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Java - Convert integer to string [duplicate]

... String.valueOf(number) (my preference) "" + number (I don't know how the compiler handles it, perhaps it is as efficient as the above) Integer.toString(number) share | improve this answer ...
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Truststore and Keystore Definitions

...e or trustStore by using any key management utility e.g. keytool. Source: http://javarevisited.blogspot.ch share | improve this answer | follow | ...
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Python set to list

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A gentle tutorial to Emacs/Swank/Paredit for Clojure

... There is one more excelent tutorial: http://www.braveclojure.com/basic-emacs/ (1st part) http://www.braveclojure.com/using-emacs-with-clojure/ (2nd part) In 30 to 45 minutes one can have everything setup from scratch. The tutorial does not assumes any prior k...
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Assign pandas dataframe column dtypes

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Is String.Format as efficient as StringBuilder

...t a proper comparison. This chap, Jerry Dixon, did some benchmarking: http://jdixon.dotnetdevelopersjournal.com/string_concatenation_stringbuilder_and_stringformat.htm Updated: Sadly the link above has since died. However there's still a copy on the Way Back Machine: http://web.archive.o...
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Placement of the ng-app directive (html vs body)

...at all, unless you have a very very bulky DOM. If you want examples here: http://noypi-linux.blogspot.com/2014/07/angularjs-tutorials-understanding.html share | improve this answer | ...
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How to add Google Analytics Tracking ID to GitHub Pages

... Browse to your github pages branch - which would be something like - ( https://github.com/YourUserName/YourRepository/tree/gh-pages ) Then edit index.html from listed files Now in within HEAD tag of index.html - paste your Google Analytics Tracking ID Script ( if have already signed up for Goog...
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How to remove all white spaces in java [duplicate]

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Is there a numpy builtin to reject outliers from a list

...ee that the 90% percentile corresponds to 1.2815σ and the 95% is 1.645σ (http://vassarstats.net/tabs.html?#z) As a simple example: import numpy as np # Create some random numbers x = np.random.normal(5, 2, 1000) # Calculate the statistics print("Mean= ", np.mean(x)) print("Median= ", np.median...