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A alternativa correta é C – Certo. Vamos entender o porquê disso. O módulo pyplot faz parte da biblioteca Matplotlib, que é uma das bibliotecas de visualização de dados mais populares e amplamente utilizadas na linguagem de programação Python. O módulo pyplot oferece uma interface que imita a do MATLAB, outra linguagem de programação muito usada por engenheiros e cientistas. Isso é útil porque muitos usuários vêm de um background onde o MATLAB é uma ferramenta padrão.
Com o módulo pyplot, é possível criar diversos tipos de gráficos, como linhas, barras, histogramas, gráficos de dispersão, entre outros. O estilo de comando mencionado no enunciado refere-se à maneira como essas funções são utilizadas: elas permitem ao usuário controlar aspectos como a criação de figuras, a definição de áreas de plotagem, a plotagem de linhas, a adição de rótulos, entre outros, tudo de maneira muito similar à chamada de funções.
Por exemplo, para gerar um gráfico de linha simples, você utilizaria comandos como plt.plot(x, y) seguido por plt.show(), onde plt é a convenção comum para a importação do módulo pyplot de Matplotlib. O primeiro comando cria o gráfico com os dados fornecidos, enquanto o segundo exibe o gráfico para o usuário.
Portanto, a afirmação de que o módulo pyplot da biblioteca Matplotlib é um conjunto de funções de estilo de comando que permitem que gráficos sejam gerados está correta, e essa é uma das funcionalidades mais básicas e essenciais do Matplotlib para a visualização de dados em Python.