查看简单的散点图来查看两个不同平台生成的因素的相关性
问题描述 投票：0回答：1
我想为从两个不同平台生成的约 100 个样本中的一组因子生成简单的散点图具有两种颜色的点，以查看每个因子的相关性。
使用 pandas 查找 python3，具有 x、y 轴比例范围特征的 matplotlib，每个平台数据点的颜色不同，大小为 1. 使用循环在单个图像文件（多窗口）中的所有九个数据图和 2. 每个图在一个单独的文件中。预先感谢您的任何帮助。 我尝试了以下基本步骤来生成每个数据的绘图。
import pandas as pd
#import csv
import numpy as np
import matplotlib.pyplot as plt
df=pd.read_csv("test_data_np_arg.csv")
df.head()
Samples yield_NP mean_NP pct_NP mad_NP pct-act_NP pct-pp_NP mean_NP.1 insert_NP rate_NP yield_Arg mean_Arg pct_Arg mad_Arg pct-act_Arg pct-pp_Arg mean_Arg.1 insert_Arg rate_Arg
0 sample_1 1.020000e+11 30.85476 95.83108 2.40 99.72261 97.95775 440.6 99.7 5.970000e-09 1.019400e+11 30.30078 95.7618 4 99.72261 97.95775 440.6 99.7 0
1 sample_2 1.350000e+11 39.54372 96.13075 2.69 99.73480 97.92363 446.7 103.7 1.120000e-06 1.348150e+11 38.89375 96.2904 5 99.73480 97.92363 446.7 103.7 0
2 sample_3 1.040000e+11 31.50230 95.87788 2.53 99.79733 98.28176 450.1 101.8 3.980000e-06 1.043480e+11 30.95051 95.8694 5 99.79733 98.28176 450.1 101.8 0
3 sample_4 1.080000e+11 32.88599 95.94028 2.58 99.80831 98.33480 452.7 102.2 1.351000e-06 1.080160e+11 32.25406 95.9667 5 99.80831 98.33480 452.7 102.2 0
4 sample_5 1.070000e+11 30.95200 95.87643 2.85 99.73196 97.89158 436.1 99.2 1.280000e-06 1.069150e+11 30.45470 95.8471 5 99.73196 97.89158 436.1 99.2 0
###x = range(100)
###y = range(100)
### X-axis limits
###xmin = 1e-4;
###xmax = 3e-3;
###plt.scatter(df.iloc[:,2])
###df.plot(kind = 'scatter', x = 'yield_NP', y = 'yeild_Arg')
###plt.scatter(yield_NP,yield_Arg) #line graph
x = df['yield_NP']
y = df['yield_Arg']
plt.scatter(x, y)
plt.xlabel()
plt.ylabel()
plt.title()
plt.scatter(x,y,color='blue')
plt.rcParams.update({'figure.figsize':(10,8), 'figure.dpi':100})
plt.show()
示例：
附上我的.csv格式数据。 100 个样本排成一行，每个因子（值）来自两个不同的平台，名为 NP 和 Arg 位于列中。
标题： 第1栏样品
平台NP： 第 2 至 10 列产量_NPmean_NP、pct_NP、mad_NP、pct-act_NP、pct-pp_NP、mean_NP、insert_NP、rate_NP
平台参数： 第11至19列yield_Arg，mean_Arg，pct_Arg，mad_Arg，pct-act_Arg，pct-pp_Arg，mean_Arg，insert_Arg，rate_Arg
- 散点图“yield”应属于 yield_NP 与 yield_Arg 列，OR（第 2 列 vs 11）
- 散点图“平均值”应属于列 mean_NP vs 列mean_Arg，（第 3 列 vs 12 列）
- … ....
- …
输入数据
test_data_np_arg.csvSamples yield_NP mean_NP pct_NP mad_NP pct-act_NP pct-pp_NP mean_NP insert_NP rate_NP yield_Arg mean_Arg pct_Arg mad_Arg pct-act_Arg pct-pp_Arg mean_Arg insert_Arg rate_Arg
sample_1 1.02E+11 30.85476 95.83108 2.4 99.72261 97.95775 440.6 99.7 5.97E-09 1.0194E+11 30.30078 95.7618 4 99.72261 97.95775 440.6 99.7 0
sample_2 1.35E+11 39.54372 96.13075 2.69 99.7348 97.92363 446.7 103.7 1.12E-06 1.34815E+11 38.89375 96.2904 5 99.7348 97.92363 446.7 103.7 0
sample_3 1.04E+11 31.5023 95.87788 2.53 99.79733 98.28176 450.1 101.8 3.98E-06 1.04348E+11 30.95051 95.8694 5 99.79733 98.28176 450.1 101.8 0
sample_4 1.08E+11 32.88599 95.94028 2.58 99.80831 98.3348 452.7 102.2 0.000001351 1.08016E+11 32.25406 95.9667 5 99.80831 98.3348 452.7 102.2 0
sample_5 1.07E+11 30.952 95.87643 2.85 99.73196 97.89158 436.1 99.2 1.28E-06 1.06915E+11 30.4547 95.8471 5 99.73196 97.89158 436.1 99.2 0
sample_6 1.02E+11 30.32588 95.82636 2.32 99.74506 98.09959 443.9 99.4 3.82E-09 1.01891E+11 29.77961 95.7173 4 99.74506 98.09959 443.9 99.4 0
sample_7 1.03E+11 30.8906 95.87171 2.41 99.72588 97.97383 442.1 99.5 7.48E-07 1.02859E+11 30.33201 95.8008 4 99.72588 97.97383 442.1 99.5 0
sample_8 1.05E+11 32.29805 95.91017 2.54 99.78956 98.12378 447.3 100.8 1.63E-06 1.04712E+11 31.69718 95.9272 5 99.78956 98.12378 447.3 100.8 0
sample_9 98732711940 29.64056 95.79516 2.26 99.73939 97.91273 437.9 97.7 2.95E-09 98732711940 29.11294 95.6311 4 99.73939 97.91273 437.9 97.7 0
sample_10 1.02E+11 30.22417 95.78791 2.41 99.69657 97.78881 437.3 97.8 1.92E-06 1.01992E+11 29.69243 95.6681 4 99.69657 97.78881 437.3 97.8 0
sample_11 1.77E+11 52.53136 96.31651 3.73 99.74559 98.03557 440.9 100.9 7.83E-07 1.7654E+11 51.61069 96.5147 6 99.74559 98.03557 440.9 100.9 0
sample_12 1.20E+11 35.07535 95.99761 2.87 99.76128 98.045 432.6 100.8 1.31E-06 1.19786E+11 34.61427 96.1337 5 99.76128 98.045 432.6 100.8 0
sample_13 98874217002 29.67494 95.79408 2.28 99.74523 97.95379 445.2 99.5 6.72E-09 98874217002 29.14371 95.6212 4 99.74523 97.95379 445.2 99.5 0
sample_14 1.09E+11 32.06474 95.89239 2.47 99.71998 97.89142 443.9 99.9 1.05E-06 1.0895E+11 31.49802 95.8792 5 99.71998 97.89142 443.9 99.9 0
sample_15 1.00E+11 29.80763 95.78573 2.42 99.75593 97.87908 435.1 99.1 2.39E-09 1.00279E+11 29.29912 95.6557 4 99.75593 97.87908 435.1 99.1 0
sample_16 1.09E+11 32.91384 95.90146 2.51 99.70689 97.85116 445.6 100.7 1.88E-06 1.09404E+11 32.29913 95.9107 5 99.70689 97.85116 445.6 100.7 0
sample_17 97816752073 28.99877 95.80532 2.52 99.77984 98.11997 426.5 99.9 3.42E-09 97816752073 28.57639 95.6557 4 99.77984 98.11997 426.5 99.9 0
sample_18 99875608784 29.8512 95.84741 2.3 99.77063 98.227 443.8 99 3.90E-10 99875608784 29.30749 95.7026 4 99.77063 98.227 443.8 99 0
sample_19 1.05E+11 31.18936 95.8826 2.51 99.71659 97.8446 443.5 101 4.05E-09 1.05462E+11 30.71611 95.8931 4 99.71659 97.8446 443.5 101 0
sample_20 1.14E+11 34.54803 95.99543 2.5 99.73037 97.95208 446.9 100.4 3.05E-09 1.14368E+11 33.94012 96.0641 5 99.73037 97.95208 446.9 100.4 0
sample_21 91070755092 28.08189 95.69757 2.39 99.49053 97.29799 424.5 97.7 7.58E-10 91070755092 27.16736 95.1967 4 99.49053 97.29799 424.5 97.7 0
sample_22 1.03E+11 30.18906 95.80496 2.32 99.7367 98.0612 444 99.9 1.45E-06 1.02681E+11 29.65553 95.6822 4 99.7367 98.0612 444 99.9 0
sample_23 94779004959 28.32233 95.74401 2.26 99.75454 98.06741 440.1 101.9 4.55E-09 94779004959 27.79295 95.4909 4 99.75454 98.06741 440.1 101.9 0
sample_24 1.10E+11 32.6702 95.93303 2.45 99.79297 98.24325 458 102.7 2.48E-09 1.09683E+11 32.10852 95.947 5 99.79297 98.24325 458 102.7 0
sample_25 1.10E+11 32.51392 95.91561 2.58 99.69296 97.88712 438.9 100.3 8.80E-07 1.09664E+11 31.98217 95.9614 5 99.69296 97.88712 438.9 100.3 0
sample_26 1.11E+11 33.18012 95.9421 2.51 99.68512 97.88962 449.1 103.5 3.25E-09 1.10539E+11 32.59671 96.0175 5 99.68512 97.88962 449.1 103.5 0
sample_27 1.09E+11 31.75891 95.89965 2.54 99.74522 97.79328 439.7 99.9 2.67E-09 1.0945E+11 31.30704 95.9617 5 99.74522 97.79328 439.7 99.9 0
sample_28 1.07E+11 32.02777 95.92396 2.57 99.72103 97.78891 454 104.8 9.02E-09 1.07001E+11 31.52126 95.959 5 99.72103 97.78891 454 104.8 0
sample_29 1.12E+11 33.64239 95.93847 2.7 99.74315 97.92744 447.5 103.1 4.11E-09 1.11869E+11 33.10581 96.0227 5 99.74315 97.92744 447.5 103.1 0
sample_30 1.12E+11 32.99544 95.93774 2.53 99.73674 97.98786 442.8 100.9 1.20E-06 1.12014E+11 32.51 96.0109 5 99.73674 97.98786 442.8 100.9 0
sample_31 1.05E+11 32.27342 95.90836 2.44 99.72944 98.04976 441.8 100.3 1.47E-06 1.04834E+11 31.37597 95.8615 4 99.72944 98.04976 441.8 100.3 0
sample_32 1.08E+11 31.67663 95.87933 2.51 99.74561 97.88388 435.8 99.6 8.24E-07 1.08499E+11 31.18913 95.9151 4 99.74561 97.88388 435.8 99.6 0
sample_33 1.12E+11 32.50864 95.92867 2.61 99.68827 97.78834 449.6 102.8 9.57E-09 1.11538E+11 31.97458 95.9779 5 99.68827 97.78834 449.6 102.8 0
sample_34 1.13E+11 34.29474 96.00631 2.78 99.83226 98.27716 446.4 101.6 2.75E-09 1.12849E+11 33.82919 96.1052 5 99.83226 98.27716 446.4 101.6 0
