karate--deepwalk.embedding 及 karate--node2vec.embedding散点图绘制

一，karate--deepwalk.embedding

# -- coding: utf-8
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
df=pd.read_csv(r"C:\Users\WBL\Desktop\DeepWalk\karate--deepwalk.embedding.csv")  # r为转义字符

fig,ax = plt.subplots(figsize = (8,5),dpi = 70)  #figsize:宽和高比例，dpi：分辨率

# 着色
categories = np.unique(df['category'])
colors = [plt.cm.tab10(i/float(len(categories)-1)) for i in range(len(categories))]
for i, category in enumerate(categories):
    plt.scatter('x', 'y',data=df.loc[df.category==category, :],s=300, cmap=colors[i], label=str(category))


# 为每个点添加标签，一些形如（x轴，y轴，标签）的元组，水平及垂直位置，背景颜色
for x, y, tex in zip(df["x"],df["y"],df["label"]):
    t = plt.text(x, y,tex, horizontalalignment='center',
                 verticalalignment='center', fontdict={'color':'black'})


plt.gca().spines["top"].set_alpha(.9)   #设置最顶那条线的透明度
plt.gca().spines["bottom"].set_alpha(.3)
plt.gca().spines["right"].set_alpha(.3)
plt.gca().spines["left"].set_alpha(.3)


plt.title('karate--deepwalk.embedding', fontdict={'size':20})
plt.grid(linestyle='--', alpha=0.5)
plt.show()

效果图：

# -- coding: utf-8
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
df=pd.read_csv(r"C:\Users\WBL\Desktop\node2vec-master\karate--node2vec.embeddings.csv")  # r为转义字符

fig,ax = plt.subplots(figsize = (15,12),dpi = 70)  #figsize:宽和高比例，dpi：分辨率

# 着色
categories = np.unique(df['category'])
colors = [plt.cm.tab10(i/float(len(categories)-1)) for i in range(len(categories))]
for i, category in enumerate(categories):
    plt.scatter('x', 'y',data=df.loc[df.category==category, :],s=300, cmap=colors[i], label=str(category))


# 为每个点添加标签，一些形如（x轴，y轴，标签）的元组，水平及垂直位置，背景颜色
for x, y, tex in zip(df["x"],df["y"],df["label"]):
    t = plt.text(x, y,tex, horizontalalignment='center',
                 verticalalignment='center', fontdict={'color':'black'})


plt.gca().spines["top"].set_alpha(.9)   #设置最顶那条线的透明度
plt.gca().spines["bottom"].set_alpha(.3)
plt.gca().spines["right"].set_alpha(.3)
plt.gca().spines["left"].set_alpha(.3)


plt.title('karate--node2vec.embeddings', fontdict={'size':20})
plt.grid(linestyle='--', alpha=0.5)
plt.show()