{"id":1087919,"date":"2025-01-08T13:39:35","date_gmt":"2025-01-08T05:39:35","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1087919.html"},"modified":"2025-01-08T13:39:37","modified_gmt":"2025-01-08T05:39:37","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e7%bb%98%e5%88%b6%e6%95%b0%e6%8d%ae%e5%88%86%e6%9e%90%e5%9b%be-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1087919.html","title":{"rendered":"\u5982\u4f55\u7528python\u7ed8\u5236\u6570\u636e\u5206\u6790\u56fe"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u7ed8\u5236\u6570\u636e\u5206\u6790\u56fe\"<\/p>\n

\u5982\u4f55\u7528Python\u7ed8\u5236\u6570\u636e\u5206\u6790\u56fe<\/strong><\/p>\n<\/p>\n

\u4f7f\u7528Python\u7ed8\u5236\u6570\u636e\u5206\u6790\u56fe\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u51e0\u79cd\u5e38\u89c1\u7684\u65b9\u6cd5\u5b9e\u73b0\uff1a\u4f7f\u7528Matplotlib\u3001Seaborn\u3001Pandas\u7b49\u5e93\u3002Matplotlib\u3001Seaborn\u3001Pandas<\/strong>\u662f\u6700\u5e38\u7528\u7684\u5e93\uff0c\u5c24\u5176\u662fMatplotlib\u548cSeaborn\uff0c\u56e0\u4e3a\u5b83\u4eec\u63d0\u4f9b\u4e86\u5e7f\u6cdb\u7684\u529f\u80fd\u548c\u7075\u6d3b\u6027\u3002\u672c\u6587\u5c06\u91cd\u70b9\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u5e93\u7ed8\u5236\u5404\u79cd\u6570\u636e\u5206\u6790\u56fe\uff0c\u5e76\u8be6\u7ec6\u89e3\u91ca\u5176\u4e2d\u7684\u4e00\u4e2a\u2014\u2014Matplotlib\u7684\u4f7f\u7528\u3002<\/p>\n<\/p>\n

\u4e00\u3001Matplotlib<\/h3>\n<\/p>\n

Matplotlib\u662fPython\u4e2d\u6700\u6d41\u884c\u7684\u6570\u636e\u53ef\u89c6\u5316\u5e93\u4e4b\u4e00\u3002\u5b83\u63d0\u4f9b\u4e86\u4e00\u79cd\u7b80\u5355\u800c\u7075\u6d3b\u7684\u65b9\u5f0f\u6765\u521b\u5efa\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u8868\u3002<\/p>\n<\/p>\n

1\u3001\u5b89\u88c5\u548c\u5bfc\u5165Matplotlib<\/h4>\n<\/p>\n

\u5728\u4f7f\u7528Matplotlib\u4e4b\u524d\uff0c\u4f60\u9700\u8981\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86\u5b83\u3002\u4f60\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5Matplotlib\uff1a<\/p>\n<\/p>\n

pip install matplotlib<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u7ed8\u5236\u57fa\u672c\u56fe\u8868<\/h4>\n<\/p>\n
Matplotlib\u652f\u6301\u591a\u79cd\u7c7b\u578b\u7684\u56fe\u8868\uff0c\u5305\u62ec\u6298\u7ebf\u56fe\u3001\u67f1\u72b6\u56fe\u3001\u6563\u70b9\u56fe\u3001\u997c\u56fe\u7b49\u3002\u6211\u4eec\u5c06\u9010\u4e00\u4ecb\u7ecd\u5b83\u4eec\u7684\u4f7f\u7528\u65b9\u6cd5\u3002<\/p>\n<\/p>\n
\u6298\u7ebf\u56fe<\/strong><\/p>\n
\u6298\u7ebf\u56fe\u7528\u4e8e\u663e\u793a\u6570\u636e\u968f\u65f6\u95f4\u53d8\u5316\u7684\u8d8b\u52bf\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u6298\u7ebf\u56fe\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
x = [1, 2, 3, 4, 5]<\/p>\n
y = [2, 3, 5, 7, 11]<\/p>\n
\u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\n
plt.plot(x, y)<\/p>\n
\u6dfb\u52a0\u6807\u9898\u548c\u6807\u7b7e<\/strong><\/h2>\n
