can you apply K-Means clustering, elbow curve and silhouette score on scaled data for the below dataset and determine optimum clusters.

Data set

spending advance_payments probability_of_full_payment current_balance credit_limit min_payment_amt max_spent_in_single_shopping 19.94 16.92 0.8752 6.675 3.763 3.252 6.55 15.99 14.89 0.9064 5.363 3.582 3.336 5.144 18.95 16.42 0.8829 6.248 3.755 3.368 6.148 10.83 12.96 0.8099 5.278 2.641 5.182 5.185 17.99 15.86 0.8992 5.89 3.694 2.068 5.837 12.7 13.41 0.8874 5.183 3.091 8.456 5 12.02 13.33 0.8503 5.35 2.81 4.271 5.308 13.74 14.05 0.8744 5.482 3.114 2.932 4.825 18.17 16.26 0.8637 6.271 3.512 2.853 6.273 11.23 12.88 0.8511 5.14 2.795 4.325 5.003 18.55 16.22 0.8865 6.153 3.674 1.738 5.894 14.09 14.41 0.8529 5.717 3.186 3.92 5.299 12.15 13.45 0.8443 5.417 2.837 3.638 5.338 18.98 16.57 0.8687 6.449 3.552 2.144 6.453 12.1 13.15 0.8793 5.105 2.941 2.201 5.056 12.79 13.53 0.8786 5.224 3.054 5.483 4.958 16.14 14.99 0.9034 5.658 3.562 1.355 5.175 10.8 12.57 0.859 4.981 2.821 4.773 5.063 13.22 13.84 0.868 5.395 3.07 4.157 5.088 12.7 13.71 0.8491 5.386 2.911 3.26 5.316 12.37 13.47 0.8567 5.204 2.96 3.919 5.001 13.07 13.92 0.848 5.472 2.994 5.304 5.395 17.98 15.85 0.8993 5.979 3.687 2.257 5.919 12.62 13.67 0.8481 5.41 2.911 3.306 5.231 15.11 14.54 0.8986 5.579 3.462 3.128 5.18 15.56 14.89 0.8823 5.776 3.408 4.972 5.847 12.78 13.57 0.8716 5.262 3.026 1.176 4.782 11.02 13 0.8189 5.325 2.701 6.735 5.163 11.35 13.12 0.8291 5.176 2.668 4.337 5.132 11.23 12.82 0.8594 5.089 2.821 7.524 4.957 13.78 14.06 0.8759 5.479 3.156 3.136 4.872 11.84 13.21 0.8521 5.175 2.836 3.598 5.044 12.55 13.57 0.8558 5.333 2.968 4.419 5.176 15.88 14.9 0.8988 5.618 3.507 0.7651 5.091 11.82 13.4 0.8274 5.314 2.777 4.471 5.178 11.19 13.05 0.8253 5.25 2.675 5.813 5.219 11.14 12.79 0.8558 5.011 2.794 6.388 5.049 12.22 13.32 0.8652 5.224 2.967 5.469 5.221 11.81 13.45 0.8198 5.413 2.716 4.898 5.352 19.51 16.71 0.878 6.366 3.801 2.962 6.185 18.72 16.34 0.881 6.219 3.684 2.188 6.097 13.84 13.94 0.8955 5.324 3.379 2.259 4.805 16.87 15.65 0.8648 6.139 3.463 3.696 5.967 20.03 16.9 0.8811 6.493 3.857 3.063 6.32 10.79 12.93 0.8107 5.317 2.648 5.462 5.194 11.18 12.72 0.868 5.009 2.81 4.051 4.828 13.16 13.82 0.8662 5.454 2.975 0.8551 5.056 19.06 16.45 0.8854 