已信任 Jupyter 服务器: 本地 Python 3: Not Started [7] import pandas as pd import numpy as np UsageError: unrecognized arguments: 设置这行代码，显示 [4] df = pd.DataFrame(np.random.randn(10,4),index=pd.date_range('2020-1-1',periods=10),columns=list('ABCD')) df A B C D 2020-01-01 0.846958 -0.092453 1.439972 -1.736005 2020-01-02 0.199984 -0.822618 0.756459 -0.566921 2020-01-03 -0.400146 0.505496 -0.306564 0.920308 2020-01-04 0.222298 -0.985005 1.126557 2.711075 2020-01-05 1.952021 1.096278 -0.085026 0.335684 2020-01-06 -1.359681 1.493068 -0.736807 -0.846511 2020-01-07 -0.837022 -1.017107 -0.444694 0.689624 2020-01-08 0.097225 1.996268 0.703147 -0.461194 2020-01-09 0.749375 0.003991 -0.871616 0.287275 2020-01-10 -0.733558 0.575336 1.087097 0.201447 [11] %matplotlib inline # 设置这行代码，显示 df.plot() UsageError: unrecognized arguments: # 设置这行代码，显示 [12] df = pd.DataFrame(np.random.randn(10,4),columns=['A','B','C','D']) df A B C D 0 -0.220509 -0.042927 -0.238487 1.672412 1 -0.164110 -0.507156 -0.403201 0.212512 2 -0.213318 0.100192 1.569447 1.140537 3 0.899244 -0.773582 0.186109 0.630794 4 -0.065581 -0.331992 0.296159 -0.477399 5 -0.681295 -0.035207 -0.843813 0.294918 6 0.447513 2.029172 -0.418954 0.435755 7 2.448048 0.931032 -0.470845 -1.186709 8 -0.318224 -1.299177 0.344508 -0.996497 9 0.230928 0.715940 -0.567065 -0.009406 [13] df.plot.bar() <matplotlib.axes._subplots.AxesSubplot at 0x24f7fe441d0> [14] # 堆积条形图,h表示水平 df.plot.barh(stacked=True) <matplotlib.axes._subplots.AxesSubplot at 0x24f7ff59470> [15] df = pd.DataFrame({ 'a':np.random.randn(100)+1, 'b':np.random.randn(100), 'c':np.random.randn(100)-1 },columns=['a','b','c']) df a b c 0 0.000225 -0.802291 -2.977373 1 2.643898 -0.722520 -1.057299 2 1.387954 -1.036934 -1.058767 3 0.581279 -1.228817 -1.139152 4 -0.401500 -1.500153 0.081929 ... ... ... ... 95 2.895006 0.212231 -1.123560 96 0.641197 0.207960 0.833677 97 0.837922 0.228554 -0.961109 98 2.107162 -0.056751 -2.883269 99 0.586976 -1.269353 -0.343638 100 rows × 3 columns [16] df.plot.hist(bins=20)# bins=20是区间显示 <matplotlib.axes._subplots.AxesSubplot at 0x24f00052a90> [17] df.plot.box() <matplotlib.axes._subplots.AxesSubplot at 0x24f7ff44e80> [22] # 区域块形图,这个代码错了 # df.plot.area() [23] # 散点图 df = pd.DataFrame(np.random.randn(50,4),columns=['A','B','C','D']) df A B C D 0 0.976834 1.149036 -0.350094 0.547278 1 1.076609 -0.729466 0.805290 0.077687 2 0.905936 -1.384177 0.945078 2.239078 3 -0.769447 -0.833319 1.633905 0.195962 4 0.337959 0.195163 0.052347 -1.759461 5 0.291865 -0.140926 -0.171821 -0.193732 6 -0.030381 1.252231 -1.371790 0.955666 7 -0.159967 -0.204076 -0.608549 1.698038 8 0.025247 -0.433548 0.546536 0.317204 9 -0.668021 0.835804 1.448863 -0.855055 10 0.869959 -0.907479 -0.353877 -0.904369 11 -0.266059 -1.525401 -0.820096 -1.532421 12 -0.573746 -0.382850 -0.173064 0.609361 13 0.499136 -0.553104 -1.271152 -0.778085 14 -0.125324 -0.910958 -0.620956 -0.634354 15 2.388082 1.657346 -1.980270 0.851881 16 1.040289 0.063811 -0.644910 0.686238 17 0.614557 0.313544 0.319014 -0.126910 18 1.762719 -2.197812 -0.644599 1.103788 19 -0.665237 0.588063 -1.395894 0.111074 20 -1.197394 -0.529851 -1.176089 -0.718828 21 0.115390 0.030522 -0.367691 0.733676 22 0.665735 -0.498446 -0.265189 -1.100315 23 0.494392 -1.982058 -0.384783 -0.372455 24 1.215364 1.043641 0.624550 0.467968 25 0.215523 0.312841 -0.060308 -0.875984 26 -1.135017 -0.063532 0.319131 -0.700542 27 0.183737 -0.076965 -0.014999 0.711829 28 1.348638 0.812489 0.489820 1.207570 29 -2.435077 -0.858729 -0.942066 0.732689 30 0.791332 -1.089636 -0.453003 -0.630916 31 0.071361 0.029469 0.051310 0.473051 32 -0.814295 0.398640 -0.185814 -0.774485 33 0.578655 -1.780421 1.203517 0.166697 34 0.430287 -0.916687 1.447872 -0.166584 35 -0.142278 -0.033319 -0.503827 1.685162 36 0.267174 -0.660718 0.592760 -1.999655 37 -0.008522 1.281695 -0.247696 -0.792215 38 1.461348 -0.716580 0.748531 -0.948239 39 -0.627528 1.069450 -0.598248 0.544610 40 -0.079064 1.758644 1.057895 0.532964 41 -0.104020 0.659945 -0.109066 -1.724713 42 -0.501239 -1.516701 1.095822 1.801034 43 0.076188 -1.364045 0.142956 -0.062114 44 -0.450091 1.413097 0.594281 -0.867741 45 -0.617244 1.112824 -0.484753 -0.348894 46 0.736782 -0.601504 0.917616 0.387469 47 -0.921364 0.194857 0.965232 0.006958 48 -0.568531 -1.979506 0.965640 -0.617862 49 -0.161154 -0.278164 0.236000 -0.181289 [24] df.plot.scatter(x='A',y='B') <matplotlib.axes._subplots.AxesSubplot at 0x24f003b98d0> [31] # 散点图 df = pd.DataFrame(3*np.random.rand(4),index=['A','B','C','D'],columns=['aa']) df aa A 2.265322 B 1.600306 C 2.545557 D 2.660989 [32] df.plot.pie(subplots=True) array([<matplotlib.axes._subplots.AxesSubplot object at 0x0000024F0154A6D8>], dtype=object) [-]