レーダーチャートを作成したいです．

import matplotlib.pyplot as plt
import pandas as pd
import csv

from math import pi


fn = 'yu1.csv'
df = pd.DataFrame({
'group': ['1','2','3','4','5','6','7','8','9','10','11','12','13','14', '15', '16','17','18','19','20','21','22','23','24','25','26','27','28','29','30','31','32','33','34','35','36'],
'var1': [1004.72,445.717,862.441,550.069,848.328,550.067,815.25,739.188,923.845,871.974,886.006,549.924,838.862,706.268,938.187,810.32,824.671,933.573,928.955,1194.19,985.606,1492.45,781.973,928.788,777.108,1194.08,616.147,1421.46,995.02,426.756,1009.43,435.993,923.875,426.812,0,0],
'var2': [1004.72,426.553,862.482,516.789,852.879,521.388,815.141,701.361,933.637,810.522,881.393,512.215,838.862,706.268,938.187,810.32,810.192,900.394,886.111,1184.49,961.972,1478.15,796.163,890.991,777.304,1170.25,639.949,1407.18,995.02,398.15,1009.43,435.993,919.39,398.261,0,0],
'var3': [1004.6,407.834,867.131,493.143,852.879,502.434,815.141,668.288,961.761,772.42,886.006,488.263,838.862,706.268,938.187,810.32,786.683,886.181,838.717,1170.37,886.241,1463.97,805.531,881.328,786.741,1151.4,649.403,1350.29,990.412,388.887,1009.43,435.993,919.278,388.74,0,0],
'var4': [1004.51,426.553,862.482,493.143,852.931,502.434,815.067,654.097,966.61,734.603,881.393,488.263,838.862,706.268,938.187,810.32,767.724,890.919,810.402,1184.49,800.798,1459.25,805.531,886.206,890.911,1113.53,649.403,1350.29,990.236,393.771,1009.43,435.993,914.62,393.594,0,0],
'var5': [999.991,426.553,862.482,493.143,853.194,502.434,810.572,630.487,971.45,701.682,881.307,488.263,838.862,706.268,938.187,810.32,744.057,890.919,777.037,1184.49,696.768,1459.25,805.531,886.206,923.869,1075.48,649.403,1307.59,980.821,393.771,1009.43,435.993,909.906,393.594,0,0],
'var6': [999.782,426.595,852.904,493.143,853.194,502.434,810.572,630.487,990.414,701.642,834.012,488.263,838.862,706.268,935.9456667,810.0963333,744.001,890.919,739.468,1189.26,625.583,1459.25,796.163,886.206,933.686,1042.56,729.828,1189.24,976.095,393.771,1009.43,435.993,909.833,393.594,0,0],
'var7': [999.618,436.296,848.279,507.037,853.144,507.13,810.572,630.487,999.845,701.642,819.92,493.098,838.862,706.268,933.7043333,809.8726667,734.466,909.862,710.86,1194.09,568.794,1459.29,777.394,900.319,961.718,1032.96,767.634,1189.41,971.601,412.48,1009.43,435.993,905.121,403.219,0,0],
'var8': [995.008,464.611,843.506,512.124,853.194,516.664,810.572,630.487,1004.53,701.642,815.103,502.56,838.862,706.268,931.463,809.649,734.419,923.938,696.72,1194.1,559.34,1463.97,777.26,909.822,966.625,1028.25,767.771,1156.28,971.505,436.092,1009.43,435.993,905.121,431.623,0,0],
'var9': [995.008,478.915,843.417,544.984,857.668,544.958,815.047,658.766,1004.53,701.642,814.998,531.003,838.862,706.268,929.2216667,809.4253333,715.696,938.213,692.032,1203.46,549.831,1468.76,772.634,924.114,966.625,1028.25,786.638,1189.41,971.505,459.956,1009.43,435.993,905.121,450.398,0,0],
'var10': [995.008,497.657,843.417,550.113,857.668,554.643,819.837,668.44,1004.53,729.824,814.993,545.097,838.862,706.268,926.9803333,809.2016667,706.269,947.716,692.032,1203.5,549.803,1482.94,772.61,928.78,966.625,1028.25,786.638,1189.41,971.505,469.343,1009.43,435.993,905.121,469.182,0,0],
'var11': [995.008,507.375,843.417,559.395,857.668,568.762,824.692,696.543,1004.53,744.211,814.993,549.954,838.862,706.268,924.739,808.978,706.269,952.453,692.032,1203.57,549.803,1487.48,772.61,933.514,966.625,1028.25,824.539,1264.85,971.505,478.863,1009.43,435.993,914.497,474.073,0,0],
'var12': [999.585,512.088,843.417,564.085,857.923,573.653,829.24,701.381,1004.52,772.284,814.993,554.546,838.862,706.268,922.4976667,808.7543333,706.269,957.264,692.032,1222.31,549.803,1487.56,772.601,942.981,961.841,1047.26,886.194,1326.58,980.854,488.278,1009.43,435.993,919.184,474.394,0,0],
'var13': [999.776,516.729,843.602,573.494,862.55,582.848,829.36,701.578,999.969,777.416,814.993,559.299,838.862,706.268,920.2563333,808.5306667,706.269,961.925,696.603,1227.04,549.831,1487.61,772.61,947.766,957.012,1080.44,924.19,1373.97,990.23,502.329,1009.43,435.993,923.983,488.233,0,0],
'var14': [1004.46,535.647,848.2,582.941,867.278,587.593,838.783,729.707,999.938,796.247,815.009,573.493,838.862,706.268,918.015,808.307,725.103,971.476,701.53,1231.82,549.949,1487.61,772.61,966.56,957.012,1118.06,966.816,1411.7,999.533,507.248,1009.43,435.993,924.101,493.046,0,0],