6.416 3.719 2.248 6.163 18.96 16.2 0.9077 6.051 3.897 4.334 5.75 18.83 16.29 0.8917 6.037 3.786 2.553 5.879 12.73 13.75 0.8458 5.412 2.882 3.533 5.067 18.72 16.19 0.8977 6.006 3.857 5.324 5.879 19.46 16.5 0.8985 6.113 3.892 4.308 6.009 19.38 16.72 0.8716 6.303 3.791 3.678 5.965 18.81 16.29 0.8906 6.272 3.693 3.237 6.053 16.23 15.18 0.885 5.872 3.472 3.769 5.922 12.38 13.44 0.8609 5.219 2.989 5.472 5.045 11.83 13.23 0.8496 5.263 2.84 5.195 5.307 10.93 12.8 0.839 5.046 2.717 5.398 5.045 18.65 16.41 0.8698 6.285 3.594 4.391 6.102 14.79 14.52 0.8819 5.545 3.291 2.704 5.111 11.41 12.95 0.856 5.09 2.775 4.957 4.825 11.27 12.97 0.8419 5.088 2.763 4.309 5 15.26 14.85 0.8696 5.714 3.242 4.543 5.314 14.34 14.37 0.8726 5.63 3.19 1.313 5.15 18.85 16.17 0.9056 6.152 3.806 2.843 6.2 20.71 17.23 0.8763 6.579 3.814 4.451 6.451 14.11 14.1 0.8911 5.42 3.302 2.7 5 19.15 16.45 0.889 6.245 3.815 3.084 6.185 12.19 13.2 0.8783 5.137 2.981 3.631 4.87 13.54 13.85 0.8871 5.348 3.156 2.587 5.178 12.49 13.46 0.8658 5.267 2.967 4.421 5.002 20.1 16.99 0.8746 6.581 3.785 1.955 6.449 20.2 16.89 0.8894 6.285 3.864 5.173 6.187 13.34 13.95 0.862 5.389 3.074 5.995 5.307 18.94 16.32 0.8942 6.144 3.825 2.908 5.949 15.03 14.77 0.8658 5.702 3.212 1.933 5.439 12.13 13.73 0.8081 5.394 2.745 4.825 5.22 16.82 15.51 0.8786 6.017 3.486 4.004 5.841 14.29 14.09 0.905 5.291 3.337 2.699 4.825 14.52 14.6 0.8557 5.741 3.113 1.481 5.487 12.88 13.5 0.8879 5.139 3.119 2.352 4.607 13.94 14.17 0.8728 5.585 3.15 2.124 5.012 18.59 16.05 0.9066 6.037 3.86 6.001 5.877 10.91 12.8 0.8372 5.088 2.675 4.179 4.956 14.49 14.61 0.8538 5.715 3.113 4.116 5.396 16.63 15.46 0.8747 6.053 3.465 2.04 5.877 15.38 14.9 0.8706 5.884 3.268 4.462 5.795 16.17 15.38 0.8588 5.762 3.387 4.286 5.703 13.2 13.66 0.8883 5.236 3.232 8.315 5.056 13.99 13.83 0.9183 5.119 3.383 5.234 4.781 21.18 17.21 0.8989 6.573 4.033 5.78 6.231 15.26 14.84 0.871 5.763 3.312 2.221 5.22 11.18 13.04 0.8266 5.22 2.693 3.332 5.001 11.87 13.02 0.8795 5.132 2.953 3.597 5.132 18.43 15.97 0.9077 5.98 3.771 2.984 5.905 19.57 16.74 0.8779 6.384 3.772 1.472 6.273 16.16 15.33 0.8644 5.845 3.395 4.266 5.795 10.82 12.83 0.8256 5.18 2.63 4.853 5.089 17.63 15.86 0.88 6.033 3.573 3.747 5.929 13.37 13.78 0.8849 5.32 3.128 4.67 5.091 19.31 16.59 0.8815 6.341 3.81 3.477 