Question

基本上，我必须创建一个区域内人群的热图。我有两个坐标。 X从0开始，最大值为119994。Y从-14,000到+27,000。我必须根据需要将这些坐标划分为任意多个块，计算每个块中的人数并创建整个区域的热图。基本上显示出该区域的拥挤程度。

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我尝试将两个坐标最大值都除以100（以生成100个块），并尝试找到块坐标，但这非常复杂。

当我必须制作热图时，我必须准备块形式的值矩阵。每个数据块都会有一定数量的人，我可以计算并从我的数据中找出来，但是问题是如何制作这些坐标块？

关于散点图，我还有另一个问题：我的数据是：-

I have data in the below format:-
Employee_ID X_coord Y_coord_start Y_coord_end
    23       1333      0           6000
    45       3999    7000          17000

当我使用以下代码绘制它时：-

Batch_ID         Pieces_Productivity
181031008780     4.578886
181031008781     2.578886

它没有给我适当的阴谋。但是，当我使用Batch_ID的小整数（0-1000）进行绘制时，会得到良好的图形。如何处理大整数以进行绘图？

Answer 1

我既不知道Y_coord_行中的哪一行都应该给出实际的Y坐标，也不知道您的绘图是否应该在严格的“网格”上评估数据，或者应该比较平滑出来;因此，我在以下代码中同时使用了imshow()和sns.kdeplot()：

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

### generate some data
np.random.seed(0)
data = np.random.multivariate_normal([0, 0], [(1, .6), (.6, 1)], 100)

## this would e.g. be X,Y=df['X_coord'], df['Y_coord_start'] :
X,Y=data[:,0],data[:,1] 


fig,ax=plt.subplots(nrows=1,ncols=3,figsize=(10,5))
ax[0].scatter(X,Y)
sns.kdeplot(X,Y, shade=True, ax=ax[1],cmap="viridis")
## the X,Y points are binned into 10x10 bins here, you will need 
#  to adjust the amount of bins so that it looks "nice" for you
heatmap, xedges, yedges = np.histogram2d(X, Y, bins=(10,10))
extent = [xedges[0], xedges[-1], yedges[0], yedges[-1]]
im=ax[2].imshow(heatmap.T, extent=extent, 
            origin="lower",aspect="auto",
            interpolation="nearest") ## also play with different interpolations

## Loop over heatmap dimensions and create text annotations:
#  note that we need to "push" the text from the lower left corner of each pixel
#     into the center of each pixel 
## also try to choose a text color which is readable on all pixels, 
#     or e.g. use vmin=… vmax=  to adjust the colormap such that the colors
#     don't clash with e.g. white text

pixel_center_x=(xedges[1]-xedges[0])/2.
pixel_center_y=(yedges[1]-yedges[0])/2.
for i in range(np.shape(heatmap)[1]):
    for j in range(np.shape(heatmap)[0]):
        text = ax[2].text(pixel_center_x+xedges[j], pixel_center_y+yedges[i],'{0:0.0f}'.format(heatmap[j, i]),
                       ha="center", va="center", color="w",fontsize=6)

plt.colorbar(im)
plt.show()

产量：

如何将两个坐标之间的区域划分为块并为这些块分配一些值？

1 个答案: