Search results
Results from the WOW.Com Content Network
Data visualization is a technique that allows data scientists to convert raw data into charts and plots that generate valuable insights. There are many tools to perform data visualization, such as ...
Data and information visualization (data viz/vis or info viz/vis) [2] is the practice of designing and creating easy-to-communicate and easy-to-understand graphic or visual representations of a large amount [3] of complex quantitative and qualitative data and information with the help of static, dynamic or interactive visual items.
Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.
Data visualization is a related subcategory of visualization dealing with statistical graphics and geospatial data (as in thematic cartography) that is abstracted in schematic form. [ 7 ] Information visualization concentrates on the use of computer-supported tools to explore large amount of abstract data.
Graphic representation of a minute fraction of the WWW, demonstrating hyperlinks.. Graph drawing is an area of mathematics and computer science combining methods from geometric graph theory and information visualization to derive two-dimensional depictions of graphs arising from applications such as social network analysis, cartography, linguistics, and bioinformatics.
A waterfall chart is a form of data visualization that helps in understanding the cumulative effect of sequentially introduced positive or negative values. These intermediate values can either be time based or category based.
Violin plots are similar to box plots, except that they also show the probability density of the data at different values, usually smoothed by a kernel density estimator.A violin plot will include all the data that is in a box plot: a marker for the median of the data; a box or marker indicating the interquartile range; and possibly all sample points, if the number of samples is not too high.
A box plot of the data set can be generated by first calculating five relevant values of this data set: minimum, maximum, median (Q 2), first quartile (Q 1), and third quartile (Q 3). The minimum is the smallest number of the data set. In this case, the minimum recorded day temperature is 57°F. The maximum is the largest number of the data set.