sample_35 99400525623 30.81942 95.8387 2.48 99.78345 98.20671 446 101.2 1.08E-06 99400525623 29.98714 95.7308 4 99.78345 98.20671 446 101.2 0
sample_36 1.15E+11 34.29637 95.97148 2.82 99.77035 98.02257 441.1 101.1 1.04E-06 1.14885E+11 33.74547 96.0615 5 99.77035 98.02257 441.1 101.1 0
sample_37 1.07E+11 32.37888 95.9508 2.61 99.7133 97.98365 444.5 100.5 1.34E-09 1.07473E+11 31.76157 95.9864 5 99.7133 97.98365 444.5 100.5 0
sample_38 1.03E+11 31.53656 95.93194 2.64 99.77947 98.19387 439.4 101 1.50E-09 1.02917E+11 31.02146 95.951 5 99.77947 98.19387 439.4 101 0
sample_39 1.06E+11 30.28286 95.87534 2.45 99.75018 98.05562 439.9 100.9 1.37E-06 1.05871E+11 29.79179 95.8127 4 99.75018 98.05562 439.9 100.9 0
sample_40 1.05E+11 31.52802 95.91706 2.47 99.79558 98.06771 427.3 98.4 1.18E-08 1.05336E+11 30.91472 95.9214 4 99.79558 98.06771 427.3 98.4 0
sample_40 1.05E+11 31.52802 95.91706 2.47 99.79558 98.06771 427.3 98.4 1.18E-08 1.05336E+11 30.91472 95.9214 4 99.79558 98.06771 427.3 98.4 0
sample_41 1.09E+11 31.29889 95.91489 2.35 99.73194 97.99713 427.2 97.5 9.77E-09 1.0949E+11 30.81643 95.9266 4 99.73194 97.99713 427.2 97.5 0
sample_42 1.03E+11 30.35667 95.89239 2.41 99.73659 98.03721 438.7 101.2 8.28E-07 1.03284E+11 29.88501 95.8842 4 99.73659 98.03721 438.7 101.2 0
sample_43 1.10E+11 32.5761 95.94972 2.74 99.71097 97.89525 454.2 103.2 2.21E-09 1.10059E+11 32.00364 95.9879 5 99.71097 97.89525 454.2 103.2 0
sample_44 1.13E+11 33.22374 96.00668 2.89 99.77643 98.12726 437.6 100 1.59E-09 1.132E+11 32.77427 96.1141 5 99.77643 98.12726 437.6 100 0
sample_45 1.20E+11 34.19891 96.00994 3.05 99.76761 98.08657 444.4 101.3 1.33E-09 1.19803E+11 33.77175 96.1266 5 99.76761 98.08657 444.4 101.3 0
sample_46 1.19E+11 35.68893 96.07089 2.56 99.7517 98.01643 439.8 100.2 2.04E-09 1.19052E+11 35.17978 96.227 5 99.7517 98.01643 439.8 100.2 0
sample_47 1.56E+11 47.59501 96.27841 3.11 99.77304 98.13004 441.7 100.9 5.48E-07 1.55554E+11 46.80516 96.4836 6 99.77304 98.13004 441.7 100.9 0
sample_48 1.28E+11 37.59036 96.09955 2.62 99.7544 98.08099 436.8 100.2 1.94E-09 1.28106E+11 37.08409 96.2848 5 99.7544 98.08099 436.8 100.2 0
sample_49 99660967688 29.62502 95.82274 2.36 99.76129 98.06697 424.5 99.1 1.82E-09 99660967688 29.11601 95.6862 4 99.76129 98.06697 424.5 99.1 0
sample_50 1.10E+11 32.38506 95.96205 2.4 99.73501 98.05385 442.5 101.1 3.24E-09 1.10417E+11 31.8706 96.0418 4 99.73501 98.05385 442.5 101.1 0
sample_51 1.01E+11 30.60525 95.90146 2.37 99.71151 97.85232 440.7 101 4.59E-06 1.00502E+11 30.02358 95.8872 4 99.71151 97.85232 440.7 101 0
