用python画Bar chart with error bars叠加scatter plot

 原数据

• data.xlsx (For bar chart)

• data2.xlsx(For scatter plot)

Bar chart with error bars

#!/usr/bin/env python3


import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns


# Enter data
data = pd.read_excel('./data.xlsx')


# Create lists for car plot
materials = ['nsp3', 'nsp5', 'nsp12', 'nsp13', 'nsp16']
x_pos = np.arange(len(materials))
CTEs = [np.mean(data['nsp3']), np.mean(data['nsp5']), np.mean(data['nsp12']), np.mean(data['nsp13']), np.mean(data['nsp16'])]    # Calaulate the average
error = [np.std(data['nsp3']), np.std(data['nsp5']), np.std(data['nsp12']), np.std(data['nsp13']), np.std(data['nsp16'])]    # Calaulate the std


# Build the plot
fig, ax = plt.subplots()
ax.bar(x_pos, CTEs, yerr=error, align='center', width=0.5, alpha=0.5, ecolor='black', capsize=10, color=sns.xkcd_rgb['faded blue'])  # bar with error bars
plt.yticks(fontproperties='Times New Roman', fontsize=12)
ax.set_xticks(x_pos)
ax.set_xticklabels(materials, fontproperties='Times New Roman', fontsize=12)
ax.invert_yaxis()     #翻转y轴负值到x轴上方
ax.set_ylabel('Docking score(kcal/mol)', fontproperties='Times New Roman', fontsize=15, weight='bold')
ax.set_xlabel('Protein', fontproperties='Times New Roman', fontsize=15, weight='bold')
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)


plt.show()

叠加scatter plot(seaborn库)

# Enter data
data2 = pd.read_excel('./data2.xlsx')


# Build the plot
sns.set(style='darkgrid')
sns.swarmplot(x='protein', y='docking score', hue='coronavirus', data=data2, palette='Set2')  
plt.legend(bbox_to_anchor=(1.02, 0.95), loc=2, borderaxespad=0, prop='Times New Roman', fontsize=10)
plt.tight_layout()  


# Save and show the figure
plt.savefig('plot_with_error_bars.png')
plt.show()