Interesting post. Thanks for the data, doing a simple analysis here are the top 30 keywords:

1. django: 803
2. performance: 774
3. test: 662
4. elsewhere: 492
5. yahoo: 468
6. cache: 430
7. expire: 404
8. tutorial: 326
9. pro: 325
10. storage: 75
11. design: 73
12. admin: 72
13. schedule: 71
14. template: 69
15. model: 68
16. app: 65
17. registration: 65
18. engine: 62
19. search: 50
20. newsletter: 47
21. cms: 41
22. queryset: 41
23. ajax: 40
24. google: 39
25. blog: 38
26. forms: 35
27. jquery: 33
28. models: 32
29. request: 27
30. appengine: 24

Django at #1 is no surprise but it is a bit like searching google for google.

-2 is a bit odd. Looking at likes 1597 onwards explains why perfomance comes up so much. Although, it is commonly used all through the log, so maybe performance is a key concern/worry for people?

-4 and #5 not really sure why elsewhere and yahoo are coming up so much?

It'd be interesting to see this information against the useragent as I suspect some of the unusual things will be front annoying robots.

Oh and FWIW;

from string import punctuation
from operator import itemgetter

words = {}

words_gen = (word.strip(punctuation).lower() for line in open("queries.log")
                                             for word in line.split())
for word in words_gen:
    words[word] = words.get(word, 0) + 1

top_words = sorted(words.iteritems(), key=itemgetter(1), reverse=True)[:30]

for word, frequency in top_words:
    print "%s: %d" % (word, frequency)

Your counts are off. According to "grep -cE '\bdjango\b' queries.log" there are 858 queries with "django" as a keyword.

import codecs
import re

word_re = re.compile(r'\w+', re.UNICODE)
words = (word.lower() for line in codecs.open('queries.log', encoding='utf-8')
                      for word in word_re.findall(line))

stats = {}
for word in words:
    stats[word] = stats.get(word, 0) + 1

# ... etc...

Returns 861 occurences of "django". (Why not 858? "django" appears four times on one line.)

Yahoo and Elsewhere were suggested queries on a tutorial and on the GitHub blog, respectively.