6.238 15.38 14.66 0.899 5.477 3.465 3.6 5.439 18.89 16.23 0.9008 6.227 3.769 3.639 5.966 15.69 14.75 0.9058 5.527 3.514 1.599 5.046 18.94 16.49 0.875 6.445 3.639 5.064 6.362 18.36 16.52 0.8452 6.666 3.485 4.933 6.448 13.32 13.94 0.8613 5.541 3.073 7.035 5.44 12.8 13.47 0.886 5.16 3.126 4.873 4.914 18.75 16.18 0.8999 6.111 3.869 4.188 5.992 15.6 15.11 0.858 5.832 3.286 2.725 5.752 14.33 14.28 0.8831 5.504 3.199 3.328 5.224 20.24 16.91 0.8897 6.315 3.962 5.901 6.188 12.89 13.77 0.8541 5.495 3.026 6.185 5.316 11.21 13.13 0.8167 5.279 2.687 6.169 5.275 17.32 15.91 0.8599 6.064 3.403 3.824 5.922 13.5 13.85 0.8852 5.351 3.158 2.249 5.176 14.28 14.17 0.8944 5.397 3.298 6.685 5.001 11.48 13.05 0.8473 5.18 2.758 5.876 5.002 20.97 17.25 0.8859 6.563 3.991 4.677 6.316 12.08 13.23 0.8664 5.099 2.936 1.415 4.961 11.56 13.31 0.8198 5.363 2.683 4.062 5.182 12.46 13.41 0.8706 5.236 3.017 4.987 5.147 12.54 13.67 0.8425 5.451 2.879 3.082 5.491 14.11 14.26 0.8722 5.52 3.168 2.688 5.219 15.01 14.76 0.8657 5.789 3.245 1.791 5.001 18.3 15.89 0.9108 5.979 3.755 2.837 5.962 11.4 13.08 0.8375 5.136 2.763 5.588 5.089 14.11 14.18 0.882 5.541 3.221 2.754 5.038 14.46 14.35 0.8818 5.388 3.377 2.802 5.044 11.36 13.05 0.8382 5.175 2.755 4.048 5.263 14.86 14.67 0.8676 5.678 3.258 2.129 5.351 12.36 13.19 0.8923 5.076 3.042 3.22 4.605 18.98 16.66 0.859 6.549 3.67 3.691 6.498 12.05 13.41 0.8416 5.267 2.847 4.988 5.046 17.63 15.98 0.8673 6.191 3.561 4.076 6.06 19.14 16.61 0.8722 6.259 3.737 6.682 6.053 11.27 12.86 0.8563 5.091 2.804 3.985 5.001 17.55 15.66 0.8991 5.791 3.69 5.366 5.661 14.59 14.28 0.8993 5.351 3.333 4.185 4.781 15.78 14.91 0.8923 5.674 3.434 5.593 5.136 14.92 14.43 0.9006 5.384 3.412 1.142 5.088 11.24 13 0.8359 5.09 2.715 3.521 5.088 11.34 12.87 0.8596 5.053 2.849 3.347 5.003 12.74 13.67 0.8564 5.395 2.956 2.504 4.869 12.19 13.36 0.8579 5.24 2.909 4.857 5.158 19.13 16.31 0.9035 6.183 3.902 2.109 5.924 10.74 12.73 0.8329 5.145 2.642 4.702 4.963 13.8 14.04 0.8794 5.376 3.155 1.56 4.961 12.44 13.59 0.8462 5.319 2.897 4.924 5.27 14.16 14.4 0.8584 5.658 3.129 3.072 5.176 12.11 13.27 0.8639 5.236 2.975 4.132 5.012 14.99 14.56 0.8883 5.57 3.377 2.958 5.175 16.2 15.27 0.8734 5.826 3.464 2.823 5.527 11.42 12.86 0.8683 5.008 2.85 2.7 4.607 14.7 14.21 0.9153 5.205 3.466 1.767 