Análise Exploratória de Dados (EDA)
Exploratória Análise de Dados (EDA) is a crucial step in the processo de análise de dados, focusing on the initial investigation of conjuntos de dados to discover patterns, spot anomalies, test hypotheses, and check assumptions. EDA employs a variety of techniques, primarily graphical and quantitative methods, to provide insights into the structure and relationships within the data.
The main goal of EDA is to understand the underlying structure of the data, which can inform further modelagem estatística e na tomada de decisão. Técnicas usadas na EDA incluem:
- Estatísticas Descritivas: Summarizing data using measures such as mean, median, mode, range, and standard deviation.
- Visualização de Dados: Creating visual representations of data, such as histograms, scatter plots, box plots, and heatmaps, to identify trends and correlations.
- Limpeza de Dados: Identifying and handling missing values, outliers, and inconsistencies to prepare the data for analysis.
EDA is iterative and often leads to new questions or hypotheses about the data, guiding the analysis process. By conducting EDA, analysts can gain a deeper understanding of the data, which can help in selecting the appropriate técnicas estatísticas e modelos para análise adicional.
Em resumo, Análise Exploratória de Dados é uma prática essencial em ciência de dados and statistics that emphasizes the importance of understanding data before applying more complex methods.