Text Data Reader Lifetime Deal $5.99

If you have been part of the data science (or any data!) industry, you would know the challenge of working with different data types. Different formats, different compression, different parsing on different systems – you could be quickly pulling your hair! Oh and I have not talked about the unstructured data or semi-structured data yet.

For any data scientist or data engineer, dealing with different formats can become a tedious task. In real-world, people rarely get neat tabular data. Thus, it is mandatory for any data scientist (or a data engineer) to be aware of different file formats, common challenges in handling them and the best / efficient ways to handle this data in real life.

A file format is a standard way in which information is encoded for storage in a file. First, the file format specifies whether the file is a binary or ASCII file. Second, it shows how the information is organized. For example, comma-separated values (CSV) file format stores tabular data in plain text.

To identify a file format, you can usually look at the file extension to get an idea. For example, a file saved with name “Data” in “CSV” format will appear as “Data.csv”. By noticing “.csv” extension we can clearly identify that it is a “CSV” file and data is stored in a tabular format.

Usually, the files you will come across will depend on the application you are building. For example, in an image processing system, you need image files as input and output. So you will mostly see files in jpeg, gif or png format.

As a data scientist, you need to understand the underlying structure of various file formats, their advantages and disadvantages. Unless you understand the underlying structure of the data, you will not be able to explore it. Also, at times you need to make decisions about how to store data.

Choosing the optimal file format for storing data can improve the performance of your models in data processing

Introducing Text Data Reader

Text Data Reader is an MS Windows desktop application for quick viewing and exporting organized text data such as .CSV or .TXT (catalogs for example) with different field separators to Excel format. Even you have data with millions of records, you can use split feature to export your data to a bunch of Excel files

Get Text Data Reader for only $5.95

You can use any field separator from this:

Also, Text Data Reader is integrated to Windows context menu for easy using:

If your data file is big enough you can split it into parts:

Size of parts you can adjust with Settings menu:

If your data have a headline you can set it as header: