我有用于繪制圖表的代碼：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() 該代碼運行得很好。我想知道如何在同一個圖上繪制多個圖表？換句話說，兩張圖表合二為一。我一直在嘗試子圖，但無法獲得預期的結果。謝謝，謝謝。這是我的數據示例：DAYS_UNTIL_DEPARTURE,DESTINY,COST10,JPA,1009,JPA,908,JPA,857,JPA,866,JPA,875,JPA,714,JPA,903,JPA,772,JPA,881,JPA,870,JPA,7410,FOR,999,FOR,908,FOR,967,FOR,796,FOR,845,FOR,744,FOR,853,FOR,742,FOR,881,FOR,1000,FOR,87
3 回答
婷婷同學_
TA貢獻1844條經驗 獲得超8個贊
groupby和stack數據框?要容易得多。兩者
min, 和max可以同時聚合。
seaborn是 的高級API選項matplotlib，因此我建議使用seaborn.relplot, 在同一個圖中繪制兩個目的地
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}'))
ibeautiful
TA貢獻1993條經驗 獲得超6個贊
可以使用以下代碼實現將多個圖表組合成單個圖表的簡單示例
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()
眼眸繁星
TA貢獻1873條經驗 獲得超9個贊
使用ax參數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')
添加回答
舉報
0/150
提交
取消