Above is a clustergram/heatmap visualization of your input matrix. The rows and columns have been hierarchically clustered, using the Scipy library in Python, using cosine distance and average linkage. Red/blue cells in the matrix represent positive/negative values in your matrix. The visualization interactive (zoomable, reorderable, filterable) and shareable - the current URL is permanent and shareable.

Above is a similarity matrix of the columns in your input matrix. The cells in the matrix represent the similarity between columns, where red/blue represent positive/negative similarity (measured as 1 - cosine-distance). Similarity matrices offer a more detailed view of the similarities and differences between rows/columms, e.g. blue cells indicate data points that behave 'oppositely' and this can not be easily seen in a clustergram/heatmap view.

Above is a similarity matrix of the rows in your input matrix. The cells in the matrix represent the similarity between rows, where red/blue represent positive/negative similarity (measured as 1 - cosine-distance).