Exploratory data analysis of text
Exploratory Data Analysis (EDA) is a crucial step in any data science project. When it comes to text data, EDA can help us understand the structure and characteristics of the data, identify potential issues or inconsistencies, and inform our choice of data preprocessing and modeling techniques. In this section, we will walk through the steps involved in performing EDA on text data.
Loading the data
The first step in EDA is to load the text data into our environment. Text data can come in many formats, including plain text files, CSV files, or database tables. Once we have the data loaded, we can begin to explore its structure and content.
Understanding the data
The next step in EDA is to gain an understanding of the data. For text data, this may involve examining the size of the dataset, the number of documents or samples, and the overall structure of the text (e.g., whether it is structured or unstructured). We can use descriptive statistics...
