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How to get all of the immediate subdirectories in Python
... return the directory with the final slash (as unix would) while most path based solutions will omit the final slash.
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Regular expression that matches valid IPv6 addresses
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@user712092 -- everyone who has seen a code base with eyesores such as that
– danielpops
Jan 12 '12 at 3:28
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Why does Math.round(0.49999999999999994) return 1?
...ound%28double%29
2. http://bugs.java.com/bugdatabase/view_bug.do?bug_id=6430675 (credits to @SimonNickerson for finding this)
3. http://docs.oracle.com/javase/7/docs/api/java/lang/Math.html#round%28double%29
4. http://grepcode.com/file/repository.grepcode.com/java/root/jdk/openjdk/7u40-b43/...
How can I get query string values in JavaScript?
...nsitive parameter name, [add 'i' modifier to RegExp][2]
This is an update based on the new URLSearchParams specs to achieve the same result more succinctly. See answer titled "URLSearchParams" below.
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Set a path variable with spaces in the path in a Windows .cmd file or batch file
... JoeyJoey
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Efficiently replace all accented characters in a string?
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Here is a more complete version based on the Unicode standard, taken from here: http://semplicewebsites.com/removing-accents-javascript
var Latinise={};Latinise.latin_map={"Á":"A",
"Ă":"A",
"Ắ":"A",
"Ặ":"A",
"Ằ":"A",
"Ẳ":"A",
"Ẵ":"A",
"Ǎ":"A",...
Sanitizing strings to make them URL and filename safe?
...e provides:
canonicalize (string $input, [bool $strict = true])
decodeFromBase64 (string $input)
decodeFromURL (string $input)
encodeForBase64 (string $input, [bool $wrap = false])
encodeForCSS (string $input)
encodeForHTML (string $input)
encodeForHTMLAttribute (string $input)
encodeForJavaScript ...
Difference between Document-based and Key/Value-based databases?
I know there are three different, popular types of non-sql databases.
2 Answers
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symfony 2 twig limit the length of the text and put three dots
...s character (…) instead of 3 real dots (...)
– Nemo64
Jul 31 '17 at 10:51
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count the frequency that a value occurs in a dataframe column
...columns you can use:
df.apply(pd.value_counts)
This will apply a column based aggregation function (in this case value_counts) to each of the columns.
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