Cách vẽ nhiều biểu đồ trong python

Vẽ sơ đồ phân phối trên cùng một biểu đồ

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background [use sns.set_theme[] if seaborn version 0.11.0 or above] 
sns.set[style="darkgrid"]
df = sns.load_dataset["iris"]

sns.histplot[data=df, x="sepal_length", color="skyblue", label="Sepal Length", kde=True]
sns.histplot[data=df, x="sepal_width", color="red", label="Sepal Width", kde=True]

plt.legend[] 
plt.show[]

ví dụ 1. Biểu đồ với các biến khác nhau

Biểu đồ bên dưới được vẽ bằng cách sử dụng các tham số bổ sung như thùng, alpha và màu sắc. alpha xác định độ trong suốt, thùng xác định số lượng thùng và màu đại diện cho màu của biểu đồ

Python3

# import all modules

import pandas as pd

import seaborn as sns

import matplotlib.pyplot as plt

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background [use sns.set_theme[] if seaborn version 0.11.0 or above] 
sns.set[style="darkgrid"]
df = sns.load_dataset["iris"]

fig, axs = plt.subplots[2, 2, figsize=[7, 7]]

sns.histplot[data=df, x="sepal_length", kde=True, color="skyblue", ax=axs[0, 0]]
sns.histplot[data=df, x="sepal_width", kde=True, color="olive", ax=axs[0, 1]]
sns.histplot[data=df, x="petal_length", kde=True, color="gold", ax=axs[1, 0]]
sns.histplot[data=df, x="petal_width", kde=True, color="teal", ax=axs[1, 1]]

plt.show[]

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background [use sns.set_theme[] if seaborn version 0.11.0 or above] 
sns.set[style="darkgrid"]
df = sns.load_dataset["iris"]

fig, axs = plt.subplots[2, 2, figsize=[7, 7]]

sns.histplot[data=df, x="sepal_length", kde=True, color="skyblue", ax=axs[0, 0]]
sns.histplot[data=df, x="sepal_width", kde=True, color="olive", ax=axs[0, 1]]
sns.histplot[data=df, x="petal_length", kde=True, color="gold", ax=axs[1, 0]]
sns.histplot[data=df, x="petal_width", kde=True, color="teal", ax=axs[1, 1]]

plt.show[]

import5

import6import7____38import0 seaborn as sns0seaborn as sns1

seaborn as sns2seaborn as sns3import0 seaborn as sns5seaborn as sns6import0 seaborn as sns8import3

import9

đầu ra

ví dụ 2. chồng chéo biểu đồ

Trong đoạn mã dưới đây, chúng tôi vẽ hai biểu đồ trên cùng một trục. chúng tôi sử dụng plt. hist[] hai lần và sử dụng các tham số, thùng, alpha và màu giống như trong ví dụ trước.  

Để tải xuống và xem tệp CSV được sử dụng, hãy nhấp vào đây.  

Python3

# import all modules

import pandas as pd

import seaborn as sns

import matplotlib.pyplot as plt

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background [use sns.set_theme[] if seaborn version 0.11.0 or above] 
sns.set[style="darkgrid"]
df = sns.load_dataset["iris"]

fig, axs = plt.subplots[2, 2, figsize=[7, 7]]

sns.histplot[data=df, x="sepal_length", kde=True, color="skyblue", ax=axs[0, 0]]
sns.histplot[data=df, x="sepal_width", kde=True, color="olive", ax=axs[0, 1]]
sns.histplot[data=df, x="petal_length", kde=True, color="gold", ax=axs[1, 0]]
sns.histplot[data=df, x="petal_width", kde=True, color="teal", ax=axs[1, 1]]

plt.show[]

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background [use sns.set_theme[] if seaborn version 0.11.0 or above] 
sns.set[style="darkgrid"]
df = sns.load_dataset["iris"]

fig, axs = plt.subplots[2, 2, figsize=[7, 7]]

sns.histplot[data=df, x="sepal_length", kde=True, color="skyblue", ax=axs[0, 0]]
sns.histplot[data=df, x="sepal_width", kde=True, color="olive", ax=axs[0, 1]]
sns.histplot[data=df, x="petal_length", kde=True, color="gold", ax=axs[1, 0]]
sns.histplot[data=df, x="petal_width", kde=True, color="teal", ax=axs[1, 1]]

plt.show[]

matplotlib.pyplot as plt6

import6matplotlib.pyplot as plt8matplotlib.pyplot as plt9import0 1 2import0seaborn as sns5seaborn as sns6import0seaborn as sns8import3

import6

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background [use sns.set_theme[] if seaborn version 0.11.0 or above] 
sns.set[style="darkgrid"]
df = sns.load_dataset["iris"]

fig, axs = plt.subplots[2, 2, figsize=[7, 7]]

sns.histplot[data=df, x="sepal_length", kde=True, color="skyblue", ax=axs[0, 0]]
sns.histplot[data=df, x="sepal_width", kde=True, color="olive", ax=axs[0, 1]]
sns.histplot[data=df, x="petal_length", kde=True, color="gold", ax=axs[1, 0]]
sns.histplot[data=df, x="petal_width", kde=True, color="teal", ax=axs[1, 1]]

plt.show[]

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background [use sns.set_theme[] if seaborn version 0.11.0 or above] 
sns.set[style="darkgrid"]
df = sns.load_dataset["iris"]

fig, axs = plt.subplots[2, 2, figsize=[7, 7]]

sns.histplot[data=df, x="sepal_length", kde=True, color="skyblue", ax=axs[0, 0]]
sns.histplot[data=df, x="sepal_width", kde=True, color="olive", ax=axs[0, 1]]
sns.histplot[data=df, x="petal_length", kde=True, color="gold", ax=axs[1, 0]]
sns.histplot[data=df, x="petal_width", kde=True, color="teal", ax=axs[1, 1]]

plt.show[]

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background [use sns.set_theme[] if seaborn version 0.11.0 or above] 
sns.set[style="darkgrid"]
df = sns.load_dataset["iris"]

fig, axs = plt.subplots[2, 2, figsize=[7, 7]]

sns.histplot[data=df, x="sepal_length", kde=True, color="skyblue", ax=axs[0, 0]]
sns.histplot[data=df, x="sepal_width", kde=True, color="olive", ax=axs[0, 1]]
sns.histplot[data=df, x="petal_length", kde=True, color="gold", ax=axs[1, 0]]
sns.histplot[data=df, x="petal_width", kde=True, color="teal", ax=axs[1, 1]]

plt.show[]

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background [use sns.set_theme[] if seaborn version 0.11.0 or above] 
sns.set[style="darkgrid"]
df = sns.load_dataset["iris"]

fig, axs = plt.subplots[2, 2, figsize=[7, 7]]

sns.histplot[data=df, x="sepal_length", kde=True, color="skyblue", ax=axs[0, 0]]
sns.histplot[data=df, x="sepal_width", kde=True, color="olive", ax=axs[0, 1]]
sns.histplot[data=df, x="petal_length", kde=True, color="gold", ax=axs[1, 0]]
sns.histplot[data=df, x="petal_width", kde=True, color="teal", ax=axs[1, 1]]

plt.show[]

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background [use sns.set_theme[] if seaborn version 0.11.0 or above] 
sns.set[style="darkgrid"]
df = sns.load_dataset["iris"]

fig, axs = plt.subplots[2, 2, figsize=[7, 7]]

sns.histplot[data=df, x="sepal_length", kde=True, color="skyblue", ax=axs[0, 0]]
sns.histplot[data=df, x="sepal_width", kde=True, color="olive", ax=axs[0, 1]]
sns.histplot[data=df, x="petal_length", kde=True, color="gold", ax=axs[1, 0]]
sns.histplot[data=df, x="petal_width", kde=True, color="teal", ax=axs[1, 1]]

plt.show[]

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background [use sns.set_theme[] if seaborn version 0.11.0 or above] 
sns.set[style="darkgrid"]
df = sns.load_dataset["iris"]

fig, axs = plt.subplots[2, 2, figsize=[7, 7]]

sns.histplot[data=df, x="sepal_length", kde=True, color="skyblue", ax=axs[0, 0]]
sns.histplot[data=df, x="sepal_width", kde=True, color="olive", ax=axs[0, 1]]
sns.histplot[data=df, x="petal_length", kde=True, color="gold", ax=axs[1, 0]]
sns.histplot[data=df, x="petal_width", kde=True, color="teal", ax=axs[1, 1]]

plt.show[]

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background [use sns.set_theme[] if seaborn version 0.11.0 or above] 
sns.set[style="darkgrid"]
df = sns.load_dataset["iris"]

fig, axs = plt.subplots[2, 2, figsize=[7, 7]]

sns.histplot[data=df, x="sepal_length", kde=True, color="skyblue", ax=axs[0, 0]]
sns.histplot[data=df, x="sepal_width", kde=True, color="olive", ax=axs[0, 1]]
sns.histplot[data=df, x="petal_length", kde=True, color="gold", ax=axs[1, 0]]
sns.histplot[data=df, x="petal_width", kde=True, color="teal", ax=axs[1, 1]]

plt.show[]

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background [use sns.set_theme[] if seaborn version 0.11.0 or above] 
sns.set[style="darkgrid"]
df = sns.load_dataset["iris"]

fig, axs = plt.subplots[2, 2, figsize=[7, 7]]

sns.histplot[data=df, x="sepal_length", kde=True, color="skyblue", ax=axs[0, 0]]
sns.histplot[data=df, x="sepal_width", kde=True, color="olive", ax=axs[0, 1]]
sns.histplot[data=df, x="petal_length", kde=True, color="gold", ax=axs[1, 0]]
sns.histplot[data=df, x="petal_width", kde=True, color="teal", ax=axs[1, 1]]

plt.show[]

import9

đầu ra

ví dụ 3. Vẽ ba biểu đồ trên cùng một trục

plt. hist[] được sử dụng nhiều lần để tạo một hình gồm ba biểu đồ chồng lên nhau. chúng tôi điều chỉnh độ mờ, màu sắc và số lượng thùng khi cần. Ba cột khác nhau từ khung dữ liệu được lấy làm dữ liệu cho biểu đồ