})

def make_spider(nrows, ncols, index, color, label=None, title=None, ax=None):
    categories=list(df)[1:]
    N = len(categories)

    angles = [n / float(N) * 2 * pi for n in range(N)]
    angles += angles[:1]

    if ax == None:
        ax = plt.subplot(nrows, ncols, index+1, polar=True)

    ax.set_theta_offset(pi / 2)
    ax.set_theta_direction(-1)

    plt.xticks(angles[:-1], categories, color='grey', size=8)

    ax.set_rlabel_position(0)
    plt.yticks([10,20,30], ["10","20","30"], color="grey", size=7)
    plt.ylim(0,40)

    values=df.loc[row].drop('group').values.flatten().tolist()
    values += values[:1]
    ax.plot(angles, values, color=color, linewidth=2, linestyle='solid', label=label)
    ax.fill(angles, values, color=color, alpha=0.4)

    if title:
        plt.title(title, size=11, color=color, y=1.1)

my_dpi=96
plt.figure(figsize=(1000/my_dpi, 1000/my_dpi), dpi=my_dpi)

my_palette = plt.cm.get_cmap("Set2", len(df.index))

nr, nc = 3, 2
for row in range(0, len(df.index)):
    make_spider(nr, nc, row, title='group '+df['group'][row], color=my_palette(row))
plt.show()
   

n![イメージ説明](4f1015522c017e526366073afac7080a.png)= 3, 2
for row in range(0, len(df.index)):
    make_spider(nr, nc, row, title='group '+df['group'][row], color=my_palette(row))
plt.show()

