CSV数据集操作

import pandas as pd
df = pd.read_csv(r‘F:\catering_sale.csv‘)
print(df)

             日期      销量
0    2015-03-01    51.0
1    2015-02-28  2618.2
2    2015-02-27  2608.4
3    2015-02-26  2651.9
4    2015-02-25  3442.1
5    2015-02-24  3393.1
6    2015-02-23  3136.6
7    2015-02-22  3744.1
8    2015-02-21  6607.4
9    2015-02-20  4060.3
10   2015-02-19  3614.7
11   2015-02-18  3295.5
12   2015-02-16  2332.1
13   2015-02-15  2699.3
14   2015-02-14     NaN
15   2015-02-13  3036.8
16   2015-02-12   865.0
17   2015-02-11  3014.3
18   2015-02-10  2742.8
19   2015-02-09  2173.5
20   2015-02-08  3161.8
21   2015-02-07  3023.8
22   2015-02-06  2998.1
23   2015-02-05  2805.9
24   2015-02-04  2383.4
25   2015-02-03  2620.2
26   2015-02-02  2600.0
27   2015-02-01  2358.6
28   2015-01-31  2682.2
29   2015-01-30  2766.8
..          ...     ...
171  2014-08-31  3494.7
172  2014-08-30  3691.9
173  2014-08-29  2929.5
174  2014-08-28  2760.6
175  2014-08-27  2593.7
176  2014-08-26  2884.4
177  2014-08-25  2591.3
178  2014-08-24  3022.6
179  2014-08-23  3052.1
180  2014-08-22  2789.2
181  2014-08-21  2909.8
182  2014-08-20  2326.8
183  2014-08-19  2453.1
184  2014-08-18  2351.2
185  2014-08-17  3279.1
186  2014-08-16  3381.9
187  2014-08-15  2988.1
188  2014-08-14  2577.7
189  2014-08-13  2332.3
190  2014-08-12  2518.6
191  2014-08-11  2697.5
192  2014-08-10  3244.7
193  2014-08-09  3346.7
194  2014-08-08  2900.6
195  2014-08-07  2759.1
196  2014-08-06  2915.8
197  2014-08-05  2618.1
198  2014-08-04  2993.0
199  2014-08-03  3436.4
200  2014-08-02  2261.7

[201 rows x 2 columns]

max_number = pd.DataFrame(df["销量"]).max()
min_number = pd.DataFrame(df["销量"]).min()
average = pd.DataFrame(df["销量"]).mean()
print("max:")
print(max_number)
print("min:")
print(min_number)
print("ave:")
print(average)

max:
销量    9106.44
dtype: float64
min:
销量    22.0
dtype: float64
ave:
销量    2755.2147
dtype: float64

missing_value = df[‘销量‘].shape[0] -  df[‘销量‘].count()
print("缺失个数：",missing_value)
print("样本个数：",df[‘销量‘].shape[0])


缺失个数： 1
样本个数： 201

import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv(r‘F:\catering_sale.csv‘)
#解决中文显示问题
plt.rcParams[‘font.sans-serif‘] = [‘KaiTi‘] # 指定默认字体
plt.rcParams[‘axes.unicode_minus‘] = False # 解决保存图像是负号‘-‘显示为方块的问题
fig,axes = plt.subplots()
df.boxplot(column=‘销量‘,ax=axes)
# column参数表示要绘制成箱形图的数据，可以是一列或多列
# by参数表示分组依据
axes.set_ylabel(‘values of data‘)
fig.savefig(r‘F:\demo1.png‘)