BinLists

BinLists[{x1,x2,…}]

gives lists of the elements xi whose values lie in successive integer bins.

BinLists[{x1,x2,…},dx]

gives lists of the elements xi whose values lie in successive bins of width dx.

BinLists[{x1,x2,…},{xmin,xmax,dx}]

gives lists of the xi that lie in successive bins of width dx from xmin to xmax.

BinLists[{x1,x2,…},{{b1,b2,…}}]

gives lists of the xi that lie in the intervals [b1,b2), [b2,b3), ….

BinLists[{{x1,y1,…},{x2,y2,…},…},xbins,ybins,…]

gives an array of lists where the first index corresponds to x bins, the second to y, and so on.

Details

  • BinLists drops elements whose values do not correspond to real numbers.
  • Within each bin, elements appear in the same order as in the original data.
  • BinLists[data,dx] takes the bin boundaries to be integer multiples of dx, with the first bin starting at Ceiling[Min[data]-dx,dx] and the last bin ending at Floor[Max[data]+dx,dx].
  • BinLists[data] is equivalent to BinLists[data,1].
  • BinLists[data,{xmin,xmax}] is equivalent to BinLists[data,{xmin,xmax,1}].
  • In BinLists[data,{xmin,xmax,dx}], elements are placed in bin i when their values satisfy .
  • In the form BinLists[data,{{b1,b2,…}}], the bi at each end can be -Infinity and +Infinity.
  • If the bi do not form an increasing sequence, they are automatically sorted by BinLists.
  • In BinLists[data,{{b1,b2,…}}], elements are put in bin i when their values satisfy .
  • If data consists of length-n sublists, then n bin specifications must be given, and BinLists[data,…] yields an array of lists of depth n.
  • BinLists works with SparseArray objects.

Examples

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Basic Examples  (3)

Make lists of elements in bins of width 1 from 0 to 10:

List elements in a sequence of ranges:

List elements in bins of a specified width:

Scope  (7)

List squares mod 3 and 5 in two-dimensional unit bins:

List random pairs in bins of width 0.25 in both dimensions:

List multidimensional data in ranges:

Bin data in any dimension:

Bin data, ignoring values that are not real:

Bin data of any precision:

Bin data from a time series:

The time stamps are ignored:

Applications  (1)

Visualize two-dimensional data in bins:

Properties & Relations  (1)

The length of BinLists is equivalent to the results from BinCounts:

Possible Issues  (1)

Binning intervals are closed on the left:

Wolfram Research (2007), BinLists, Wolfram Language function, https://reference.wolfram.com/language/ref/BinLists.html.

Text

Wolfram Research (2007), BinLists, Wolfram Language function, https://reference.wolfram.com/language/ref/BinLists.html.

CMS

Wolfram Language. 2007. "BinLists." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/BinLists.html.

APA

Wolfram Language. (2007). BinLists. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/BinLists.html

BibTeX

@misc{reference.wolfram_2022_binlists, author="Wolfram Research", title="{BinLists}", year="2007", howpublished="\url{https://reference.wolfram.com/language/ref/BinLists.html}", note=[Accessed: 04-June-2023 ]}

BibLaTeX

@online{reference.wolfram_2022_binlists, organization={Wolfram Research}, title={BinLists}, year={2007}, url={https://reference.wolfram.com/language/ref/BinLists.html}, note=[Accessed: 04-June-2023 ]}