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Building an Environmental Metrics Dashboard in R Using Shiny

  In today's data-driven world, tracking environmental indicators such as CO2 emissions, renewable energy consumption, and energy use is essential for understanding and addressing global challenges. This blog walks you through building an   Environmental Metrics Dashboard   in R using the   Shiny   framework, enabling users to visualize and compare these critical indicators across multiple countries over time. Why Build an Environmental Metrics Dashboard? Environmental data, such as CO2 emissions per capita and renewable energy consumption, provide invaluable insights into a country's progress toward sustainability. By visualizing these metrics interactively, stakeholders and decision-makers can identify trends, compare countries, and focus on actionable solutions. The dashboard we’ll create allows users to: Compare multiple countries across key environmental metrics. Explore trends over time. Customize visualizations with a user-friendly interface. Key Componen...
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Medical Data Set Clustering Analysis Using R-Programming

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   Medical Data Set Clustering Analysis Using       R-Programming By Bharani Dharan N  CB.BU.P2ASB23046 1 . Importing Libraries import pandas as pd import numpy as np from sklearn.cluster import KMeans from sklearn.preprocessing import MinMaxScaler import matplotlib.pyplot as plt from sklearn.impute import SimpleImputer from sklearn.preprocessing import FunctionTransformer from sklearn.pipeline import Pipeline from sklearn.compose import ColumnTransformer from sklearn.base import BaseEstimator, TransformerMixin from sklearn.decomposition import PCA from sklearn.metrics import silhouette_score from sklearn.cluster import AgglomerativeClustering from sklearn_extra.cluster import KMedoids Explanation : This code snippet outlines a data preparation and clustering analysis pipeline. We leverage pandas for data loading and cleaning tasks. Missing values are handled using scikit-learn's SimpleImputer. Feature scaling for improved clustering distance calculat...
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