plt.title('Simple Line Plot')<\/p>\n
plt.xlabel('X-axis')<\/p>\n
plt.ylabel('Y-axis')<\/p>\n
\u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u5b9a\u4e49\u4e86x\u548cy\u6570\u636e\uff0c\u7136\u540e\u4f7f\u7528plt.plot()<\/code>\u51fd\u6570\u7ed8\u5236\u6298\u7ebf\u56fe\uff0c\u6700\u540e\u4f7f\u7528plt.show()<\/code>\u663e\u793a\u56fe\u8868\u3002<\/p>\n<\/p>\n
\u67f1\u72b6\u56fe<\/strong><\/p>\n
\u67f1\u72b6\u56fe\u7528\u4e8e\u6bd4\u8f83\u4e0d\u540c\u7c7b\u522b\u7684\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u67f1\u72b6\u56fe\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
categories = ['A', 'B', 'C', 'D', 'E']<\/p>\n
values = [3, 7, 5, 6, 9]<\/p>\n
\u7ed8\u5236\u67f1\u72b6\u56fe<\/strong><\/h2>\n
plt.bar(categories, values)<\/p>\n
\u6dfb\u52a0\u6807\u9898\u548c\u6807\u7b7e<\/strong><\/h2>\n
plt.title('Simple Bar Plot')<\/p>\n
plt.xlabel('Categories')<\/p>\n
plt.ylabel('Values')<\/p>\n
\u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528plt.bar()<\/code>\u51fd\u6570\u7ed8\u5236\u67f1\u72b6\u56fe\u3002<\/p>\n<\/p>\n
\u6563\u70b9\u56fe<\/strong><\/p>\n
\u6563\u70b9\u56fe\u7528\u4e8e\u663e\u793a\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u6563\u70b9\u56fe\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
x = [1, 2, 3, 4, 5]<\/p>\n
y = [2, 3, 5, 7, 11]<\/p>\n
\u7ed8\u5236\u6563\u70b9\u56fe<\/strong><\/h2>\n
plt.scatter(x, y)<\/p>\n
\u6dfb\u52a0\u6807\u9898\u548c\u6807\u7b7e<\/strong><\/h2>\n
plt.title('Simple Scatter Plot')<\/p>\n
plt.xlabel('X-axis')<\/p>\n
plt.ylabel('Y-axis')<\/p>\n
\u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528plt.scatter()<\/code>\u51fd\u6570\u7ed8\u5236\u6563\u70b9\u56fe\u3002<\/p>\n<\/p>\n
\u997c\u56fe<\/strong><\/p>\n
\u997c\u56fe\u7528\u4e8e\u663e\u793a\u6570\u636e\u7684\u7ec4\u6210\u90e8\u5206\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u997c\u56fe\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
labels = ['A', 'B', 'C', 'D']<\/p>\n
sizes = [15, 30, 45, 10]<\/p>\n
\u7ed8\u5236\u997c\u56fe<\/strong><\/h2>\n
plt.pie(sizes, labels=labels, autopct='%1.1f%%')<\/p>\n
\u6dfb\u52a0\u6807\u9898<\/strong><\/h2>\n
plt.title('Simple Pie Chart')<\/p>\n
\u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528plt.pie()<\/code>\u51fd\u6570\u7ed8\u5236\u997c\u56fe\uff0c\u5e76\u4f7f\u7528autopct<\/code>\u53c2\u6570\u663e\u793a\u6bcf\u4e2a\u90e8\u5206\u7684\u767e\u5206\u6bd4\u3002<\/p>\n<\/p>\n
\u4e8c\u3001Seaborn<\/h3>\n<\/p>\n
Seaborn\u662f\u57fa\u4e8eMatplotlib\u4e4b\u4e0a\u7684\u9ad8\u7ea7\u6570\u636e\u53ef\u89c6\u5316\u5e93\uff0c\u63d0\u4f9b\u4e86\u66f4\u7b80\u6d01\u3001\u66f4\u7f8e\u89c2\u7684\u56fe\u8868\u7ed8\u5236\u63a5\u53e3\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5\u548c\u5bfc\u5165Seaborn<\/h4>\n<\/p>\n
\u5728\u4f7f\u7528Seaborn\u4e4b\u524d\uff0c\u4f60\u9700\u8981\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86\u5b83\u3002\u4f60\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5Seaborn\uff1a<\/p>\n<\/p>\n
