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  • Matplotlib 图表的样式参数

    1.

    import numpy as np
    import pandas as pd
    import matplotlib.pyplot as plt
    % matplotlib inline
    # 导入相关模块
    
    # linestyle参数
    
    plt.plot([i**2 for i in range(100)],
            linestyle = '-.')  #不用设置的时候默认为直线‘-’
    # '-'       solid line style
    # '--'      dashed line style
    # '-.'      dash-dot line style
    # ':'       dotted line style

    输出:

    [<matplotlib.lines.Line2D at 0x1e1348c8550>]

    2.

    df = pd.DataFrame(np.random.randn(1000))
    df.plot(kind = 'kde',linestyle = '--')  #绘制密度图
    df.hist()  #绘制直方图

    输出:

    array([[<matplotlib.axes._subplots.AxesSubplot object at 0x00000185B8B0ADA0>]], dtype=object)

    3.

    # marker参数
    
    s = pd.Series(np.random.randn(100).cumsum())
    s.plot(linestyle = '--',linewidth = 1,  
          marker = 'x')  #图中点的风格设置  默认为‘.’ linwidth为线宽 即线的粗细
    # '.'       point marker
    # ','       pixel marker
    # 'o'       circle marker
    # 'v'       triangle_down marker
    # '^'       triangle_up marker
    # '<'       triangle_left marker
    # '>'       triangle_right marker
    # '1'       tri_down marker
    # '2'       tri_up marker
    # '3'       tri_left marker
    # '4'       tri_right marker
    # 's'       square marker
    # 'p'       pentagon marker
    # '*'       star marker
    # 'h'       hexagon1 marker
    # 'H'       hexagon2 marker
    # '+'       plus marker
    # 'x'       x marker
    # 'D'       diamond marker
    # 'd'       thin_diamond marker
    # '|'       vline marker
    # '_'       hline marker

    输出:

    <matplotlib.axes._subplots.AxesSubplot at 0x185b8faed30>

    5.

    x = np.random.randn(1000)
    y = np.random.randn(1000)
    plt.scatter(x,y,marker = '.')

    输出:

    6.

    # color参数
    
    plt.hist(np.random.randn(100),
            color = 'g',alpha = 0.8)
    # alpha:0-1,透明度
    # 常用颜色简写:red-r, green-g, black-k, blue-b, yellow-y
    
    df = pd.DataFrame(np.random.randn(1000, 4),columns=list('ABCD'))
    df = df.cumsum()
    df.plot(style = '--.',alpha = 0.8,colormap = 'GnBu')
    # colormap:颜色板,包括:      
    # Accent, Accent_r, Blues, Blues_r, BrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens, Greens_r,
    # Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, Pastel2_r, PiYG, PiYG_r, 
    # PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy, RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, 
    # RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, Spectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, 
    # YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn, autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, 
    # cool, cool_r, coolwarm, coolwarm_r, copper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r,
    # gist_heat, gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r, gnuplot, 
    # gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma, magma_r, nipy_spectral, 
    # nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, seismic, seismic_r, spectral, 
    # spectral_r ,spring, spring_r, summer, summer_r, terrain, terrain_r, viridis, viridis_r, winter, winter_r
    
    # 其他参数见“颜色参数.docx”

    输出:

    <matplotlib.axes._subplots.AxesSubplot at 0x1e135dac4a8>

    6.

    # style参数,可以包含linestyle,marker,color
    
    ts = pd.Series(np.random.randn(1000).cumsum(), index=pd.date_range('1/1/2000', periods=1000))
    ts.plot(style = '--g.',grid = True)
    # style → 风格字符串,这里包括了linestyle(-),marker(.),color(g)
    # plot()内也有grid参数

    输出:

    <matplotlib.axes._subplots.AxesSubplot at 0x1e135e04fd0>

    7.

    # 整体风格样式
    
    import matplotlib.style as psl
    print(plt.style.available)
    # 查看样式列表
    psl.use('ggplot')
    ts = pd.Series(np.random.randn(1000).cumsum(), index=pd.date_range('1/1/2000', periods=1000))
    ts.plot(style = '--g.',grid = True,figsize=(10,6))
    # 一旦选用样式后,所有图表都会有样式,重启后才能关掉

    输出:

    ['seaborn-paper', 'seaborn-deep', 'fivethirtyeight', 'seaborn-pastel', 'dark_background', 
    'seaborn-bright', 'seaborn-ticks', 'seaborn-notebook', 'classic', 'seaborn-white',
    'grayscale', 'seaborn-muted', 'seaborn-darkgrid', 'seaborn-dark', 'seaborn-talk',
    'seaborn-colorblind', 'seaborn-dark-palette', 'ggplot', 'seaborn-whitegrid', 'seaborn-poster', 'bmh']
    <matplotlib.axes._subplots.AxesSubplot at 0x1e134aef940>

    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
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  • 原文地址:https://www.cnblogs.com/carlber/p/9934397.html
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