Concept Creative gives back to the open-source community by sharing our tools and expertise.
One part literature and one part software, our tools help us make better decisions on the web.
Analyze search terms and identify those words and phrases that are most important.
> python analyze.py --help usage: analyze.py [-h] [--skip-lines SKIP_LINES] [--drop-lines DROP_LINES] [--column COLUMN] [--weight WEIGHT] [--ngram-size NGRAM_SIZE] [--display DISPLAY] filename Ngram Analyzer positional arguments: filename optional arguments: -h, --help show this help message and exit --skip-lines SKIP_LINES number of lines to skip at the start of the file --drop-lines DROP_LINES number of lines to drop at the end of the file --column COLUMN name of the search term column --weight WEIGHT name of the column by which to weight terms --ngram-size NGRAM_SIZE size of the ngram --display DISPLAY number of ngrams to display
What link directories are most important? Use Google and SeoMoz to answer that question.
Though it can be complex to automate the process, the results are well worth it:
Rather than listen to so-called experts in SEO, this process tells you which link directories matter most. The results will surprise you!
Parsingwordswithoutspacesishard, but domain names work like that. This is such an important problem that the Director of Research at Google published a billion-word corpus to help us out.
Installing WordSegment is simple with pip:
> pip install wordsegment
You can access documentation in the interpreter with Python’s built-in help function:
>>> import wordsegment >>> help(wordsegment)
In your own Python programs, you’ll mostly want to use segment to divide a phrase into a list of its parts:
>>> from wordsegment import segment >>> segment('thisisatest') ['this', 'is', 'a', 'test']
WordSegment also provides a command-line interface for batch processing. This interface accepts two arguments: in-file and out-file. Lines from in-file are segmented iteratively, joined by a space, and written to out-file. Input and output default to stdin and stdout respectively.
> echo thisisatest | python -m wordsegment this is a test
Web search auto-complete can tell you a lot about what people are looking for.
This project also includes notes on how to visualize the search queries in clusters.
usage: crawl_google_autocomplete.py [-h] [--query QUERY] [--prefix PREFIX] [--include INCLUDE] [--exclude EXCLUDE] filename Crawl Google Auto-Complete Query positional arguments: filename optional arguments: -h, --help show this help message and exit --query QUERY --prefix PREFIX --include INCLUDE --exclude EXCLUDE
Wish you could visualize ad variation by day? Use even more tools to slice and dice your data.
> python analyze.py --help usage: analyze.py [-h] [--adwords ADWORDS] [--adsense ADSENSE] [--print-col-names] [--interactive] Ad Network Statistics optional arguments: -h, --help show this help message and exit --adwords ADWORDS path to Google Adwords csv report --adsense ADSENSE path to Google Adsense csv report --print-col-names --interactive
Our most ambitious project yet. Question and answer deployed to the financial industry.
As this is a work in progress, more details are forthcoming.