Steps involved in Data Exploration
Data exploration is an iterative process, but there are generally some key steps involved:
Data Understanding
- Familiarization: Get an overview of the data format, size, and source.
- Variable Identification: Understand the meaning and purpose of each variable in the dataset.
Data Cleaning
- Identifying Missing Values: Locate and address missing data points strategically (e.g., removal, imputation).
- Error Correction: Find and rectify any inconsistencies or errors within the data.
- Outlier Treatment: Identify and decide how to handle outliers that might skew the analysis.
- Univariate Analysis: Analyze individual variables to understand their distribution (e.g., histograms, boxplots for numerical variables; frequency tables for categorical variables).
- Bivariate Analysis: Explore relationships between two variables using techniques like scatterplots to identify potential correlations.
Data Visualization
- Creating Visualizations: Use charts and graphs (bar charts, line charts, heatmaps) to effectively communicate patterns and trends within the data.
- Choosing the Right Charts: Select visualizations that best suit the type of data and the insights you’re looking for.
Iteration and Refinement
- Iterate: As you explore, you may need to revisit previous steps.
- Refinement: New discoveries might prompt you to clean further, analyze differently, or create new visualizations.
What is Data Exploration and its process?
Data exploration is the first step in the journey of extracting insights from raw datasets. Data exploration serves as the compass that guides data scientists through the vast sea of information. It involves getting to know the data intimately, understanding its structure, and uncovering valuable nuggets that lay hidden beneath the surface.
In this article, we will delve into the importance of Data Exploration and the key techniques used in this process of data cleaning to build of model.
Table of Content
- What is Data Exploration?
- Significance of Understanding Data Exploration
- How Data Exploration Works?
- Steps involved in Data Exploration
- Importance of Data Exploration
- Example of Data Exploration
- Benefits of Data Exploration
- Applications of Data Exploration
- Conclusion
- What is Data Exploration – FAQs