python做图表的模块有哪些,python如何制作图表

• 花匠小妙招
• 2025-01-11 22:42

40张Python可视化图形

1.熊猫基本花图

import pandas as pd

import matplotlib.pyplot as plt

df = pd.DataFrame([8,8,1,2], index=['a', 'b', 'c', 'd'], columns=['x'])

df.plot(kind='pie', subplots=True, figsize=(8, 8))

plt.show()

2.堆叠面积图的基线选项

import numpy as np

import matplotlib.pyplot as plt

import seaborn as sns

X = np.arange(0, 10, 1)

Y = X + 5 * np.random.random((5, X.size))

baseline = ["zero", "sym", "wiggle", "weighted_wiggle"]

for n, v in enumerate(baseline):

if n<3 :

plt.tick_params(labelbottom='off')

plt.subplot(2 ,2, n + 1)

plt.stackplot(X, *Y, baseline=v)

plt.title(v)

plt.tight_layout()

3.柱形图

import matplotlib.pyplot as plt

height = [3, 12, 5, 18, 45]

bars = ('A', 'B', 'C', 'D', 'E')

x_pos = [0,1,5,8,9]

plt.bar(x_pos, height)

plt.xticks(x_pos, bars)

plt.show()

4.散点图

import matplotlib.pyplot as plt

import numpy as np

import pandas as pd

df=pd.DataFrame({

'x_values': range(1,101), 'y_values': np.random.randn(100)*15+range(1,101) })

plt.plot( 'x_values', 'y_values', data=df, linestyle='none', marker='o')

plt.show()

5.基本气泡图

import matplotlib.pyplot as plt

import numpy as np

x = np.random.rand(40)

y = np.random.rand(40)

z = np.random.rand(40)

plt.scatter(x, y, s=z*1000, alpha=0.5)

plt.show()

6.面积图和饰面

import numpy as np

import seaborn as sns

import matplotlib.pyplot as plt

sns.set_style("whitegrid")

blue, = sns.color_palette("muted", 1)

x = np.arange(23)

y = np.random.randint(8, 20, 23)

fig, ax = plt.subplots()

ax.plot(x, y, color=blue, lw=3)

ax.fill_between(x, 0, y, alpha=.3)

ax.set(xlim=(0, len(x) - 1), ylim=(0, None), xticks=x)

plt.show()

7.自定义matplotlib标题

import matplotlib.pyplot as plt

import numpy as np

x = np.random.normal(size=50000)

y = x * 3 + np.random.normal(size=50000)

plt.hist2d(x, y, bins=(50, 50), cmap=plt.cm.Reds)

plt.title("A 2D histogram")

plt.show()

8.基本甜甜圈图

import matplotlib.pyplot as plt

size_of_groups=[12,11,3,30]

plt.pie(size_of_groups)

my_circle=plt.Circle( (0,0), 0.7, color='white')

p=plt.gcf()

p.gca().add_artist(my_circle)

plt.show()

9.有条件颜色的棒棒糖图

import matplotlib.pyplot as plt

import numpy as np

import seaborn as sns

x = np.linspace(0, 2*np.pi, 100)

y = np.sin(x) + np.random.uniform(size=len(x)) - 0.2

my_color = np.where(y>=0, 'orange', 'skyblue')

plt.vlines(x=x, ymin=0, ymax=y, color=my_color, alpha=0.4)

plt.scatter(x, y, color=my_color, s=1, alpha=1)

plt.title("Evolution of the value of ...", loc='left')

plt.xlabel('Value of the variable')

plt.ylabel('Group')

plt.show(

10.基本堆积面积图

import numpy as np

import matplotlib.pyplot as plt

x=range(1,6)

y=[ [1,4,6,8,9], [2,2,7,10,12], [2,8,5,10,6] ]

plt.stackplot(x,y, labels=['A','B','C'])

plt.legend(loc='upper left')

plt.show()

11.控制堆叠区域图中的颜色

import numpy as np

import matplotlib.pyplot as plt

import seaborn as sns

x = range(1,6)

y = [ [10,4,6,5,3], [12,2,7,10,1], [8,18,5,7,6] ]

pal = sns.color_palette("Set1")

plt.stackplot(x,y, labels=['A','B','C'], colors=pal, alpha=0.4 )

plt.legend(loc='upper right')

pal = ["#9b59b6", "#e74c3c", "#34495e", "#2ecc71"]

plt.stackplot(x,y, labels=['A','B','C'], colors=pal, al

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