问答详情
源自:3-3 数据解析和可视化

请问一下,3-3中的csv数据是怎么获得的?去哪里下载?

请问一下,3-3中的csv数据是怎么获得的?去哪里下载?

提问者:浮夸的小蚂蚁 2018-01-09 16:21

个回答

  • qq_Sunshine暖阳_0
    2018-01-12 20:13:34
    已采纳

    5.1,3.5,1.4,0.2,Iris-setosa
    4.9,3.0,1.4,0.2,Iris-setosa
    4.7,3.2,1.3,0.2,Iris-setosa
    4.6,3.1,1.5,0.2,Iris-setosa
    5.0,3.6,1.4,0.2,Iris-setosa
    5.4,3.9,1.7,0.4,Iris-setosa
    4.6,3.4,1.4,0.3,Iris-setosa
    5.0,3.4,1.5,0.2,Iris-setosa
    4.4,2.9,1.4,0.2,Iris-setosa
    4.9,3.1,1.5,0.1,Iris-setosa
    5.4,3.7,1.5,0.2,Iris-setosa
    4.8,3.4,1.6,0.2,Iris-setosa
    4.8,3.0,1.4,0.1,Iris-setosa
    4.3,3.0,1.1,0.1,Iris-setosa
    5.8,4.0,1.2,0.2,Iris-setosa
    5.7,4.4,1.5,0.4,Iris-setosa
    5.4,3.9,1.3,0.4,Iris-setosa
    5.1,3.5,1.4,0.3,Iris-setosa
    5.7,3.8,1.7,0.3,Iris-setosa
    5.1,3.8,1.5,0.3,Iris-setosa
    5.4,3.4,1.7,0.2,Iris-setosa
    5.1,3.7,1.5,0.4,Iris-setosa
    4.6,3.6,1.0,0.2,Iris-setosa
    5.1,3.3,1.7,0.5,Iris-setosa
    4.8,3.4,1.9,0.2,Iris-setosa
    5.0,3.0,1.6,0.2,Iris-setosa
    5.0,3.4,1.6,0.4,Iris-setosa
    5.2,3.5,1.5,0.2,Iris-setosa
    5.2,3.4,1.4,0.2,Iris-setosa
    4.7,3.2,1.6,0.2,Iris-setosa
    4.8,3.1,1.6,0.2,Iris-setosa
    5.4,3.4,1.5,0.4,Iris-setosa
    5.2,4.1,1.5,0.1,Iris-setosa
    5.5,4.2,1.4,0.2,Iris-setosa
    4.9,3.1,1.5,0.1,Iris-setosa
    5.0,3.2,1.2,0.2,Iris-setosa
    5.5,3.5,1.3,0.2,Iris-setosa
    4.9,3.1,1.5,0.1,Iris-setosa
    4.4,3.0,1.3,0.2,Iris-setosa
    5.1,3.4,1.5,0.2,Iris-setosa
    5.0,3.5,1.3,0.3,Iris-setosa
    4.5,2.3,1.3,0.3,Iris-setosa
    4.4,3.2,1.3,0.2,Iris-setosa
    5.0,3.5,1.6,0.6,Iris-setosa
    5.1,3.8,1.9,0.4,Iris-setosa
    4.8,3.0,1.4,0.3,Iris-setosa
    5.1,3.8,1.6,0.2,Iris-setosa
    4.6,3.2,1.4,0.2,Iris-setosa
    5.3,3.7,1.5,0.2,Iris-setosa
    5.0,3.3,1.4,0.2,Iris-setosa
    7.0,3.2,4.7,1.4,Iris-versicolor
    6.4,3.2,4.5,1.5,Iris-versicolor
    6.9,3.1,4.9,1.5,Iris-versicolor
    5.5,2.3,4.0,1.3,Iris-versicolor
    6.5,2.8,4.6,1.5,Iris-versicolor
    5.7,2.8,4.5,1.3,Iris-versicolor
    6.3,3.3,4.7,1.6,Iris-versicolor
    4.9,2.4,3.3,1.0,Iris-versicolor
    6.6,2.9,4.6,1.3,Iris-versicolor
    5.2,2.7,3.9,1.4,Iris-versicolor
    5.0,2.0,3.5,1.0,Iris-versicolor
    5.9,3.0,4.2,1.5,Iris-versicolor
    6.0,2.2,4.0,1.0,Iris-versicolor
    6.1,2.9,4.7,1.4,Iris-versicolor
    5.6,2.9,3.6,1.3,Iris-versicolor
    6.7,3.1,4.4,1.4,Iris-versicolor
    5.6,3.0,4.5,1.5,Iris-versicolor
    5.8,2.7,4.1,1.0,Iris-versicolor
    6.2,2.2,4.5,1.5,Iris-versicolor
    5.6,2.5,3.9,1.1,Iris-versicolor
    5.9,3.2,4.8,1.8,Iris-versicolor
    6.1,2.8,4.0,1.3,Iris-versicolor
    6.3,2.5,4.9,1.5,Iris-versicolor
    6.1,2.8,4.7,1.2,Iris-versicolor
    6.4,2.9,4.3,1.3,Iris-versicolor
