This is just the mode. Here’s a quick, non-optimized solution. It should be O(n). function mode(array) { if(array.length == 0) return null; var modeMap = {}; var maxEl = array[0], maxCount = 1; for(var i = 0; i < array.length; i++) { var el = array[i]; if(modeMap[el] == null) modeMap[el] = 1; else modeMap[el]++; if(modeMap[el] … Read more
MsBuild.exe [Path to your solution(*.sln)] /t:Build /p:Configuration=Release /p:TargetFrameworkVersion=v4.0
Check scipy.stats.mode() (inspired by @tom10’s comment): import numpy as np from scipy import stats a = np.array([[1, 3, 4, 2, 2, 7], [5, 2, 2, 1, 4, 1], [3, 3, 2, 2, 1, 1]]) m = stats.mode(a) print(m) Output: ModeResult(mode=array([[1, 3, 2, 2, 1, 1]]), count=array([[1, 2, 2, 2, 1, 2]])) As you can see, … Read more
You can use the max function and a key. Have a look at python max function using ‘key’ and lambda expression. max(set(lst), key=lst.count)
Pandas >= 0.16 pd.Series.mode is available! Use groupby, GroupBy.agg, and apply the pd.Series.mode function to each group: source.groupby([‘Country’,’City’])[‘Short name’].agg(pd.Series.mode) Country City Russia Sankt-Petersburg Spb USA New-York NY Name: Short name, dtype: object If this is needed as a DataFrame, use source.groupby([‘Country’,’City’])[‘Short name’].agg(pd.Series.mode).to_frame() Short name Country City Russia Sankt-Petersburg Spb USA New-York NY The useful thing … Read more
To exit Scale Mode, press: Right Ctrl (Host Key) + c Note that your (Host Key) may be different from Right Ctrl. To check the current binding, go to VirtualBox Preferences > Input > Virtual Machine > Host Key Combination.