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Python如何利用pandas读取csv数据并绘图_python_

2023-05-26 349人已围观

简介 Python如何利用pandas读取csv数据并绘图_python_

如何利用pandas读取csv数据并绘图

导包，常用的numpy和pandas，绘图模块matplotlib，

import matplotlib.pyplot as plt import pandas as pd import numpy as np fig = plt.figure() ax = fig.add_subplot(111)

读取csv文件的数据，保存到numpy数组内

path_csv = "E:\\python\\python\\2021\\202104\\04091\\path_data.csv" xa = np.array([42.0, 44.4, 43.1, 40.6]) ya = np.array([21.6, 21.2, 13.5, 14.0]) xa1 = np.array([10, 40]) ya1 = np.array([10, 40]) path_data_x = pd.read_csv(path_csv, header=None, usecols=[0]) path_data_y = pd.read_csv(path_csv, header=None, usecols=[1]) path_x = np.array(path_data_x)[:, 0] path_y = np.array(path_data_y)[:, 0]

绘制图像

print(path_x[0]) print(path_y[0]) ax.plot(xa1, ya1, color='g', linestyle='', marker='.') ax.plot(xa, ya, color='g', linestyle='-', marker='.') ax.plot(path_x, path_y, color='m', linestyle='', marker='.') plt.show()

展示结果

pandas画pearson相关系数热力图

pearson相关系数计算函数

data.corr()

该方法支持空值：np.nan

import seaborn as sns import numpy as np import matplotlib.pyplot as plt data = pd.DataFrame({"A":[np.nan,2,9], "B":[4,14,6], "c":[987,8,9]}) f, ax= plt.subplots(figsize = (14, 10)) corr = data.corr() # print(corr) sns.heatmap(corr,cmap='RdBu', linewidths = 0.05, ax = ax) # 设置Axes的标题 ax.set_title('Correlation between features') plt.show() plt.close() f.savefig('sns_style_origin.jpg', dpi=100, bbox_inches='tight')