使用python的bokeh库对housing是否有房贷和default信用卡是否违约条形图判断有房贷是否违约和无房贷是否违约比例进行可视化分析布局合理from bokehplotting import figure showoutput_fileimport numpy as npimport pandas as pdimport pandasdf = pdread_csvrUsersfuchu
数据清洗
df.dropna(inplace=True) test.dropna(inplace=True)
统计有/无房贷违约比例
housing_default = df.groupby(['housing', 'default']).size().reset_index(name='count') housing_default['percent'] = housing_default['count'] / housing_default['count'].sum()
绘制条形图
p = figure(x_range=housing_default['housing'] + housing_default['default'], plot_height=350, title="Housing and Default", toolbar_location=None, tools="")
p.vbar(x=housing_default['housing'] + housing_default['default'], top=housing_default['percent'], width=0.9)
p.xgrid.grid_line_color = None p.y_range.start = 0 p.y_range.end = 0.7 p.legend.orientation = "horizontal" p.legend.location = "top_center"
输出HTML文件
output_file("housing_default.html")
显示图形
show(p
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