pip install seaborn<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165\uff1a<\/p>\n<\/p>\n
import seaborn as sns<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u7ed8\u5236\u57fa\u672c\u56fe\u8868<\/h4>\n<\/p>\n
Seaborn\u652f\u6301\u591a\u79cd\u7c7b\u578b\u7684\u56fe\u8868\uff0c\u5305\u62ec\u5206\u7c7b\u56fe\u3001\u5206\u5e03\u56fe\u3001\u56de\u5f52\u56fe\u7b49\u3002\u6211\u4eec\u5c06\u9010\u4e00\u4ecb\u7ecd\u5b83\u4eec\u7684\u4f7f\u7528\u65b9\u6cd5\u3002<\/p>\n<\/p>\n
\u5206\u7c7b\u56fe<\/strong><\/p>\n
\u5206\u7c7b\u56fe\u7528\u4e8e\u663e\u793a\u4e0d\u540c\u7c7b\u522b\u7684\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u5206\u7c7b\u56fe\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import seaborn as sns<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
tips = sns.load_dataset('tips')<\/p>\n
\u7ed8\u5236\u5206\u7c7b\u56fe<\/strong><\/h2>\n
sns.catplot(x='day', y='total_bill', data=tips)<\/p>\n
\u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528sns.load_dataset()<\/code>\u51fd\u6570\u52a0\u8f7d\u793a\u4f8b\u6570\u636e\u96c6\uff0c\u7136\u540e\u4f7f\u7528sns.catplot()<\/code>\u51fd\u6570\u7ed8\u5236\u5206\u7c7b\u56fe\u3002<\/p>\n<\/p>\n
\u5206\u5e03\u56fe<\/strong><\/p>\n
\u5206\u5e03\u56fe\u7528\u4e8e\u663e\u793a\u6570\u636e\u7684\u5206\u5e03\u60c5\u51b5\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u5206\u5e03\u56fe\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import seaborn as sns<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
tips = sns.load_dataset('tips')<\/p>\n
\u7ed8\u5236\u5206\u5e03\u56fe<\/strong><\/h2>\n
sns.histplot(tips['total_bill'])<\/p>\n
\u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528sns.histplot()<\/code>\u51fd\u6570\u7ed8\u5236\u5206\u5e03\u56fe\u3002<\/p>\n<\/p>\n
\u56de\u5f52\u56fe<\/strong><\/p>\n
\u56de\u5f52\u56fe\u7528\u4e8e\u663e\u793a\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u56de\u5f52\u56fe\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import seaborn as sns<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
tips = sns.load_dataset('tips')<\/p>\n
\u7ed8\u5236\u56de\u5f52\u56fe<\/strong><\/h2>\n
sns.lmplot(x='total_bill', y='tip', data=tips)<\/p>\n
\u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528sns.lmplot()<\/code>\u51fd\u6570\u7ed8\u5236\u56de\u5f52\u56fe\u3002<\/p>\n<\/p>\n
\u4e09\u3001Pandas<\/h3>\n<\/p>\n
Pandas\u662fPython\u4e2d\u6700\u6d41\u884c\u7684\u6570\u636e\u5904\u7406\u5e93\u4e4b\u4e00\u3002\u5b83\u4e0d\u4ec5\u53ef\u4ee5\u5904\u7406\u548c\u5206\u6790\u6570\u636e\uff0c\u8fd8\u63d0\u4f9b\u4e86\u7b80\u5355\u7684\u56fe\u8868\u7ed8\u5236\u63a5\u53e3\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5\u548c\u5bfc\u5165Pandas<\/h4>\n<\/p>\n
\u5728\u4f7f\u7528Pandas\u4e4b\u524d\uff0c\u4f60\u9700\u8981\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86\u5b83\u3002\u4f60\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5Pandas\uff1a<\/p>\n<\/p>\n
pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u7ed8\u5236\u57fa\u672c\u56fe\u8868<\/h4>\n<\/p>\n
Pandas\u652f\u6301\u591a\u79cd\u7c7b\u578b\u7684\u56fe\u8868\uff0c\u5305\u62ec\u6298\u7ebf\u56fe\u3001\u67f1\u72b6\u56fe\u3001\u6563\u70b9\u56fe\u7b49\u3002\u6211\u4eec\u5c06\u9010\u4e00\u4ecb\u7ecd\u5b83\u4eec\u7684\u4f7f\u7528\u65b9\u6cd5\u3002<\/p>\n<\/p>\n
\u6298\u7ebf\u56fe<\/strong><\/p>\n
\u6298\u7ebf\u56fe\u7528\u4e8e\u663e\u793a\u6570\u636e\u968f\u65f6\u95f4\u53d8\u5316\u7684\u8d8b\u52bf\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u6298\u7ebf\u56fe\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
data = {'x': [1, 2, 3, 4, 5], 'y': [2, 3, 5, 7, 11]}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
\u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\n
df.plot(x='x', y='y', kind='line')<\/p>\n
\u6dfb\u52a0\u6807\u9898\u548c\u6807\u7b7e<\/strong><\/h2>\n
plt.title('Simple Line Plot')<\/p>\n
plt.xlabel('X-axis')<\/p>\n
plt.ylabel('Y-axis')<\/p>\n
\u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u521b\u5efa\u4e00\u4e2aDataFrame\uff0c\u7136\u540e\u4f7f\u7528df.plot()<\/code>\u51fd\u6570\u7ed8\u5236\u6298\u7ebf\u56fe\u3002<\/p>\n<\/p>\n
\u67f1\u72b6\u56fe<\/strong><\/p>\n
\u67f1\u72b6\u56fe\u7528\u4e8e\u6bd4\u8f83\u4e0d\u540c\u7c7b\u522b\u7684\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u67f1\u72b6\u56fe\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
data = {'categories': ['A', 'B', 'C', 'D', 'E'], 'values': [3, 7, 5, 6, 9]}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
\u7ed8\u5236\u67f1\u72b6\u56fe<\/strong><\/h2>\n
df.plot(x='categories', y='values', kind='bar')<\/p>\n
\u6dfb\u52a0\u6807\u9898\u548c\u6807\u7b7e<\/strong><\/h2>\n
plt.title('Simple Bar Plot')<\/p>\n
plt.xlabel('Categories')<\/p>\n
plt.ylabel('Values')<\/p>\n
\u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528df.plot()<\/code>\u51fd\u6570\u7ed8\u5236\u67f1\u72b6\u56fe\u3002<\/p>\n<\/p>\n
\u6563\u70b9\u56fe<\/strong><\/p>\n
\u6563\u70b9\u56fe\u7528\u4e8e\u663e\u793a\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u6563\u70b9\u56fe\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
data = {'x': [1, 2, 3, 4, 5], 'y': [2, 3, 5, 7, 11]}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
\u7ed8\u5236\u6563\u70b9\u56fe<\/strong><\/h2>\n
df.plot(x='x', y='y', kind='scatter')<\/p>\n
\u6dfb\u52a0\u6807\u9898\u548c\u6807\u7b7e<\/strong><\/h2>\n
plt.title('Simple Scatter Plot')<\/p>\n
plt.xlabel('X-axis')<\/p>\n
plt.ylabel('Y-axis')<\/p>\n
\u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528df.plot()<\/code>\u51fd\u6570\u7ed8\u5236\u6563\u70b9\u56fe\u3002<\/p>\n<\/p>\n
\u56db\u3001\u7efc\u5408\u793a\u4f8b<\/h3>\n<\/p>\n
