Seaborn catplot（kind ='count'）将条形图更改为饼形图

Posted 2021-04-13

我在电晕跟踪应用程序上的论文（使用pd.melt）的外观如下：]

    CTQ-tool    opinion
0   Information and awareness purposes  unacceptable
1   Information and awareness purposes  unacceptable
2   Information and awareness purposes  acceptable
3   Information and awareness purposes  acceptable
4   Information and awareness purposes  unacceptable
... ... ...
2827    Central/Local data storage  NaN
2828    Central/Local data storage  NaN
2829    Central/Local data storage  NaN
2830    Central/Local data storage  NaN
2831    Central/Local data storage  NaN
2832 rows × 2 columns

我正在使用Seaborn库进行以下绘制：

代码：

g = sns.catplot("opinion", col="CTQ-tool", col_wrap=4, data=df_original_small, kind="count", height=6.5, aspect=.8)

但是，与其将它们显示在条形图中，不如将它们显示为饼图。 Seaborn.catplot不允许使用kind ='count-pie'。有人知道可以解决吗？

在TiTo问题之后编辑：

这基本上是我希望看到的所有8个条形图都发生的情况：

答案

我最终使用matplotlib库从bottem构建它：

plt.style.use('seaborn') IAP = df_original_small['Information and awareness purposes'].value_counts().to_frame().T QE = df_original_small['Quarantine Enforcement'].value_counts().to_frame().T CTCR = df_original_small['Contact Tracing and Cross-Referencing'].value_counts().to_frame().T VPID = df_original_small['Voluntary provision of infection data'].value_counts().to_frame().T QMA = df_original_small['Quarantine Monitoring App'].value_counts().to_frame().T QRCode = df_original_small['QR code provided registration tracking'].value_counts().to_frame().T total = pd.concat([IAP, QE, CTCR, VPID, QMA, QRCode]) fig, ax = plt.subplots(nrows=3, ncols=2) labels = 'acceptable', 'unacceptable' colors = ['#008fd5', '#fc4f30'] explode = (0, 0.1) explode2 = (0.2, 0) plt.title('Pie chart per CTQ-tool') plt.tight_layout() ax[0,0].pie(total.iloc[[0]], startangle=90, colors=colors, wedgeprops={'edgecolor': 'black'}, autopct='%1.f%%', explode=explode, shadow=True) ax[0,0].set_title('Information and awareness purposes', fontweight='bold') ax[0,1].pie(total.iloc[[1]], startangle=90, colors=colors, wedgeprops={'edgecolor': 'black'}, autopct='%1.f%%', explode=explode, shadow=True) ax[0,1].set_title('Quarantine Enforcement', fontweight='bold') ax[1,0].pie(total.iloc[[2]], startangle=90, colors=colors, wedgeprops={'edgecolor': 'black'}, autopct='%1.f%%', explode=explode2, shadow=True) ax[1,0].set_title('Contact Tracing and Cross-Referencing', fontweight='bold') ax[1,1].pie(total.iloc[[3]], startangle=90, colors=colors, wedgeprops={'edgecolor': 'black'}, autopct='%1.f%%', explode=explode, shadow=True) ax[1,1].set_title('Voluntary provision of infection data', fontweight='bold') ax[2,0].pie(total.iloc[[4]], startangle=90, colors=colors, wedgeprops={'edgecolor': 'black'}, autopct='%1.f%%', explode=explode2, shadow=True) ax[2,0].set_title('Quarantine Monitoring App', fontweight='bold') ax[2,1].pie(total.iloc[[5]], startangle=90, colors=colors, wedgeprops={'edgecolor': 'black'}, autopct='%1.f%%', explode=explode, shadow=True) ax[2,1].set_title('QR code provided registration tracking', fontweight='bold') fig.suptitle('Public Opinion on CTQ-measures', fontsize=20, y=1.07, fontweight='bold', x=0.37) fig.set_figheight(10) fig.set_figwidth(7) fig.legend(loc='best', labels=labels, fontsize='medium') fig.tight_layout() fig.savefig('Opinions_ctq') plt.show()