[英]Matplotlib loop through axes in a seaborn plot for multiple subplots
我想在一個海洋直方圖(分布圖)上創建五個子圖(一個數據框的特定列中的每個類別一個)。
我的數據集是:
prog score
cool 1.9
cool 3.7
yay 4.5
yay 2.6
neat 1.4
neat 7
neat 6
wow 4.1
wow 1.7
wow 1.4
hooray 6.6
hooray 5.6
hooray 4.9
yikes 1.2
yikes 3.9
yikes 6.9
我不希望繪制所有 “程序”,而只希望列表中的每個:
prog_list = ['cool', 'yay', 'neat', 'yikes', 'wow']
scores = df['score']
f, axes = plt.subplots(3, 2, figsize=(15, 15))
# Delete last chart since there are only 5 subplots I need
f.delaxes(ax = axes[2,1])
for i, axes in enumerate(f.axes):
scores = df.loc[(df['prog'] == prog_list[i])]['score']
axes = sns.distplot(scores, norm_hist=True, color='b')
sigma = round(scores.std(), 3)
mu = round(scores.mean(), 2)
axes.set_xlim(1,7)
axes.set_xticks(range(2,8))
axes.set_xlabel('Score - Mean: {} (σ {})'.format(mu, sigma))
axes.set_ylabel('Density')
但是,當我這樣做時,它只是將每個子集繪制到相同的圖上(這很酷,但絕對不是我想要的)。
嘗試這個:
# your code use axes and redefine it after every iteration
# I think this would be better
for prog, ax in zip(prog_list, axes.flatten()[:5]):
scores = df.loc[(df['prog'] == prog)]['score']
# note how I put 'ax' here
sns.distplot(scores, norm_hist=True, ax=ax, color='b')
# change all the axes into ax
sigma = round(scores.std(), 3)
mu = round(scores.mean(), 2)
ax.set_xlim(1,7)
ax.set_xticks(range(2,8))
ax.set_xlabel('Score - Mean: {} (σ {})'.format(mu, sigma))
ax.set_ylabel('Density')
plt.show()
輸出:
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