\u6700\u540e\uff0c\u6211\u4eec\u5c06\u7ed3\u5408Matplotlib\u3001Seaborn\u548cPandas\uff0c\u5c55\u793a\u4e00\u4e2a\u7efc\u5408\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u5728\u4e00\u4e2a\u9879\u76ee\u4e2d\u4f7f\u7528\u8fd9\u4e9b\u5e93\u8fdb\u884c\u6570\u636e\u5206\u6790\u548c\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
import seaborn as sns<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
data = {<\/p>\n
    'A': [1, 2, 3, 4, 5],<\/p>\n
    'B': [2, 3, 5, 7, 11],<\/p>\n
    'C': [1, 4, 9, 16, 25]<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
\u4f7f\u7528Pandas\u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\n
df.plot(kind='line')<\/p>\n
plt.title('Line Plot with Pandas')<\/p>\n
plt.show()<\/p>\n
\u4f7f\u7528Seaborn\u7ed8\u5236\u5206\u7c7b\u56fe<\/strong><\/h2>\n
sns.catplot(x='A', y='B', data=df)<\/p>\n
plt.title('Categorical Plot with Seaborn')<\/p>\n
plt.show()<\/p>\n
\u4f7f\u7528Matplotlib\u7ed8\u5236\u6563\u70b9\u56fe<\/strong><\/h2>\n
plt.scatter(df['A'], df['C'])<\/p>\n
plt.title('Scatter Plot with Matplotlib')<\/p>\n
plt.xlabel('A')<\/p>\n
plt.ylabel('C')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u7efc\u5408\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u521b\u5efa\u4e00\u4e2aDataFrame\uff0c\u63a5\u7740\u4f7f\u7528Pandas\u7ed8\u5236\u6298\u7ebf\u56fe\uff0c\u4f7f\u7528Seaborn\u7ed8\u5236\u5206\u7c7b\u56fe\uff0c\u6700\u540e\u4f7f\u7528Matplotlib\u7ed8\u5236\u6563\u70b9\u56fe\u3002\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u53ef\u4ee5\u5145\u5206\u5229\u7528\u4e0d\u540c\u5e93\u7684\u4f18\u52bf\uff0c\u5b8c\u6210\u590d\u6742\u7684\u6570\u636e\u5206\u6790\u548c\u53ef\u89c6\u5316\u4efb\u52a1\u3002<\/p>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u7684\u4ecb\u7ecd\u548c\u793a\u4f8b\uff0c\u4f60\u5e94\u8be5\u80fd\u591f\u638c\u63e1\u5982\u4f55\u4f7f\u7528Python\u4e2d\u7684Matplotlib\u3001Seaborn\u548cPandas\u5e93\u7ed8\u5236\u5404\u79cd\u6570\u636e\u5206\u6790\u56fe\u8868\u3002\u5e0c\u671b\u8fd9\u4e9b\u5185\u5bb9\u80fd\u5bf9\u4f60\u5728\u5b9e\u9645\u9879\u76ee\u4e2d\u5e94\u7528\u6570\u636e\u53ef\u89c6\u5316\u6280\u672f\u6709\u6240\u5e2e\u52a9\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u9009\u62e9\u5408\u9002\u7684\u5e93\u6765\u7ed8\u5236\u6570\u636e\u5206\u6790\u56fe\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u6709\u51e0\u4e2a\u6d41\u884c\u7684\u7ed8\u56fe\u5e93\u53ef\u4f9b\u9009\u62e9\uff0c\u5982Matplotlib\u3001Seaborn\u548cPlotly\u3002Matplotlib\u662f\u57fa\u7840\u5e93\uff0c\u9002\u5408\u521d\u5b66\u8005\u548c\u7b80\u5355\u56fe\u8868\uff1bSeaborn\u6784\u5efa\u5728Matplotlib\u4e4b\u4e0a\uff0c\u63d0\u4f9b\u66f4\u7f8e\u89c2\u7684\u7edf\u8ba1\u56fe\u8868\uff0c\u7279\u522b\u9002\u5408\u5904\u7406\u590d\u6742\u6570\u636e\u5173\u7cfb\uff1bPlotly\u5219\u9002\u5408\u4e92\u52a8\u56fe\u8868\uff0c\u9002\u7528\u4e8e\u9700\u8981\u5728\u7f51\u9875\u4e0a\u5c55\u793a\u56fe\u5f62\u7684\u573a\u666f\u3002\u9009\u62e9\u65f6\u53ef\u4ee5\u6839\u636e\u6570\u636e\u7684\u590d\u6742\u6027\u548c\u5c55\u793a\u9700\u6c42\u6765\u51b3\u5b9a\u3002<\/p>\n
