HTML – Text Fields

HTML – Text Fields


Text fields are encountered as forms. Those are processed with the help of a programming language, most of the times ASP, PERL or PHP.

Additional attributes that are used for formatting the text fields are:

  • size – to set the field size
  • value – to set a predefined value
  • maxlength – to set the maximum caracters nunmber that can be entered by the user


We will exemplify each of them.

HTML – The text field size

The size attribute establishes the text field’s length. The standard length of a text field is usually between 20-25 characters, but it can vary depending on the forms or the text field’s purpose.


<p><input type="text" size="5" /></p>

<p><input type="text" size="15" /></p>

<p><input type="text" size="25" /></p>


HTML – Another attribute is value

Using this attribute we will make possible the writing of the information in our fields, information which the user can erase or not. This application is quite useful, especially when a PHP script recognizes a visitor and keeps the options chosen by the user.


<p><input type="text" size="5" value="12345" /></p>

<p><input type="text" size="15" value="HTML text filed" /></p>

<p><input type="text" size="25" value="HTML Tutorials " /></p>


HTML – Maxlength

Maxlength is one of the most useful attributes of the text fields because it does not allow the user to type a bigger number of characters than intended.


<p><input type="text" size="5" maxlength="5" /></p>

<p><input type="text" size="15" maxlength="15" /></p>

<p><input type="text" size="25" maxlength="25" /></p>


In case you want to introduce more than 5, 15 and 25 characters in the above fields, this thing will not be possible because of the restriction applied by ‘maxlength’.


Python Example for Beginners

Two Machine Learning Fields

There are two sides to machine learning:

  • Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
  • Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.

Data Science Resources: Data Science Recipes and Applied Machine Learning Recipes

Introduction to Applied Machine Learning & Data Science for Beginners, Business Analysts, Students, Researchers and Freelancers with Python & R Codes @ Western Australian Center for Applied Machine Learning & Data Science (WACAMLDS) !!!

Latest end-to-end Learn by Coding Recipes in Project-Based Learning:

Applied Statistics with R for Beginners and Business Professionals

Data Science and Machine Learning Projects in Python: Tabular Data Analytics

Data Science and Machine Learning Projects in R: Tabular Data Analytics

Python Machine Learning & Data Science Recipes: Learn by Coding

R Machine Learning & Data Science Recipes: Learn by Coding

Comparing Different Machine Learning Algorithms in Python for Classification (FREE)

Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.  

Google –> SETScholars