【发布时间】:2021-07-31 03:04:01
【问题描述】:
我想从 excel 中获取数据并在 python 中绘制 2D 内核密度估计,但它显示“ValueError:要解压的值太多(预期 2)”。如何解决?按照编码:
# libraries
import matplotlib.pyplot as plt
from scipy.stats import kde
import pandas as pd
# create data
x = pd.read_excel(r'C:\Users\Ezra\Desktop\montex.xlsx')
y = pd.read_excel(r'C:\Users\Ezra\Desktop\montey.xlsx')
# Evaluate a gaussian kde on a regular grid of nbins x nbins over data extents
nbins=500
k = kde.gaussian_kde([x,y])
xi, yi = pd.mgrid[x.min():x.max():nbins*100j, y.min():y.max():nbins*100j]
zi = k(pd.vstack([xi.flatten(), yi.flatten()]))
# Make the plot
plt.pcolormesh(xi, yi, zi.reshape(xi.shape), shading='auto')
plt.show()
# Change color palette
plt.pcolormesh(xi, yi, zi.reshape(xi.shape), shading='auto', cmap=plt.cm.Greens_r)
plt.show()
【问题讨论】:
标签: python pandas kernel gaussian