seaborn - PowerPoint PPT Presentation

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seaborn

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Seaborn is a Python data visualization library based on matplotlib. Some basics of seaborn are highlighted in this tutorial along with some characteristics. Moreover, various plots that can be plotted to observe the distribution patterns using seaborn are also named. Distplot function is discussed in detail. – PowerPoint PPT presentation

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Title: seaborn


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Rug Plot
  • A rug plot is a plot of data for a single
    quantitative variable, displayed as marks along
    an axis. It is used to visualise the distribution
    of the data
  • Eghist  sns.distplot(pokemon_data'Attack Point
    ', rug  True)hist.set_title('Attack capability 
    with Density and Rug plot')hist.set_xlabel('Attac
    k')plt.show()

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O/P
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Plotting Bivariate Data
  • Plotting of data with 2 variables is also
    possible.
  • Different plots that can be plotted for bivariate
    data are 1.Scatter plot 2.Hexbin
    plot 3.kdeplot 4.Corelation

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Scatter Plot
  • jointplot() function is used to plot thescatter
    plot for bivariate data.
  • It is also possible to have the limit for x axis
    and y axis.
  • Egsns.jointplot(x 'Attack Point',y 'Defense P
    oint', data  pokemon_data)plt.show()

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  • Adding the limit to axes.
  • Egsns.jointplot(x  'Attack Point', y 'Defense 
    Point',data  pokemon_data,xlim  0,450, ylim  
    0,200)plt.show()
  • O/P

8
Hexbin Plot
  • A Hexbin plot is useful to depict the relationship
     of 2 numerical variables when you have a lot of 
    data point. Instead of overlapping, the plotting w
    indow is split in multiple hexbins, and the number
     of points per hexbin is counted. This number of p
    oints is denoted by the colour.
  • Darker the shade of the hexagon more are the data
    points in that region.
  • Egwith sns.axes_style('white')sns.jointplot(x 
    'Attack Point',
  • y 'Defense Point',
  •                   data  pokemon_data,
  •  kind 'hex',
     color 'r')

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