如何繪製大熊貓從數據幀熱圖

Question

這裏是我的數據框：

   jan   f   m  a  m   j \ 
2000 -7.894737 22.387006 22.077922 14.5455 15.8038 -3.33333 
2001 -3.578947 11.958763 28.741093 5.05415 74.7151 11.2426 
2002 -24.439661 -2.570483  1.810242 8.56044 84.5474 -26.9753 
2003 14.410453 -10.106570  8.179654 -11.6469 -15.0022 -13.9757 
2004 -3.978623 -13.280310  2.558639 -1.13076 12.7156 -4.47235 
2005  2.018146 1.385053  9.461930 14.1947 -10.4865 -11.1553 
2006 -6.528617 -5.506220 -2.054323 1.39073 7.74041 -0.328937 
2007 -1.634891 8.923088  4.951521 -1.33334 3.82215 7.69231 
2008 20.539609 0.132377 -3.117323 6.53806 9.99998 16.1356 
2009 -3.979917 -9.342541 -23.233634 -26.5963 -27.0396 -4.39528 
2010  6.141145 5.304527 -4.722650 4.32727 -4.55749 -3.98345 
2011 -1286.639676 16.295265 -13.697203 89.2141 12.4599 -2.56771 
2012  1.939279 -6.047198 -273.852729 -2.06906 9.35551 -327.816 
2013  5.361207 -0.341469 93.825888 -4.90762 61.0443 3.89917 
2014  7.900937 65.372284 65.955447 -8.5217 8.12922 6.99473 
2015 -116.635830 -1.094263 96.942247 -6308.42 -1.05717 1.70411 
2016 67.714100 -8.219712 2806.000000  nr  nr  nr 

的指數值應該來對x軸和列名需要在Y軸上顯示。我怎樣才能做到這一點？

Answer 1

這是直接使用seaborn;我演示瞭如何使用隨機數據來做到這一點，所以您只需在實例中用下面的示例代替data。

我的數據框看起來是這樣的：

   A   B   C   D   E 
2000 0.722553 0.948447 0.598707 0.656252 0.618292 
2001 0.920532 0.054941 0.909858 0.721002 0.222167 
2002 0.048496 0.963871 0.689730 0.697573 0.349308 
2003 0.692897 0.272768 0.581736 0.150674 0.861672 
2004 0.889694 0.658286 0.879855 0.739821 0.010971 
2005 0.937347 0.132955 0.704528 0.443084 0.552123 
2006 0.869499 0.750177 0.675160 0.873720 0.270204 
2007 0.156933 0.186630 0.371993 0.153790 0.397232 
2008 0.384696 0.585156 0.746883 0.185457 0.095387 
2009 0.667236 0.340058 0.446081 0.863402 0.227776 
2010 0.817394 0.343427 0.804157 0.245394 0.850774 

然後輸出如下（請注意該指數是在x軸和y軸的列名的要求）：

下面是一些內部註釋整個代碼：

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

# create some random data; replace that by your actual dataset 
data = pd.DataFrame(np.random.rand(11, 5), columns=['A', 'B', 'C', 'D', 'E'], index = range(2000, 2011, 1)) 

# plot heatmap 
ax = sns.heatmap(data.T) 

# turn the axis label 
for item in ax.get_yticklabels(): 
    item.set_rotation(0) 

for item in ax.get_xticklabels(): 
    item.set_rotation(90) 

# save figure 
plt.savefig('seabornPandas.png', dpi=100) 
plt.show()