dataset https://dataset.readthedocs.org/en/latest/ is pretty good and for most scenarios as easy as tinydb, but backed by a real SQL database.
I've used this with a Flask project before, great module and super easy.
Lesser-Known Python Data Analysis Libraries
51–60 of 69 posts
Re: Lesser-Known Python Data Analysis Libraries
#52My 2 cents: I would not recommend basing any new work on MRjob. As someone who inherited and has been maintaining a bunch of code that depends on it, the library seems to be barely maintained, support for VPC is only partial and not very well documented, the auditing tools stopped working quite a while ago and tracking the progress/status of EMR jobs is extremely painful (to be fair, this is more of an issue with Ela…
I have the opposite experience with MrJob. Classifying it as an inactive project is demonstrably false. The rest are EMR complaints, I use it on my own Hadoop cluster.
Re: Lesser-Known Python Data Analysis Libraries
#53Vincent has not been properly maintained in a year. and is broken at this point since the release of Vega 2.0
Yes, this recommendation puzzled me. It's essentially a dead project.
"Vincent is essetially frozen for development right now, and has been for quite a while. The features for the currently targeted version of Vega (1.4) work fine, but it will not work with Vega 2.x releases. Regarding a rewrite, I'm honestly not sure if it's worth the time and effort at this point."
Re: Lesser-Known Python Data Analysis Libraries
#54I'll have to check delorean out, I usually use http://crsmithdev.com/arrow/ for python date manipulation. It works a lot like the javascript library moment.
cool, let me know if you have any issues. sanx.
Re: Lesser-Known Python Data Analysis Libraries
#55Earlier quoted context omitted.
Perhaps I should have been more clear. I want to present the results in pdf or html. Like xtables, tables and stargazer packages in R.
I haven't used xtables or stargazer in a while, but ipython + pandas can display tables as html. Here is an interesting ipython notebook with some examples: http://nbviewer.jupyter.org/gist/chris1610/f2f4a2e9181f6ec22...
Oooo, I'm going to have to look at that qgrid widget. I've been frustrated when I had to dump a df (DataFrame) to Excel to browse a large df.
Re: Lesser-Known Python Data Analysis Libraries
#56https://github.com/turicas/rows also worths a mention.
Re: Lesser-Known Python Data Analysis Libraries
#57plotly is a fantastic tool for plotting. It has a python API [0], but also works from R, matlab, and Julia. It also has support for pandas dataframes and jupyter notebook[1], which is by far the fastest way I've found to make attractive plots. plotlyjs[2] is a fantastic wrapper around d3. So I can go all the way from plotting something quickly from a dataframe to building a totally custom chart. [0] https://plot.ly/p…
I like plotly as well but I couldn't stand the python api nor cufflinks for that matter so I created my own wrapper. It's not fully featured but it handles 90% of the cases I want. https://github.com/jwkvam/plotlywrapper
very nice. I like that it each chart method returns the figure, so if it is needed to do something you didn't implement the figure is available to edit.
Re: Lesser-Known Python Data Analysis Libraries
#58Earlier quoted context omitted.
What's wrong with using Pandas? http://pandas.pydata.org/pandas-docs/version/0.17.0/generate...
Perhaps I should have been more clear. I want to present the results in pdf or html. Like xtables, tables and stargazer packages in R.
You can easily export any pandas DataFrame to html using the to_html() method. To generate full webpage, you'll probably want a templating engine like Jinja2.
The best demo I've seen for generating a PDF report is on Practical Business Python[1]
Edit: I forgot to mention the new pandas Style[1] feature for generating some impressive looking html tables.
Re: Lesser-Known Python Data Analysis Libraries
#59Earlier quoted context omitted.
I like plotly as well but I couldn't stand the python api nor cufflinks for that matter so I created my own wrapper. It's not fully featured but it handles 90% of the cases I want. https://github.com/jwkvam/plotlywrapper
very nice. I like that it each chart method returns the figure, so if it is needed to do something you didn't implement the figure is available to edit.
Thanks, I am happy to accept PRs that expose more functionality.
Re: Lesser-Known Python Data Analysis Libraries
#60Earlier quoted context omitted.
That is a neat trick, but it would be incredibly brittle. Kids, don't try this at home!
Pass in an re.match or re.search based function, i would imagine that would be powerful enough to meet most needs. import re x = ['foo12901','fooo900','fooooooo980090'] x =sorted(x,key = lambdax:int(re.search('\d+',x).group())) print(x)
+1 this is the right way to build a custom sorting function. The only thing worse than relying on ad-hoc heuristics for processing your data is relying on heuristics that somebody else maintains!