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Clustering Demystified
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Clustering Demystified

Clustering Demystified

IntroductionImport Necessary Libraries and DataPreliminary AnalysisData PreparationDeclare Feature Vector and Target VariableConvert Categorical Variable into IntegersFeature ScalingK-Means Model with 2 ClustersCheck the QualityHow many Clusters?K-Means Model with 4 Clusters

Import Necessary Libraries and Data

Firstly, we need to import all necessary modules, upload the data, and visually examine it.

Modules and methods description

  • numpy (np): Essential for numerical computing and array operations;
  • pandas (pd):
    • read_csv(): Facilitates reading CSV files into DataFrame for data analysis;
    • DataFrame.head(): Offers a quick glimpse of the initial rows in the DataFrame.
  • matplotlib.pyplot (plt): Enables creating various types of plots for data visualization;
  • seaborn (sns): Enhances statistical data visualization based on matplotlib.

Tarea

  1. Import numpy, pandas, matplotlib.pyplot and seaborn (as np, pd, plt, and sns, respectively).
  2. Read the "Live.csv" file.
  3. Show the first 5 rows of the dataset.

Tarea

  1. Import numpy, pandas, matplotlib.pyplot and seaborn (as np, pd, plt, and sns, respectively).
  2. Read the "Live.csv" file.
  3. Show the first 5 rows of the dataset.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

Firstly, we need to import all necessary modules, upload the data, and visually examine it.

Modules and methods description

  • numpy (np): Essential for numerical computing and array operations;
  • pandas (pd):
    • read_csv(): Facilitates reading CSV files into DataFrame for data analysis;
    • DataFrame.head(): Offers a quick glimpse of the initial rows in the DataFrame.
  • matplotlib.pyplot (plt): Enables creating various types of plots for data visualization;
  • seaborn (sns): Enhances statistical data visualization based on matplotlib.

Tarea

  1. Import numpy, pandas, matplotlib.pyplot and seaborn (as np, pd, plt, and sns, respectively).
  2. Read the "Live.csv" file.
  3. Show the first 5 rows of the dataset.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
Sección 1. Capítulo 2
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