1、数据准备
import matplotlib.pyplot as plt
import numpy as np;
np.random.seed(0)
import seaborn as sns;
sns.set()
uniform_data = np.random.rand(3, 3)
print (uniform_data)
heatmap = sns.heatmap(uniform_data)
ax = sns.heatmap(uniform_data, vmin=0.2, vmax=0.5)
normal_data = np.random.randn(3, 3)
print (normal_data)
ax = sns.heatmap(normal_data, center=0)
flights = sns.load_dataset("flights")
flights.head()
'''
year month passengers
0 1949 January 112
1 1949 February 118
2 1949 March 132
3 1949 April 129
4 1949 May 121
'''
flights = flights.pivot("month", "year", "passengers")
print (flights)
ax = sns.heatmap(flights)
'''
year 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 \
month
January 112 115 145 171 196 204 242 284 315 340 360
February 118 126 150 180 196 188 233 277 301 318 342
March 132 141 178 193 236 235 267 317 356 362 406
April 129 135 163 181 235 227 269 313 348 348 396
May 121 125 172 183 229 234 270 318 355 363 420
June 135 149 178 218 243 264 315 374 422 435 472
July 148 170 199 230 264 302 364 413 465 491 548
August 148 170 199 242 272 293 347 405 467 505 559
September 136 158 184 209 237 259 312 355 404 404 463
October 119 133 162 191 211 229 274 306 347 359 407
November 104 114 146 172 180 203 237 271 305 310 362
December 118 140 166 194 201 229 278 306 336 337 405
year 1960
month
January 417
February 391
March 419
April 461
May 472
June 535
July 622
August 606
September 508
October 461
November 390
December 432
'''
ax = sns.heatmap(flights, annot=True,fmt="d")
ax = sns.heatmap(flights, linewidths=.5)
ax = sns.heatmap(flights, cmap="YlGnBu")
ax = sns.heatmap(flights, cbar=False)
