WebJan 3, 2024 · np.diagonal works for arrays with more than two dimensions, which you can specify the axis to look at with parameters axis1 and axis2, for your case, the default (axis1=0, axis2=1) works: np.diagonal(a, axis1=0, axis2=1).T # array([[1, 2], # [7, 8]]) It also works for arrays that have different sizes on the two axis looked at: WebAt Diagonal, we believe in using open data to inform the place-making process because we know it brings value to projects, communities impacted by a project, and future projects. That’s why we are passionate about demonstrating why open data should be the starting point for all transparent data-gathering endeavours. A useful open data source
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WebIf you have a project where you think analytics could help make better decisions, and you are keen to co-create algorithms that derive from your domain expertise, and develop visualisations that let you explore the possibilities, get in touch: [email protected]. Simona September 2024 WebFind company research, competitor information, contact details & financial data for DIAGONAL WORKS LTD of THAME. Get the latest business insights from Dun & … WebOct 11, 2024 · I had this problem too but solved it when I realised that np.fill_diagonal() works in-place.. np.fill_diagonal(df,0) gave me the AttributeError: you described and np.fill_diagonal(df.values,0) returns None so if you do something like: df_zeros = np.fill_diagonal(df.values,0) print(df_zeros) or try to use the result elsewhere it won't … greensprings west homeowners association