I have done character position frequency analysis given the assumption that each line is a single word. If what Mach10 said was valid than there should still be a majority of accuracy in the frequency data. The fringe character values should all remain relatively stable in terms of lining up to generalized frequency analysis datasets. The further into a word you go the less grammatical rules letters have to follow and the more evenly the spread out the data will become. This means if there are positional character substitutions you will have difficulty in tracking which letters are being swapped the most. This is reflected not only in the Top chart but also the data from Column 1,2 and 3. The further in you go to the right the less accurate the data appears:
Then there is the overall Character Analysis:
---Character Type Count---
Lower Case Count: 245
Upper Case Count: 61
Number Count : 22
Whitespace Count: 4
Total Letters : 306
---Letter Only Frequency--
Char [A]:34
Calculated Frequency: 11.11111068725586%
English Standard FRQ: 8.2
Char :4
Calculated Frequency: 1.3071895837783813%
English Standard FRQ: 1.5
Char [C]:13
Calculated Frequency: 4.248365879058838%
English Standard FRQ: 2.8
Char [D]:8
Calculated Frequency: 2.6143791675567627%
English Standard FRQ: 4.3
Char [E]:30
Calculated Frequency: 9.803921699523926%
English Standard FRQ: 12.7
Char [F]:4
Calculated Frequency: 1.3071895837783813%
English Standard FRQ: 2.2
Char [G]:2
Calculated Frequency: 0.6535947918891907%
English Standard FRQ: 2.0
Char [H]:10
Calculated Frequency: 3.2679738998413086%
English Standard FRQ: 6.1
Char
:34
Calculated Frequency: 11.11111068725586%
English Standard FRQ: 7.0
Char [J]:0
Calculated Frequency: 0.0%
English Standard FRQ: 0.2
Char [K]:3
Calculated Frequency: 0.9803921580314636%
English Standard FRQ: 0.8
Char [L]:15
Calculated Frequency: 4.901960849761963%
English Standard FRQ: 4.0
Char [M]:11
Calculated Frequency: 3.594771146774292%
English Standard FRQ: 2.4
Char [N]:17
Calculated Frequency: 5.55555534362793%
English Standard FRQ: 6.7
Char [O]:18
Calculated Frequency: 5.882352828979492%
English Standard FRQ: 7.5
Char [P]:9
Calculated Frequency: 2.941176414489746%
English Standard FRQ: 1.9
Char [Q]:2
Calculated Frequency: 0.6535947918891907%
English Standard FRQ: 0.1
Char [R]:22
Calculated Frequency: 7.189542293548584%
English Standard FRQ: 6.0
Char :18
Calculated Frequency: 5.882352828979492%
English Standard FRQ: 6.3
Char [T]:22
Calculated Frequency: 7.189542293548584%
English Standard FRQ: 9.1
Char :15
Calculated Frequency: 4.901960849761963%
English Standard FRQ: 2.8
Char [V]:3
Calculated Frequency: 0.9803921580314636%
English Standard FRQ: 1.0
Char [W]:3
Calculated Frequency: 0.9803921580314636%
English Standard FRQ: 2.4
Char [X]:3
Calculated Frequency: 0.9803921580314636%
English Standard FRQ: 0.2
Char [Y]:5
Calculated Frequency: 1.6339869499206543%
English Standard FRQ: 2.0
Char [Z]:1
Calculated Frequency: 0.32679739594459534%
English Standard FRQ: 0.1
As you can see the overall character analysis seems to reflect the data being relatively close to what you'd expect to see. Granted the sample is much smaller so it lowers the confidence level of the data. However, ignoring sample size two assumptions can be made: A) Columns do not display the correct frequency data you'd expect to see for certain character in the given positions. B) Overall frequency data seems to indicate that this is not a cipher that includes substitution of characters, and or deletion of characters. Thus we can ultimately determine that characters are spread across the data set and as a result are not in their proper positions. I am now ever more convinced this is a transpositional obfuscation/cipher of some kind. There is always the possibility Drew did this intentionally to throw us off.
-Void
More character frequency positional analysis information can be found here:
https://norvig.com/mayzner.html