02/24/2024 Class 2

[edaraa2]

Early Insight from Textual Data

This document appears to be a guide or tutorial on exploring and analyzing textual data, likely focusing on speeches or transcripts. Here's a breakdown of the potential content within 500 words:

1. Accessing and Sampling Data (100 words)

   The guide likely covers how to open a text file containing the speeches using Python libraries like open() or pandas' read_csv() function.
   It might explain how to display a specific number of lines (count) from the file for initial inspection.

• Unlocking the Vault: Access and Preview

First up, we need to access the data file. Techniques vary depending on the format (CSV, text, etc.). Once open, we can choose to display a limited amount using "count" to get a feel for the data's structure without drowning in information

• Laying the Groundwork: Overview

Next, we gain a high-level understanding. This might involve identifying the types of text (articles, emails, speeches) and getting a sense of the overall volume.

• Measuring Up: Speech Length Analysis

For speech-like data, it's valuable to examine their length. We could find the average speech, identify the shortest and longest, or explore the distribution of lengths.

• Plugging the Leaks: Addressing Missing Data

Real-world data often has missing information. Here, we'll check for these gaps and develop strategies. This might involve removing entries with missing data, imputing values based on statistics, or flagging them for further investigation.

• Visualization with Charts

Data comes alive with visuals! Tools like bar charts, histograms, and box plots bring the data to life. Bar charts can showcase word or topic frequency. Histograms depict the distribution of speech lengths or other numerical features. Box plots reveal the median, spread, and potential outliers within the data.

• The Pre-Processing Pipeline

Before diving deeper, we'll establish a pre-processing pipeline. This pipeline prepares the data for further analysis by cleaning and transforming it.

Using the data set with below details
Speeches from the UN general assembly 1970 to 2016 Available from Kaggle.com (free)
Medium size: 7 columns, 7507 long speeches
Columns: Session, year, country, country_name, speaker, position, text

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