sample_52 1.21E+11 36.92763 96.11334 2.85 99.693 97.84396 428.1 99.3 8.65E-07 1.20533E+11 35.97378 96.2246 5 99.693 97.84396 428.1 99.3 0
sample_53 1.12E+11 31.55724 95.92106 2.5 99.71733 97.94133 427.6 96.6 7.64E-10 1.11613E+11 31.0624 95.9483 4 99.71733 97.94133 427.6 96.6 0
sample_54 1.10E+11 34.16102 96.00414 2.69 99.72714 98.20101 434 99.7 5.51E-06 1.10452E+11 33.24734 96.0308 5 99.72714 98.20101 434 99.7 0
sample_55 1.08E+11 30.76239 95.87498 2.76 99.80626 98.26043 434.2 99.4 1.75E-09 1.07891E+11 30.31996 95.8528 5 99.80626 98.26043 434.2 99.4 0
sample_56 1.02E+11 31.01334 95.8884 2.44 99.71137 98.02674 438.1 100.1 4.23E-10 1.01508E+11 30.26782 95.8255 4 99.71137 98.02674 438.1 100.1 0
sample_57 1.10E+11 32.27204 95.93738 2.77 99.74261 98.04745 425.5 96.9 1.02E-06 1.09992E+11 31.78231 95.998 5 99.74261 98.04745 425.5 96.9 0
sample_58 1.01E+11 29.63566 95.83362 2.49 99.73006 98.03498 429.5 98.5 1.75E-09 1.01204E+11 29.13839 95.7239 4 99.73006 98.03498 429.5 98.5 0
sample_59 1.39E+11 41.53544 96.18445 2.95 99.8092 98.30391 436.1 101 7.78E-07 1.38829E+11 40.87246 96.3519 5 99.8092 98.30391 436.1 101 0
sample_60 1.49E+11 43.58239 96.22036 3.1 99.7331 98.18926 441.1 101.4 1.45E-06 1.48519E+11 42.89485 96.407 5 99.7331 98.18926 441.1 101.4 0
sample_61 94358139331 29.02033 95.80859 2.23 99.72827 98.04585 442.6 102 3.49E-09 94358139331 28.40806 95.5737 4 99.72827 98.04585 442.6 102 0
sample_62 1.02E+11 30.73124 95.88949 2.55 99.75763 98.1358 440.8 101 1.91E-08 1.01922E+11 30.14433 95.8251 4 99.75763 98.1358 440.8 101 0
sample_63 1.01E+11 30.26892 95.83543 2.38 99.7678 98.10769 440.7 101.3 1.58E-06 1.01125E+11 29.77872 95.7721 4 99.7678 98.10769 440.7 101.3 0
sample_64 1.08E+11 31.847 95.94573 2.5 99.72622 97.99772 433.5 97.6 1.79E-06 1.0784E+11 31.35237 95.991 4 99.72622 97.99772 433.5 97.6 0
sample_65 96776159556 30.06908 95.84777 2.45 99.52316 97.58877 422.8 98 1.25E-09 96776159556 29.2151 95.6652 4 99.52316 97.58877 422.8 98 0
sample_66 1.26E+11 37.48715 96.11951 2.79 99.74966 98.10085 430.1 99.5 3.11E-09 1.25599E+11 36.84727 96.2503 5 99.74966 98.10085 430.1 99.5 0
sample_67 1.31E+11 39.26691 96.14926 3.08 99.74451 97.95533 432 100.3 8.28E-07 1.31475E+11 38.58257 96.2912 5 99.74451 97.95533 432 100.3 0
sample_68 99308534044 29.89997 95.8387 2.41 99.79687 98.15405 434.1 100.5 4.05E-09 99308534044 29.4153 95.755 4 99.79687 98.15405 434.1 100.5 0