ValueError: num must be 1 <= num <= 6, not 7

円は1つにしたいのですが，6つできてしまいます．

csvファイルの横の数と縦の数を無理やり合わせているのですが，合わせずできる方法はありますでしょうか？
理想の図はこんな感じです．

tiitoi

2019/07/24 08:20

make_spider はどこで定義されているのでしょうか？コピペで完全に動作するコードを貼ってください。

退会済みユーザー

2019/07/24 09:38

訂正しました．よろしくお願いいたします．

tiitoi

2019/07/24 09:48

データフレームは36行14列あると思いますが、行ごとに14個の指標のレーダーチャートを作成したいということでしょうか？

退会済みユーザー

2019/07/24 10:14

はい，そのようにしたいと思っています．縦の順番でレーダーチャートを作成したいと思っています．よろしくお願いいたします．

行動規範の内容に同意します

回答1件

ベストアンサー

縦の順番でレーダーチャートを作成したいと思っています．よろしくお願いいたします．

以下のような意図であっていますでしょうか。
行ごとに var1 ~ 14 の14項目のレーダーチャートを1つ作成しています。

python
1import matplotlib.pyplot as plt
2import numpy as np
3import pandas as pd
4
5df = pd.DataFrame({
6'group': ['1','2','3','4','5','6','7','8','9','10','11','12','13','14', '15', '16','17','18','19','20','21','22','23','24','25','26','27','28','29','30','31','32','33','34','35','36'],
7'var1': [1004.72,445.717,862.441,550.069,848.328,550.067,815.25,739.188,923.845,871.974,886.006,549.924,838.862,706.268,938.187,810.32,824.671,933.573,928.955,1194.19,985.606,1492.45,781.973,928.788,777.108,1194.08,616.147,1421.46,995.02,426.756,1009.43,435.993,923.875,426.812,0,0],
8'var2': [1004.72,426.553,862.482,516.789,852.879,521.388,815.141,701.361,933.637,810.522,881.393,512.215,838.862,706.268,938.187,810.32,810.192,900.394,886.111,1184.49,961.972,1478.15,796.163,890.991,777.304,1170.25,639.949,1407.18,995.02,398.15,1009.43,435.993,919.39,398.261,0,0],
9'var3': [1004.6,407.834,867.131,493.143,852.879,502.434,815.141,668.288,961.761,772.42,886.006,488.263,838.862,706.268,938.187,810.32,786.683,886.181,838.717,1170.37,886.241,1463.97,805.531,881.328,786.741,1151.4,649.403,1350.29,990.412,388.887,1009.43,435.993,919.278,388.74,0,0],
10'var4': [1004.51,426.553,862.482,493.143,852.931,502.434,815.067,654.097,966.61,734.603,881.393,488.263,838.862,706.268,938.187,810.32,767.724,890.919,810.402,1184.49,800.798,1459.25,805.531,886.206,890.911,1113.53,649.403,1350.29,990.236,393.771,1009.43,435.993,914.62,393.594,0,0],
11'var5': [999.991,426.553,862.482,493.143,853.194,502.434,810.572,630.487,971.45,701.682,881.307,488.263,838.862,706.268,938.187,810.32,744.057,890.919,777.037,1184.49,696.768,1459.25,805.531,886.206,923.869,1075.48,649.403,1307.59,980.821,393.771,1009.43,435.993,909.906,393.594,0,0],
12'var6': [999.782,426.595,852.904,493.143,853.194,502.434,810.572,630.487,990.414,701.642,834.012,488.263,838.862,706.268,935.9456667,810.0963333,744.001,890.919,739.468,1189.26,625.583,1459.25,796.163,886.206,933.686,1042.56,729.828,1189.24,976.095,393.771,1009.43,435.993,909.833,393.594,0,0],
13'var7': [999.618,436.296,848.279,507.037,853.144,507.13,810.572,630.487,999.845,701.642,819.92,493.098,838.862,706.268,933.7043333,809.8726667,734.466,909.862,710.86,1194.09,568.794,1459.29,777.394,900.319,961.718,1032.96,767.634,1189.41,971.601,412.48,1009.43,435.993,905.121,403.219,0,0],
