Contest Analysis

So you have stayed up for a long time, sat in a chair for a long time, endured hours of QRM, the same station who keeps calling you.. and it is over....

But do you ever go and have a look - no a proper look at how you operated ??

Before, we go much further there are a few slight warnings

• This assumes you are a competent programmer
• This assumes you can understand Python and the Pandas Framework

If you do not feel confident with trying this - there are a few commercial packages to assist you.

• SH5

There may be others - but this is the only one I have seen.

Basics

We need to understand one fundamental data files before we can proceed.

• CTY.DAT
  • This is the general 'definition' of a callsign
  • CTY.dat understanding
• Cabrillo Format
  • We need to Parse/Read this type of Ham Radio generated file
  • Cabrillo format reading

Intermediate

With the ability to read the basic data files, we now can start to develop a framework - so we can look at the contest data.

• Loading Data
  • For this we will read
  • CTY.DAT
  • Contest_XXX_2022.cbr, a Cabrillo format file

Load the Cabrillo file as 1 DataFrame, then parse and load the CTY data.

We now need to lookup each callsign - to extract

• DX Country
• Continent

You probably also need to convert

• Frequency to Band

At this point you can start asking questions such as

• Which country did I contact the most ?
  • Is this a good thing or not ??.. Your input needed !
• At what time did I hear ... you maybe should make some note for the next contest.
• What time was I
  • most productive ?
  • least productive ?

If you are skilled enough - I strongly suggest you have a look a heatmap with plotly as well and Geo-overlaying data into them.