import pandas as pd import numpy as np import random import matplotlib.pyplot as plt time_range = pd.date_range('1/1/2018',periods=1096) fruits = ["苹果","西瓜","橙子","葡萄","车厘子","菠萝","荔枝","火龙果"] fruit_list = np.random.choice(fruits,size=len(time_range),replace=True) names = ["张伟","王芳","李静","王秀英","李强","李丽","刘勇"] name_list = np.random.choice(names,size=len(time_range),replace=True) order = pd.DataFrame({ "time":time_range, "fruit":fruit_list, "name":name_list, "weight":np.random.choice(list(range(40,100)),size=len(time_range),replace=True) }) information = pd.DataFrame({ "fruit":fruits, "price":[5.8,5,8.8,12,25.2,9.9,15.8,7], "region":["华南","东北","西北","华中","西北","华南","华北","华中"] }) 利用以上数据用曲线图展示每月销售量走势
时间: 2023-08-31 19:08:28 浏览: 38
可以按照以下步骤进行绘图:
1. 首先,将订单数据按月分组,并计算每月的销售量。
```
order["month"] = order["time"].dt.month
monthly_sales = order.groupby("month")["weight"].sum()
```
2. 接下来,将每月销售量走势绘制成曲线图。
```
plt.plot(monthly_sales.index, monthly_sales.values)
plt.xlabel("月份")
plt.ylabel("销售量")
plt.title("每月销售量走势")
plt.show()
```
完整代码如下:
```
import pandas as pd
import numpy as np
import random
import matplotlib.pyplot as plt
time_range = pd.date_range('1/1/2018',periods=1096)
fruits = ["苹果","西瓜","橙子","葡萄","车厘子","菠萝","荔枝","火龙果"]
fruit_list = np.random.choice(fruits,size=len(time_range),replace=True)
names = ["张伟","王芳","李静","王秀英","李强","李丽","刘勇"]
name_list = np.random.choice(names,size=len(time_range),replace=True)
order = pd.DataFrame({
"time":time_range,
"fruit":fruit_list,
"name":name_list,
"weight":np.random.choice(list(range(40,100)),size=len(time_range),replace=True)
})
information = pd.DataFrame({
"fruit":fruits,
"price":[5.8,5,8.8,12,25.2,9.9,15.8,7],
"region":["华南","东北","西北","华中","西北","华南","华北","华中"]
})
order["month"] = order["time"].dt.month
monthly_sales = order.groupby("month")["weight"].sum()
plt.plot(monthly_sales.index, monthly_sales.values)
plt.xlabel("月份")
plt.ylabel("销售量")
plt.title("每月销售量走势")
plt.show()
```
运行结果将会显示每月销售量的曲线图。