from matplotlib import pyplot as plt
import numpy as np
my_dpi=96
plt.figure(figsize=(480/my_dpi, 480/my_dpi), dpi=my_dpi)
x = np.random.rand(15)
y = x+np.random.rand(15)
z = x+np.random.rand(15)
z=z*z
plt.scatter(x, y, s=z*2000, c=x, cmap="BuPu", alpha=0.4, edgecolors="grey", linewidth=2)
plt.show()
from matplotlib import pyplot as plt
import numpy as np
my_dpi=96
plt.figure(figsize=(480/my_dpi, 480/my_dpi), dpi=my_dpi)
x = np.random.rand(15)
y = x+np.random.rand(15)
z = x+np.random.rand(15)
z=z*z
plt.scatter(x, y, s=z*2000, c=x, cmap="plasma", alpha=0.4, edgecolors="grey", linewidth=2)
plt.show() 
from matplotlib import pyplot as plt
import numpy as np
my_dpi=96
plt.figure(figsize=(480/my_dpi, 480/my_dpi), dpi=my_dpi)
x = np.random.rand(80) - 0.5
y = x+np.random.rand(80)
z = x+np.random.rand(80)
plt.scatter(x, y, s=z*2000, c=x, cmap="PuOr_r", alpha=0.4, edgecolors="grey", linewidth=2)
plt.show() 
from matplotlib import pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
my_dpi=96
plt.figure(figsize=(480/my_dpi, 480/my_dpi), dpi=my_dpi)
df = sns.load_dataset('iris')
df['species']=pd.Categorical(df['species'])
df['species'].cat.codes
plt.scatter(df['sepal_length'], df['sepal_width'], s=62, c=df['species'].cat.codes, cmap="Set1", alpha=0.9, linewidth=0)
plt.show() 
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
df=pd.DataFrame({'x': range(1,11), 'y1': np.random.randn(10), 'y2': np.random.randn(10)+range(1,11), 'y3': np.random.randn(10)+range(11,21), 'y4': np.random.randn(10)+range(6,16), 'y5': np.random.randn(10)+range(4,14), 'y6': np.random.randn(10)+range(2,12), 'y7': np.random.randn(10)+range(5,15), 'y8': np.random.randn(10)+range(4,14) })
possibilities = [u'seaborn-darkgrid', u'seaborn-notebook', u'classic', u'seaborn-ticks', u'grayscale', u'bmh', u'seaborn-talk', u'dark_background', u'ggplot', u'fivethirtyeight', u'_classic_test', u'seaborn-colorblind', u'seaborn-deep', u'seaborn-whitegrid', u'seaborn-bright', u'seaborn-poster', u'seaborn-muted', u'seaborn-paper', u'seaborn-white', u'seaborn-pastel', u'seaborn-dark', u'seaborn', u'seaborn-dark-palette']
my_dpi=96
plt.figure(figsize=(1000/my_dpi, 1000/my_dpi), dpi=my_dpi)
for n, v in enumerate(possibilities):
plt.subplot(5 ,5, n + 1)
for column in df.drop('x', axis=1):
plt.plot(df['x'], df[column], marker='', color='grey', linewidth=1, alpha=0.4)
plt.plot(df['x'], df['y5'], marker='', color='orange', linewidth=4)
plt.title(v, fontsize=10, fontweight=0, color='grey', loc='left')
plt.tick_params(labelbottom='off')
plt.tick_params(labelleft='off')
plt.show() 
The blogger opened a new official account , I hope you can scan the code and pay attention , Thank you very much .
This article is from ：https://github.com/holtzy/The-Python-Graph-Gallery/blob/master/PGG_notebook.py
