我正在尝试保存图像，但xlabels没有出现在保存的图像中。我试着修改尺寸，效果不错，但图像变大了。我想保持大小，并以某种方式显示完整的绘图信息。
数据如下。
data = {'neighbourhood': ['Allston-Brighton', 'Jamaica Plain', 'South End', 'Back Bay', 'Fenway/Kenmore', 'South Boston', 'Dorchester', 'Beacon Hill', 'North End', 'East Boston', 'Roxbury', 'Mission Hill', 'Charlestown', 'Chinatown', 'West End', 'Roslindale', 'West Roxbury', 'Theater District', 'Downtown Crossing', 'Hyde Park', 'Mattapan', 'Financial District', 'Somerville', 'Leather District', 'Downtown', 'Brookline', 'Cambridge', 'Chestnut Hill', 'Government Center', 'Harvard Square'], 'latitude': [42.35136861184197, 42.311768379852126, 42.342302581102956, 42.349542747362186, 42.34487223416756, 42.33920029843584, 42.30534371604848, 42.35916242461033, 42.36509251919781, 42.374797033371614, 42.32734681549604, 42.331789902337285, 42.378479634468505, 42.35070490587777, 42.36437167301179, 42.2844848817822, 42.28049169547555, 42.35179317067222, 42.355582834130146, 42.25870128503825, 42.286757258759295, 42.35833367767067, 42.38454210544948, 42.35075084496441, 42.358667722753495, 42.34150237882493, 42.36332342051593, 42.30072382305316, 42.3615193534256, 42.373740039980646], 'longitude': [-71.13980032939199, -71.11023629181607, -71.07406928489343, -71.08014985459491, -71.09639276028551, -71.04673010039227, -71.05980648703859, -71.06722209902804, -71.05435502753697, -71.03063773314375, -71.08533342932748, -71.10338968538669, -71.063939091515, -71.06158442474035, -71.06532504101003, -71.13144270905727, -71.15526404132471, -71.06424189076172, -71.0605365814764, -71.11810073342608, -71.0849389578363, -71.0536411757789, -71.08132624190405, -71.05746407735042, -71.05685306951624, -71.12512826846925, -71.10800606379425, -71.1623118265295, -71.06098895883044, -71.12200210465183], 'dist': [5.217274918890407, 5.117420577499391, 0.9157635862891802, 0.3306405006707467, 1.7610810938591674, 2.726903121754893, 5.1844408677649945, 1.227497247961104, 2.4324110127231613, 4.627284517560583, 2.6651506889743173, 3.0369798718044314, 3.283137336413658, 1.2079270532681, 1.7966687812416413, 8.611569508167042, 10.120811029410335, 1.0015368567582976, 1.4167815087370315, 10.751692511599911, 7.105621710489037, 2.059024017017853, 3.818876664289385, 1.546321543507951, 1.842593010462582, 4.130981378134085, 2.975557190604119, 8.966614609646907, 1.7636863017118727, 4.5639916116404695], 'price': [52.70595169067383, 78.32887268066406, 116.85491943359375, 154.3334503173828, 81.05461883544922, 112.77129364013672, 65.13931274414062, 122.6712646484375, 110.73733520507812, 87.53361511230469, 100.67787170410156, 44.86083984375, 109.29198455810547, 97.78974151611328, 172.12989807128906, 68.67533111572266, 70.07238006591797, 103.89393615722656, 92.42691802978516, 32.06399917602539, 59.09000015258789, 51.484615325927734, 56.128204345703125, 170.1875, 64.60416412353516, 21.53333282470703, 134.6619110107422, 58.25, 262.4222106933594, 0.0], 'count': [364, 314, 298, 291, 249, 216, 195, 174, 125, 117, 116, 103, 79, 78, 68, 50, 35, 33, 26, 25, 20, 13, 13, 8, 8, 8, 7, 4, 3, 2]}
df = pd.DataFrame(data)
dfc_dist_sort = df.sort_values(by=['count'],ascending=False)
我正在使用此代码。我能做些什么来保存图像而不让人头疼。如果有必要，我可以分享我的照片，只要告诉我就行了。
x = dfc_dist_sort['neighbourhood']
y = dfc_dist_sort['price']
z = dfc_dist_sort['count']
w = dfc_dist_sort['dist']
fig, axs = plt.subplots(3, 1, sharex=True,figsize=(8, 8))
fig.subplots_adjust(hspace=0)
axs[0].set_title('Comparing price, count and distance mean between neighbourhood')
axs[0].bar(x, y)
axs[0].set_ylabel('Price')
axs[1].bar(x, z)
axs[1].set_ylabel('Count')
axs[2].bar(x, w)
axs[2].set_ylabel('Distance (km)')
_ = plt.xticks(rotation=90)
plt.savefig('comp.png', dpi = 300)
谢谢。
在尝试其他方法后，我发现了这个：
plt.savefig('comp2.png', bbox_inches='tight', dpi = 100)
添加参数bbox_inches。