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Populate data table from data reader

I'm doing a basic thing in C# (MS VS2008) and have a question more about proper design than specific code. 5 Answers ...
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.Net picking wrong referenced assembly version

... publicKeyToken="121fae78165ba3d4"/> <bindingRedirect oldVersion="1.0.0.0" newVersion="2.0.0.0"/> </dependentAssembly> share | improve this answer | follow ...
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Prepend a level to a pandas MultiIndex

... cs95 231k6060 gold badges392392 silver badges456456 bronze badges answered Feb 7 '17 at 16:11 okartalokartal ...
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CSS div element - how to show horizontal scroll bars only?

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What does ** (double star/asterisk) and * (star/asterisk) do for parameters?

...s the other way around: def foo(a, b, c): print(a, b, c) obj = {'b':10, 'c':'lee'} foo(100,**obj) # 100 10 lee Another usage of the *l idiom is to unpack argument lists when calling a function. def foo(bar, lee): print(bar, lee) l = [1,2] foo(*l) # 1 2 In Python 3 it is possible to...
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Passing a URL with brackets to curl

... | edited Jul 2 '19 at 20:14 moveson 4,45011 gold badge99 silver badges3131 bronze badges answered Nov...
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How to initialize a vector in C++ [duplicate]

...is with an array: int vv[2] = { 12,43 }; std::vector<int> v(&vv[0], &vv[0]+2); Or, for the case of assignment to an existing vector: int vv[2] = { 12,43 }; v.assign(&vv[0], &vv[0]+2); Like James Kanze suggested, it's more robust to have functions that give you the beginni...
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In Scala, what exactly does 'val a: A = _' (underscore) mean?

...he variable to a default value. From the Scala Language Specification: 0 if T is Int or one of its subrange types, 0L if T is Long, 0.0f if T is Float, 0.0d if T is Double, false if T is Boolean, () if T is Unit, null for all other types T. ...
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Capturing Groups From a Grep RegEx

I've got this little script in sh (Mac OSX 10.6) to look through an array of files. Google has stopped being helpful at this point: ...
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Compare two DataFrames and output their differences side-by-side

... rows are empty*: In [21]: ne = (df1 != df2).any(1) In [22]: ne Out[22]: 0 False 1 True 2 True dtype: bool Then we can see which entries have changed: In [23]: ne_stacked = (df1 != df2).stack() In [24]: changed = ne_stacked[ne_stacked] In [25]: changed.index.names = ['id', 'col'] ...