处理数据的常见操作

pandas存储数据到csv文件中 import pandas as pd #任意的多组列表 a = [1,2,3] b = [4,5,6] df = pd.DataFrame({'a_name':a,'b_name':b}) #index表示是否显示行名，default=True df.to_csv("test.csv",index=False,sep=',') numpy 提取矩阵的某一行或某一列 行众所周知可以用下标取得，其实就是列比较新奇： arr = np.array([[1, 2, 3], [2, 3, 4]]) # 取行 arr[0] # array([1, 2, 3]) # 取列 arr[:, 0] # array([1, 2]) 案例，从networkx中得到karate.csv数据集 import networkx as nx import pandas as pd import numpy as np def getKarate(): G = nx.karate_club_graph() relationships = [] for node in G.nodes(): neighbors = G.neighbors(node) for v in neighbors: if [node, v] not in relationships and [v, node] not in relationships: relationships.append([node, v]) relationships = np.array(relationships) node1 = list(relationships[:, 0]) # 获取下标0列数据 node2 = list(relationships[:, 1]) # 获取下标1列数据 # 存储数据到csv文件中 df = pd.DataFrame({"node1": node1, "node2": node2}) df.to_csv("Karate.csv", sep=",", index=False) # index表示是否显示行名，default=True if __name__ == '__main__': getKarate()

结果部分截图：