This tutorial teaches how to use string methods and regular expression to pre-processing including cleaning up the list, converting to lower case and finding sepcific information. 

This tutorial is divided into 6 parts; they are:

  1. Metamorphosis by Franz Kafka
  2. Text Cleaning is Task Specific
  3. Manual Tokenization
  4. Tokenization and Cleaning with NLTK
  5. Additional Text Cleaning Considerations
  6. Tips for Cleaning Text for Word Embedding

This tutorial is about how to chart time series data with line plots and categorical quantities with bar charts. How to summarize data distributions with histograms and box plots. How to summarize the relationship between variables with scatter plots.

The goal of text classification is to automatically classify the text documents into one or more defined categories. In this tutorial, the author will explain about the text classification and the step by step processing to implement it in python.

This tutorial will discuss different feature extraction methods, starting with some basic techniques which will lead into advanced Natural Language Processing techniques. It will also teach pre-processing of the text data in order to extract better features from clean data.

This tutorial is about the basic of python and working with text files to compute something interesting.The first set of tutorial designed to teach the basic programming knowledge of using python to analyze text data.The second set of tutorial the author compute the proportion of positive words in tweet after cleaning up the data a bit.The third set of tutorial expand the code written in the previous two, to explore the positive and negative sentiment of any set of text.

This recipe uses regular expressions (or Regex) to clean a text document. This recipe is based on the Using Regular Expressions to Clean a Text code.

This recipe will use regular expressions to clean up a webpage. This is useful if you want to carry out any meaningful textual analysis of the content in a web page. We can remove the html tags and other unnecessary textual elements with this method.

This recipe will show how to generate basic concordances of a word and showing it within a textual context. We will use "find and replace" strategy known as regular expressions in this approach. Regex, as it is also known is universal to most programming languages and is a well documented method of parsing text. This recipe is based on Jinman's cookbook.

Tokenization is the process of splitting a sentence or a chunk of text into its constituent parts. These “tokens” may be the letters, punctuation, words, or sentences. They could even be a combination of all these elements. This recipe was adapted from a Python Notebook written by Kynan Lee.