4.649 13.02 13.76 0.8641 5.395 3.026 3.373 4.825 11.26 13.01 0.8355 5.186 2.71 5.335 5.092 15.38 14.77 0.8857 5.662 3.419 1.999 5.222 17.36 15.76 0.8785 6.145 3.574 3.526 5.971 20.88 17.05 0.9031 6.45 4.032 5.016 6.321 12.72 13.57 0.8686 5.226 3.049 4.102 4.914 18.88 16.26 0.8969 6.084 3.764 1.649 6.109 17.26 15.73 0.8763 5.978 3.594 4.539 5.791 18.27 16.09 0.887 6.173 3.651 2.443 6.197 11.65 13.07 0.8575 5.108 2.85 5.209 5.135 15.5 14.86 0.882 5.877 3.396 4.711 5.528 15.05 14.68 0.8779 5.712 3.328 2.129 5.36 12.76 13.38 0.8964 5.073 3.155 2.828 4.83 11.43 13.13 0.8335 5.176 2.719 2.221 5.132 16.19 15.16 0.8849 5.833 3.421 0.903 5.307 11.49 13.22 0.8263 5.304 2.695 5.388 5.31 14.38 14.21 0.8951 5.386 3.312 2.462 4.956 18.45 16.12 0.8921 6.107 3.769 2.235 5.794 20.16 17.03 0.8735 6.513 3.773 1.91 6.185 19.11 16.26 0.9081 6.154 3.93 2.936 6.079 14.69 14.49 0.8799 5.563 3.259 3.586 5.219 12.21 13.47 0.8453 5.357 2.893 1.661 5.178 16.44 15.25 0.888 5.884 3.505 1.969 5.533 10.59 12.41 0.8648 4.899 2.787 4.975 4.794 14.37 14.39 0.8726 5.569 3.153 1.464 5.3 13.45 14.02 0.8604 5.516 3.065 3.531 5.097 12.67 13.32 0.8977 4.984 3.135 2.3 4.745 14.01 14.29 0.8625 5.609 3.158 2.217 5.132 17.12 15.55 0.8892 5.85 3.566 2.858 5.746 16.84 15.67 0.8623 5.998 3.484 4.675 5.877 12.11 13.47 0.8392 5.159 3.032 1.502 4.519 15.49 14.94 0.8724 5.757 3.371 3.412 5.228 13.16 13.55 0.9009 5.138 3.201 2.461 4.783 11.75 13.52 0.8082 5.444 2.678 4.378 5.31 11.23 12.63 0.884 4.902 2.879 2.269 4.703 14.43 14.4 0.8751 5.585 3.272 3.975 5.144 12.26 13.6 0.8333 5.408 2.833 4.756 5.36 18.14 16.12 0.8772 6.059 3.563 3.619 6.011 15.36 14.76 0.8861 5.701 3.393 1.367 5.132 16.53 15.34 0.8823 5.875 3.467 5.532 5.88 18.76 16.2 0.8984 6.172 3.796 3.12 6.053 12.3 13.34 0.8684 5.243 2.974 5.637 5.063 19.18 16.63 0.8717 6.369 3.681 3.357 6.229 12.01 13.52 0.8249 5.405 2.776 6.992 5.27 14.88 14.57 0.8811 5.554 3.333 1.018 4.956 17.08 15.38 0.9079 5.832 3.683 2.956 5.484 14.8 14.52 0.8823 5.656 3.288 3.112 5.309 11.55 13.1 0.8455 5.167 2.845 6.715 4.956 16.41 15.25 0.8866 5.718 3.525 4.217 5.618 13.89 14.02 0.888 5.439 3.199 3.986 4.738 16.77 15.62 0.8638 5.927 3.438 4.92 5.795 14.03 14.16 0.8796 5.438 3.201 1.717 5.001 16.12 15 0.9 5.709 3.485 2.27 5.443 15.57 15.15 0.8527 5.92 3.231 2.64 5.879