如何在同一图形中按组和绘制组

Question

我有绘制图表的代码：

destinations = ['JPA', 'FOR']

for destiny in destinations:

    df_tmp = df[(df.DESTINY == destiny)]
    df_tmp['max'] = df_tmp.groupby('DAYS_UNTIL_DEPARTURE')['COST'].transform('max')
    df_tmp['min'] = df_tmp.groupby('DAYS_UNTIL_DEPARTURE')['COST'].transform('min')

    plt.figure(figsize=(10,2))
    sns.lineplot(x="DAYS_UNTIL_DEPARTURE", y="min", data=df_tmp, ci=None, palette="muted", label='min')
    sns.lineplot(x="DAYS_UNTIL_DEPARTURE", y="max", data=df_tmp, ci=None, palette="muted", label='max')
    plt.title(destiny , fontweight="bold", fontsize=16, pad=20)
    plt.ylabel('Cost')
    plt.show()

代码运行得很好。

我想知道如何在同一数字上绘制多个图表？换句话说，在一个数字中有两个图表。

我一直在尝试细分，但我没有得到预期的结果。

谢谢，谢谢。

以下是我的数据示例：

DAYS_UNTIL_DEPARTURE,DESTINY,COST
10,JPA,100
9,JPA,90
8,JPA,85
7,JPA,86
6,JPA,87
5,JPA,71
4,JPA,90
3,JPA,77
2,JPA,88
1,JPA,87
0,JPA,74
10,FOR,99
9,FOR,90
8,FOR,96
7,FOR,79
6,FOR,84
5,FOR,74
4,FOR,85
3,FOR,74
2,FOR,88
1,FOR,100
0,FOR,87

Answer 1

• -- groupby要容易得多，而数据格式的stack则容易得多。可以在同一个time.

中聚合

• ( min和max )。

• seaborn是用于matplotlib的高级API，因此我建议使用seaborn.relplot，在相同的图

中绘制两个目的地。

import pandas as pd
import numpy as np  # for sample data
import random  # for sample data
import seaborn as sns
import matplotlib.pyplot as ply

# create sample data
np.random.seed(365)
random.seed(365)
rows = 300
data = {'days': np.random.randint(10, size=(rows)), 'dest': [random.choice(['JPA', 'FOR']) for _ in range(rows)], 'cost': np.random.randint(70, 120, size=(rows))}
df = pd.DataFrame(data)

# groupby, aggregate, and stack
dfg = df.groupby(['dest', 'days'])['cost'].agg(['min', 'max']).stack().reset_index().rename(columns={'level_2': 'range', 0: 'vals'})

# plot with seaborn relplot
(sns.relplot(x='days', y='vals', hue='range', col='dest', data=dfg, kind='line')
 .set_axis_labels('Day Until Departure', 'Cost')
 .set_titles('Destination: {col_name}'))

​

​

Answer 2

使用参数ax of sns.lineplot

fig, ax = plt.subplots(1,2)
destinations = ['JPA', 'FOR']

for i, destiny in enumerate(destinations):
    df_tmp = df[(df.DESTINY == destiny)]
    df_tmp['max'] = df_tmp.groupby('DAYS_UNTIL_DEPARTURE')['COST'].transform('max')
    df_tmp['min'] = df_tmp.groupby('DAYS_UNTIL_DEPARTURE')['COST'].transform('min')

    sns.lineplot(x="DAYS_UNTIL_DEPARTURE", y="min", data=df_tmp, ci=None, palette="muted", label='min', ax=ax[i])
    sns.lineplot(x="DAYS_UNTIL_DEPARTURE", y="max", data=df_tmp, ci=None, palette="muted", label='max', ax=ax[i])
    ax[i].set_title(destiny , fontweight="bold", fontsize=16, pad=20)
    plt.ylabel('Cost')

​

​

Answer 3

可以使用以下代码实现将多个图表组合成单个图的简单示例

import matplotlib.pyplot as plt
import seaborn as sns

fig = plt.figure(figsize=(10,2))
ax = fig.add_subplot(111)

destinations = ['JPA', 'FOR']

for destiny in destinations:

    df_tmp = df[(df.DESTINY == destiny)]
    df_tmp['max'] = df_tmp.groupby('DAYS_UNTIL_DEPARTURE')['COST'].transform('max')
    df_tmp['min'] = df_tmp.groupby('DAYS_UNTIL_DEPARTURE')['COST'].transform('min')

    sns.lineplot(x="DAYS_UNTIL_DEPARTURE", y="min", data=df_tmp, ci=None, palette="muted", label='min')
    sns.lineplot(x="DAYS_UNTIL_DEPARTURE", y="max", data=df_tmp, ci=None, palette="muted", label='max')
    
plt.title('Destiny', fontweight="bold", fontsize=16, pad=20)
plt.ylabel('Cost')
plt.show()

​

​