enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    [4]: 114 A DataFrame is a 2-dimensional data structure of rows and columns, similar to a spreadsheet, and analogous to a Python dictionary mapping column names (keys) to Series (values), with each Series sharing an index. [4]: 115 DataFrames can be concatenated together or "merged" on columns or indices in a manner similar to joins in SQL.

  3. Sturges's rule - Wikipedia

    en.wikipedia.org/wiki/Sturges's_rule

    Sturges's rule [1] is a method to choose the number of bins for a histogram.Given observations, Sturges's rule suggests using ^ = + ⁡ bins in the histogram. This rule is widely employed in data analysis software including Python [2] and R, where it is the default bin selection method.

  4. Wide and narrow data - Wikipedia

    en.wikipedia.org/wiki/Wide_and_narrow_data

    The pandas package in Python implements this operation as "melt" function which converts a wide table to a narrow one. The process of converting a narrow table to wide table is generally referred to as "pivoting" in the context of data transformations.

  5. Frequency (statistics) - Wikipedia

    en.wikipedia.org/wiki/Frequency_(statistics)

    A histogram is a representation of tabulated frequencies, shown as adjacent rectangles or squares (in some of situations), erected over discrete intervals (bins), with an area proportional to the frequency of the observations in the interval. The height of a rectangle is also equal to the frequency density of the interval, i.e., the frequency ...

  6. Histogram equalization - Wikipedia

    en.wikipedia.org/wiki/Histogram_equalization

    Histogram equalization will work the best when applied to images with much higher color depth than palette size, like continuous data or 16-bit gray-scale images. There are two ways to think about and implement histogram equalization, either as image change or as palette change.

  7. Bag-of-words model in computer vision - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model_in...

    The final step for the BoW model is to convert vector-represented patches to "codewords" (analogous to words in text documents), which also produces a "codebook" (analogy to a word dictionary). A codeword can be considered as a representative of several similar patches. One simple method is performing k-means clustering over all the vectors. [7]

  8. Associative array - Wikipedia

    en.wikipedia.org/wiki/Associative_array

    The program can create a complete text representation of any group of objects by calling these methods, which are almost always already implemented in the base associative array class. [ 23 ] For programs that use very large data sets, this sort of individual file storage is not appropriate, and a database management system (DB) is required.

  9. Skewness - Wikipedia

    en.wikipedia.org/wiki/Skewness

    Skewness is a descriptive statistic that can be used in conjunction with the histogram and the normal quantile plot to characterize the data or distribution. Skewness indicates the direction and relative magnitude of a distribution's deviation from the normal distribution.