数据分析工具pandas快速入门教程3绘图2matplotlib

matplotlib统计图

seaborn的tips数据集包含消费账单的大小，人数，星期几，时间等。

• 加载tips数据集

tips = sns.load_dataset("tips")

print(tips.head())
   total_bill   tip     sex smoker  day    time  size
0       16.99  1.01  Female     No  Sun  Dinner     2
1       10.34  1.66    Male     No  Sun  Dinner     3
2       21.01  3.50    Male     No  Sun  Dinner     3
3       23.68  3.31    Male     No  Sun  Dinner     2
4       24.59  3.61  Female     No  Sun  Dinner     4

• 直方图(单变量)

fig = plt.figure()
axes1 = fig.add_subplot(1, 1, 1)
axes1.hist(tips['total_bill'], bins=10)
axes1.set_title('Histogram of Total Bill')
axes1.set_xlabel('Frequency' )
axes1.set_ylabel('Total Bill')
fig.show ()

图片.png

• 散点图(双变量)

scatter_plot = plt.figure()
axesl = scatter_plot.add_subplot(1, 1, 1)
axesl.scatter(tips['total_bill'], tips['tip'])
axesl.set_title('Scatterplot of Total Bill vs Tip')
axesl.set_xlabel('Total Bill')
axesl.set_ylabel('Tip') 
scatter_plot.show()

图片.png

• 箱形图

boxplot = plt.figure()
axesl = boxplot.add_subplot(1, 1, 1)
axesl.boxplot([tips[tips['sex'] == 'Female']['tip'], tips[tips ['sex'] == 'Male']['tip']])
axesl.set_xlabel('Sex')
axesl.set_ylabel('Tip')
axesl.set_title('Boxplot of Tips by Sex')

图片.png

• 多变量绘图

# create a color variable based on the sex
def recode_sex(sex):
    if sex == 'Female':
        return 0
    else:
        return 1
    
tips['sex_color'] = tips['sex'].apply(recode_sex)
scatter_plot = plt.figure()
axesl = scatter_plot.add_subplot(1, 1, 1)
axesl.scatter(x=tips['total_bill'], y=tips['tip'], s=tips['size'] * 10,
c=tips['sex_color'], alpha=0.5)
axesl.set_title('Total Bill vs Tip colored by Sex and sized by Size')
axesl.set_xlabel('Total Bill')
axesl.set_ylabel('Tip')
scatter_plot.show()

图片.png

参考资料

• 本文涉及的python测试开发库 谢谢点赞
• 本文相关书籍下载
• 源码下载
• 本文英文版书籍下载
• http://matplotlib.org/users/colormaps.html
• http://stanford.edu/%CB%9Cmwaskom/software/seaborn-dev/tutorial/color_palettes.html
• http://colorbrewer2.org/