生成多散点子图 - 返回意外结果

Question

我是 python 的新手，我正在尝试创建多个月的子图。发生的情况是生成了 3 x3 的块但是是空的，然后每个图表都在另一个图表下面，这不允许轻松查看。

这是我从类似问题中提取的代码。

def scat_months2(df,prod):
    """Print scatter for all months as sub plots of any given product"""
    uniq=sorted(set(train2.YM))[0:9]
    fig, axes = plt.subplots(3, 3, figsize=(6, 4), sharex=True, sharey=True)
    for period in uniq:
        df[(df["YM"]==period) & (df["item_id"]==prod)].plot(x='shop_id',
            y='item_price',
            kind='scatter',
            label=period,alpha=0.2)

    fig.tight_layout()

我已经尝试生成一些随机数据，以便您可以帮助我，但这也没有像我希望的那样成功（再次 python 新手）...它生成了一个不同的错误.我希望这仍然可以让您轻松修复我的示例，然后看到与我看到的相同的结果..

如果你能告诉我如何正确生成随机数据，那对我的学习很有帮助。对于无法提供功能示例，我深表歉意。

import numpy as np
import pandas as pd
from matplotlib import pyplot as plt

T=pd.Series([201301,201301,201301,201301,201301,201301,201301,201301,201301])
Shop=pd.Series([1,1,1,2,2,2,3,3,3])
Price=pd.Series(np.random.randint(10, size=(9)))
ds1=pd.DataFrame(dict(T = T, Shop=Shop,Price = Price))
T2=pd.Series([201302,201302,201302,201302,201302,201302,201302,201302,201302])
ds2=pd.DataFrame(dict(T = T2, Shop=Shop,Price = Price))
T3=pd.Series([201303,201303,201303,201303,201303,201303,201303,201303,201303])
ds3=pd.DataFrame(dict(T = T3, Shop=Shop,Price = Price))
ds=pd.concat([ds1,ds2,ds3], axis=0)
ds.index=range(27)

def scat_months2(df):
    """Print scatter for all months as sub plots of any given product"""
    uniq=sorted(set(df.T))
    fig, axes = plt.subplots(3, 1, figsize=(6, 4), sharex=True, sharey=True)
    for period in uniq:
        df[df["T"]==period].plot(x='Shop',
            y='Price',
            kind='scatter')

    fig.tight_layout()

Answer 1

你需要给plot函数的ax参数赋值：

import numpy as np
import pandas as pd
from matplotlib import pyplot as plt

T=pd.Series([201301,201301,201301,201301,201301,201301,201301,201301,201301])
Shop=pd.Series([1,1,1,2,2,2,3,3,3])
Price=pd.Series(np.random.randint(10, size=(9)))
ds1=pd.DataFrame(dict(T = T, Shop=Shop,Price = Price))
T2=pd.Series([201302,201302,201302,201302,201302,201302,201302,201302,201302])
ds2=pd.DataFrame(dict(T = T2, Shop=Shop,Price = Price))
T3=pd.Series([201303,201303,201303,201303,201303,201303,201303,201303,201303])
ds3=pd.DataFrame(dict(T = T3, Shop=Shop,Price = Price))
ds=pd.concat([ds1,ds2,ds3], axis=0)
ds.index=range(27)

def scat_months2(df):
    """Print scatter for all months as sub plots of any given product"""
    uniq=sorted(set(df['T']))
    fig, axes = plt.subplots(len(uniq), 1, figsize=(6, 4), sharex=True, sharey=True)
    for i, period in enumerate(uniq):
        df[df["T"]==period].plot(x='Shop',
            y='Price',
            kind='scatter',
            ax=axes[i])

    fig.tight_layout()
    plt.show()

scat_months2(ds)

（您的示例中有一个小错误，我已更正以使其正常工作：df.T returns 转置数据框，如果您的列名是 T 那么您需要明确编写 df['T'] 而不是 df.T)

PS: 为了方便创建样本数据 你可以使用numpy的repeat and tile函数:

months = [201301, 201302, 201303]
shops = [1,2,3]
n = 3
df = pd.DataFrame({'Month': np.repeat(months, n*len(shops)), 'Shop': np.tile(shops, n*len(months)), 'Price': np.random.randint(10, size=n*len(shops)*len(months))})

生成多散点子图 - 返回意外结果

Generate a multi scatter subplot - unexpected results returned

python

scatter

matplotlib

subplot