    6.6,3.0,4.4,1.4,Iris-versicolor
    6.8,2.8,4.8,1.4,Iris-versicolor
    6.7,3.0,5.0,1.7,Iris-versicolor
    6.0,2.9,4.5,1.5,Iris-versicolor
    5.7,2.6,3.5,1.0,Iris-versicolor
    5.5,2.4,3.8,1.1,Iris-versicolor
    5.5,2.4,3.7,1.0,Iris-versicolor
    5.8,2.7,3.9,1.2,Iris-versicolor
    6.0,2.7,5.1,1.6,Iris-versicolor
    5.4,3.0,4.5,1.5,Iris-versicolor
    6.0,3.4,4.5,1.6,Iris-versicolor
    6.7,3.1,4.7,1.5,Iris-versicolor
    6.3,2.3,4.4,1.3,Iris-versicolor
    5.6,3.0,4.1,1.3,Iris-versicolor
    5.5,2.5,4.0,1.3,Iris-versicolor
    5.5,2.6,4.4,1.2,Iris-versicolor
    6.1,3.0,4.6,1.4,Iris-versicolor
    5.8,2.6,4.0,1.2,Iris-versicolor
    5.0,2.3,3.3,1.0,Iris-versicolor
    5.6,2.7,4.2,1.3,Iris-versicolor
    5.7,3.0,4.2,1.2,Iris-versicolor
    5.7,2.9,4.2,1.3,Iris-versicolor
    6.2,2.9,4.3,1.3,Iris-versicolor
    5.1,2.5,3.0,1.1,Iris-versicolor
    5.7,2.8,4.1,1.3,Iris-versicolor
    6.3,3.3,6.0,2.5,Iris-virginica
    5.8,2.7,5.1,1.9,Iris-virginica
    7.1,3.0,5.9,2.1,Iris-virginica
    6.3,2.9,5.6,1.8,Iris-virginica
    6.5,3.0,5.8,2.2,Iris-virginica
    7.6,3.0,6.6,2.1,Iris-virginica
    4.9,2.5,4.5,1.7,Iris-virginica
    7.3,2.9,6.3,1.8,Iris-virginica
    6.7,2.5,5.8,1.8,Iris-virginica
    7.2,3.6,6.1,2.5,Iris-virginica
    6.5,3.2,5.1,2.0,Iris-virginica
    6.4,2.7,5.3,1.9,Iris-virginica
    6.8,3.0,5.5,2.1,Iris-virginica
    5.7,2.5,5.0,2.0,Iris-virginica
    5.8,2.8,5.1,2.4,Iris-virginica
    6.4,3.2,5.3,2.3,Iris-virginica
    6.5,3.0,5.5,1.8,Iris-virginica
    7.7,3.8,6.7,2.2,Iris-virginica
    7.7,2.6,6.9,2.3,Iris-virginica
    6.0,2.2,5.0,1.5,Iris-virginica
    6.9,3.2,5.7,2.3,Iris-virginica
    5.6,2.8,4.9,2.0,Iris-virginica
    7.7,2.8,6.7,2.0,Iris-virginica
    6.3,2.7,4.9,1.8,Iris-virginica
    6.7,3.3,5.7,2.1,Iris-virginica
    7.2,3.2,6.0,1.8,Iris-virginica
    6.2,2.8,4.8,1.8,Iris-virginica
    6.1,3.0,4.9,1.8,Iris-virginica
    6.4,2.8,5.6,2.1,Iris-virginica
    7.2,3.0,5.8,1.6,Iris-virginica
    7.4,2.8,6.1,1.9,Iris-virginica
    7.9,3.8,6.4,2.0,Iris-virginica
    6.4,2.8,5.6,2.2,Iris-virginica
    6.3,2.8,5.1,1.5,Iris-virginica
    6.1,2.6,5.6,1.4,Iris-virginica
    7.7,3.0,6.1,2.3,Iris-virginica
    6.3,3.4,5.6,2.4,Iris-virginica
    6.4,3.1,5.5,1.8,Iris-virginica
    6.0,3.0,4.8,1.8,Iris-virginica
    6.9,3.1,5.4,2.1,Iris-virginica
    6.7,3.1,5.6,2.4,Iris-virginica
    6.9,3.1,5.1,2.3,Iris-virginica
    5.8,2.7,5.1,1.9,Iris-virginica
    6.8,3.2,5.9,2.3,Iris-virginica
    6.7,3.3,5.7,2.5,Iris-virginica
    6.7,3.0,5.2,2.3,Iris-virginica
    6.3,2.5,5.0,1.9,Iris-virginica
    6.5,3.0,5.2,2.0,Iris-virginica
    6.2,3.4,5.4,2.3,Iris-virginica
    5.9,3.0,5.1,1.8,Iris-virginica