\u7ed8\u5236\u6570\u636e\u5206\u6790\u56fe\u7684\u57fa\u672c\u6b65\u9aa4\u662f\u4ec0\u4e48\uff1f<\/strong>
\u7ed8\u5236\u6570\u636e\u5206\u6790\u56fe\u7684\u57fa\u672c\u6b65\u9aa4\u5305\u62ec\uff1a\u9996\u5148\uff0c\u5bfc\u5165\u5fc5\u8981\u7684\u5e93\u548c\u6570\u636e\uff1b\u63a5\u7740\uff0c\u8fdb\u884c\u6570\u636e\u9884\u5904\u7406\uff0c\u786e\u4fdd\u6570\u636e\u683c\u5f0f\u548c\u8d28\u91cf\uff1b\u7136\u540e\uff0c\u9009\u62e9\u5408\u9002\u7684\u56fe\u8868\u7c7b\u578b\uff0c\u5982\u6298\u7ebf\u56fe\u3001\u67f1\u72b6\u56fe\u6216\u6563\u70b9\u56fe\uff0c\u5e76\u4f7f\u7528\u76f8\u5e94\u7684\u51fd\u6570\u7ed8\u5236\uff1b\u6700\u540e\uff0c\u6dfb\u52a0\u56fe\u8868\u6807\u9898\u3001\u6807\u7b7e\u548c\u56fe\u4f8b\uff0c\u4ee5\u63d0\u5347\u53ef\u8bfb\u6027\u548c\u7f8e\u89c2\u6027\u3002\u901a\u8fc7\u8fd9\u4e9b\u6b65\u9aa4\uff0c\u53ef\u4ee5\u6709\u6548\u5730\u5c55\u793a\u6570\u636e\u7684\u8d8b\u52bf\u548c\u5173\u7cfb\u3002<\/p>\n
\u5982\u4f55\u5728Python\u4e2d\u81ea\u5b9a\u4e49\u56fe\u8868\u7684\u6837\u5f0f\u548c\u989c\u8272\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u81ea\u5b9a\u4e49\u56fe\u8868\u7684\u6837\u5f0f\u548c\u989c\u8272\u901a\u5e38\u901a\u8fc7\u8bbe\u7f6e\u53c2\u6570\u6765\u5b9e\u73b0\u3002\u4ee5Matplotlib\u4e3a\u4f8b\uff0c\u53ef\u4ee5\u4f7f\u7528plt.style.use()<\/code>\u65b9\u6cd5\u9009\u62e9\u4e0d\u540c\u7684\u9884\u8bbe\u6837\u5f0f\uff0c\u6216\u8005\u901a\u8fc7\u8bbe\u7f6ecolor<\/code>\u3001linestyle<\/code>\u7b49\u53c2\u6570\u6765\u81ea\u5b9a\u4e49\u989c\u8272\u548c\u7ebf\u578b\u3002\u6b64\u5916\uff0cSeaborn\u63d0\u4f9b\u4e86\u66f4\u4e3a\u7b80\u4fbf\u7684\u65b9\u5f0f\uff0c\u53ef\u4ee5\u901a\u8fc7\u8c03\u7528sns.set_palette()<\/code>\u6765\u66f4\u6539\u8c03\u8272\u677f\uff0c\u4ece\u800c\u5b9e\u73b0\u56fe\u8868\u7684\u4e2a\u6027\u5316\u98ce\u683c\u3002\u4f7f\u7528\u8fd9\u4e9b\u529f\u80fd\u53ef\u4ee5\u4f7f\u56fe\u8868\u66f4\u52a0\u7b26\u5408\u4e2a\u4eba\u6216\u54c1\u724c\u7684\u89c6\u89c9\u9700\u6c42\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5982\u4f55\u7528Python\u7ed8\u5236\u6570\u636e\u5206\u6790\u56fe \u4f7f\u7528Python\u7ed8\u5236\u6570\u636e\u5206\u6790\u56fe\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u51e0\u79cd\u5e38\u89c1\u7684\u65b9\u6cd5\u5b9e\u73b0\uff1a\u4f7f\u7528Matpl […]","protected":false},"author":3,"featured_media":1087931,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1087919"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1087919"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1087919\/revisions"}],"predecessor-version":[{"id":1087932,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1087919\/revisions\/1087932"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1087931"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1087919"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1087919"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1087919"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}