Скачать или смотреть How to Easily Convert .fits Files to Pandas DataFrames and Vice Versa

Discover the straightforward process for converting `.fits` files to Pandas DataFrames and back, making your data processing tasks effortless.
---
This video is based on the question https://stackoverflow.com/q/71142383/ asked by the user 'NeStack' ( https://stackoverflow.com/u/5838180/ ) and on the answer https://stackoverflow.com/a/71142384/ provided by the user 'NeStack' ( https://stackoverflow.com/u/5838180/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: How to convert .fits file/ astropy table to pandas df and reverse?

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
How to Easily Convert .fits Files to Pandas DataFrames and Vice Versa

Managing data across different formats can often be a cumbersome task, especially when you frequently need to switch between file types to meet your processing needs. If you've ever found yourself needing to convert .fits files to Pandas DataFrames or vice versa, you are not alone. This article will provide a clear, step-by-step solution that will make this conversion seamless for you.

Understanding the Formats

Before diving into the conversion process, it's important to understand what each format represents:

FITS (.fits): The Flexible Image Transport System is a format used for storing astronomical data. It is commonly used in scientific computing, especially in the field of astronomy.

Pandas DataFrame: This is a 2-dimensional, size-mutable, and potentially heterogeneous tabular data structure with labeled axes, which is a part of the Pandas library in Python. It is extensively used for data manipulation and analysis.

Converting Pandas DataFrames to .fits Files

To convert a Pandas DataFrame to a .fits file, follow these simple steps:

Import the Required Libraries:
You will need both Astropy (for handling .fits files) and Pandas. Make sure they are installed in your Python environment.

[[See Video to Reveal this Text or Code Snippet]]

Read Your Data into a Pandas DataFrame:
Utilize Pandas to read in your data from a source like a CSV or ASCII file.

[[See Video to Reveal this Text or Code Snippet]]

Convert and Save:
Convert the DataFrame to an Astropy Table and then write it to a .fits file.

[[See Video to Reveal this Text or Code Snippet]]

Converting .fits Files to Pandas DataFrames

If you have a .fits file that you want to convert into a Pandas DataFrame, here’s how to do it:

Import the Required Libraries:
Just like before, make sure you have the Astropy and Pandas libraries imported.

[[See Video to Reveal this Text or Code Snippet]]

Read the .fits File:
Use the Astropy Table module to read your .fits file.

[[See Video to Reveal this Text or Code Snippet]]

Convert to DataFrame:
Finally, convert the Astropy Table into a Pandas DataFrame.

[[See Video to Reveal this Text or Code Snippet]]

Directly Converting ASCII Files to .fits

You can also bypass the Pandas DataFrame altogether by reading an ASCII file directly into an Astropy Table and saving it as a .fits file. Follow these steps:

Read the ASCII File:
This will read your ASCII data into an Astropy Table without needing an intermediate DataFrame.

[[See Video to Reveal this Text or Code Snippet]]

Save the Table:
Write the table to a .fits file.

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

Being able to convert .fits files into Pandas DataFrames and back is a useful skill, especially in the realm of data analysis and scientific research. With the steps detailed above, you can now handle your data conversions easily and efficiently. Whether you're processing astronomical data or managing a dataset, these straightforward commands can save you time and enhance your workflow.

Feel free to reach out with any questions or further assistance regarding data processing with Pandas and Astropy!