance Calculation: Compute the distance matrix.
  4. Clustering: Perform hierarchical clustering using an appropriate linkage method.
  5. Dendrogram: Visualize the dendrogram to interpret the clusters.
Let's start with data preprocessing and normalization.
The dendrogram above shows the hierarchical clustering of the data. Each merge in the dendrogram represents a cluster formed by combining two clusters or data points. The height of the merge indicates the distance or dissimilarity between the clusters being merged.
Key points to note:
  • The x-axis represents the years.
  • The y-axis represents the Euclidean distances between clusters.
  • The closer the merge is to the bottom of the plot, the more similar the clusters are.
You can choose a threshold to cut the dendrogram and decide the number of clusters.
Would you like to proceed with a specific number of clusters or explore further analysis? Feel free to ask any more questions you may have!

Vizly

AI-powered data analysis

Try for yourself