14'var8': [995.008,464.611,843.506,512.124,853.194,516.664,810.572,630.487,1004.53,701.642,815.103,502.56,838.862,706.268,931.463,809.649,734.419,923.938,696.72,1194.1,559.34,1463.97,777.26,909.822,966.625,1028.25,767.771,1156.28,971.505,436.092,1009.43,435.993,905.121,431.623,0,0],
15'var9': [995.008,478.915,843.417,544.984,857.668,544.958,815.047,658.766,1004.53,701.642,814.998,531.003,838.862,706.268,929.2216667,809.4253333,715.696,938.213,692.032,1203.46,549.831,1468.76,772.634,924.114,966.625,1028.25,786.638,1189.41,971.505,459.956,1009.43,435.993,905.121,450.398,0,0],
16'var10': [995.008,497.657,843.417,550.113,857.668,554.643,819.837,668.44,1004.53,729.824,814.993,545.097,838.862,706.268,926.9803333,809.2016667,706.269,947.716,692.032,1203.5,549.803,1482.94,772.61,928.78,966.625,1028.25,786.638,1189.41,971.505,469.343,1009.43,435.993,905.121,469.182,0,0],
17'var11': [995.008,507.375,843.417,559.395,857.668,568.762,824.692,696.543,1004.53,744.211,814.993,549.954,838.862,706.268,924.739,808.978,706.269,952.453,692.032,1203.57,549.803,1487.48,772.61,933.514,966.625,1028.25,824.539,1264.85,971.505,478.863,1009.43,435.993,914.497,474.073,0,0],
18'var12': [999.585,512.088,843.417,564.085,857.923,573.653,829.24,701.381,1004.52,772.284,814.993,554.546,838.862,706.268,922.4976667,808.7543333,706.269,957.264,692.032,1222.31,549.803,1487.56,772.601,942.981,961.841,1047.26,886.194,1326.58,980.854,488.278,1009.43,435.993,919.184,474.394,0,0],
19'var13': [999.776,516.729,843.602,573.494,862.55,582.848,829.36,701.578,999.969,777.416,814.993,559.299,838.862,706.268,920.2563333,808.5306667,706.269,961.925,696.603,1227.04,549.831,1487.61,772.61,947.766,957.012,1080.44,924.19,1373.97,990.23,502.329,1009.43,435.993,923.983,488.233,0,0],
20'var14': [1004.46,535.647,848.2,582.941,867.278,587.593,838.783,729.707,999.938,796.247,815.009,573.493,838.862,706.268,918.015,808.307,725.103,971.476,701.53,1231.82,549.949,1487.61,772.61,966.56,957.012,1118.06,966.816,1411.7,999.533,507.248,1009.43,435.993,924.101,493.046,0,0]})
21
22def make_spider(nrows, ncols, df, index, color, title):
23    categories = df.columns[1:]
24
25    angles = np.linspace(0, np.pi * 2, len(categories) + 1)
26    angles += angles[:1]
27
28    ax = plt.subplot(nrows, ncols, index + 1, polar=True)
29
30    # 角度の目盛を設定する。
31    ax.set_xticks(angles[:-1])
32    ax.set_xticklabels(categories, color="grey", size=8)
33
34    # 半径の目盛を設定する。
35    ax.set_yticks([10, 20, 30])
36    ax.set_yticklabels([10, 20, 30], color="grey", size=8)
37    ax.set_ylim(0, 40)
38
39    values = df.iloc[index].drop("group").values.flatten().tolist()
40    values += values[:1]
41
42    ax.fill(angles, values, color=color, alpha=0.4)
43    ax.set_title(title, size=11, color=color, y=1.1)
44
45
46fig = plt.figure(figsize=(12, 30), facecolor="w")
47fig.subplots_adjust(wspace=0.3, hspace=0.2)
48
49my_palette = plt.cm.get_cmap("Set2", len(df.index))
50
51ncols = 4
52nrows = int(len(df.index) / ncols + 0.5)
53
54for i in range(len(df.index)):
55    group = df["group"].iloc[i]
56    color = my_palette(i)
57    make_spider(nrows, ncols, df, i, title=f"group {group}", color=color)
58
59plt.show()