  • Du1in9
    2020-07-19 16:15:03

    数据文件(iris.data.csv):https://graph-bed-1256708472.cos.ap-chengdu.myqcloud.com/pythondata%2Firis.data.csv

    代码:

    import pandas as pd 


    file = "C:/Users/YYDL/Desktop/data.csv"

    # 读取file,第一行不是数据说明

    df = pd.read_csv(file, header = None)

    # 显示文件前十行

    df.head(10)


    import matplotlib.pyplot as plt

    import numpy as np


    # 1)得到数据前一百行的第五列

    y = df.loc[0:100, 4].values

    print(y)


    # 2)将字符串转化为数字-1和1

    y = np.where(y == 'Iris-setosa', -1, 1)

    # 抽取前100条数据的第0列和第2列

    x = df.iloc[0:100, [0, 2]].values

    print(x)


    # 3)scatter散列点绘图

    # 将前50条数据的第0列作为x坐标,第1列作为y坐标,点为红色圆圈

    plt.scatter(x[:50, 0], x[:50, 1], color='red', marker='o', label='setosa')

    # 将后50条数据的第0列作为x坐标,第1列作为y坐标,点为蓝色叉叉

    plt.scatter(x[50:100, 0], x[50:100, 1], color='blue', marker='x', label='versicolor')

    plt.xlabel('X')

    plt.ylabel('Y')

    plt.legend(loc='upper left')

    plt.show()


  • IT有点难
    2018-08-01 19:40:37

    https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data

  • qq_晓歌_0
    2018-05-11 14:21:13

    太谢谢了

  • qq_Sunshine暖阳_0
    2018-01-12 20:08:50

    我也想知道!!

    你现在知道了吗