sample_69 1.04E+11 31.11425 95.90001 2.53 99.75409 98.01168 430.9 99 6.05E-07 1.04154E+11 30.60253 95.8799 4 99.75409 98.01168 430.9 99 0
sample_70 1.20E+11 36.34303 96.09302 2.69 99.75035 97.97297 437.9 101.2 4.16E-09 1.19703E+11 35.73808 96.2123 5 99.75035 97.97297 437.9 101.2 0
sample_71 1.72E+11 51.99843 96.35387 3.62 99.745 98.13036 435.3 100.3 4.90E-07 1.72425E+11 51.06496 96.5405 6 99.745 98.13036 435.3 100.3 0
sample_72 1.00E+11 30.48683 95.86119 2.45 99.70088 97.77195 433.9 98.2 2.17E-09 1.0005E+11 29.95496 95.795 4 99.70088 97.77195 433.9 98.2 0
sample_73 1.02E+11 30.7607 95.9011 2.51 99.70653 97.88851 424.1 98.2 4.36E-09 1.02104E+11 30.15563 95.8511 4 99.70653 97.88851 424.1 98.2 0
sample_74 1.12E+11 32.35504 95.93339 2.43 99.72186 97.94937 431.1 97.9 6.83E-10 1.12015E+11 31.8753 96.0092 4 99.72186 97.94937 431.1 97.9 0
sample_75 1.55E+11 46.32393 96.26027 3.47 99.75905 98.11215 422 98 1.10E-06 1.55011E+11 45.5614 96.4486 6 99.75905 98.11215 422 98 0
sample_76 97089503358 29.48785 95.82201 2.86 99.74503 97.916 434.2 99.3 8.99E-09 97089503358 28.95893 95.6086 5 99.74503 97.916 434.2 99.3 0
sample_77 1.09E+11 32.97904 95.97475 2.63 99.71645 97.81641 437.2 100.9 1.95E-06 1.09002E+11 32.38335 96.0309 5 99.71645 97.81641 437.2 100.9 0
sample_78 1.03E+11 30.14343 95.87208 2.51 99.72748 97.94631 431.7 98.7 1.47E-09 1.02866E+11 29.69167 95.8327 4 99.72748 97.94631 431.7 98.7 0
sample_79 1.02E+11 30.40873 95.86446 2.43 99.74403 98.04649 437.3 99.9 1.50E-06 1.02082E+11 29.92895 95.8244 4 99.74403 98.04649 437.3 99.9 0
sample_80 1.25E+11 37.91671 96.09157 2.74 99.74695 98.07409 440.2 101 1.56E-06 1.25097E+11 37.29407 96.2274 5 99.74695 98.07409 440.2 101 0
sample_81 1.01E+11 31.53161 95.90328 3.29 99.71049 97.88596 433.1 100.6 9.41E-07 1.01411E+11 30.83368 95.8225 5 99.71049 97.88596 433.1 100.6 0
sample_82 99173169979 29.89573 95.85684 2.47 99.74151 98.05292 437.1 101 1.35E-09 99173169979 29.40804 95.7447 4 99.74151 98.05292 437.1 101 0
sample_83 1.04E+11 30.49102 95.88768 2.7 99.73246 97.92362 425.7 96.3 8.54E-09 1.04393E+11 30.01485 95.8424 5 99.73246 97.92362 425.7 96.3 0
sample_84 97704382884 29.88968 95.84995 2.4 99.78704 98.23961 441.2 102 4.37E-09 97704382884 29.30928 95.7342 4 99.78704 98.23961 441.2 102 0
sample_85 1.15E+11 33.95192 95.99579 2.86 99.7469 98.20643 435.9 99.7 2.10E-06 1.14548E+11 33.36085 96.0645 5 99.7469 98.20643 435.9 99.7 0
sample_86 1.06E+11 30.3987 95.86954 2.49 99.73811 98.12377 437.2 99.8 3.98E-09 1.06286E+11 29.92345 95.8407 4 99.73811 98.12377 437.2 99.8 0
sample_87 1.11E+11 33.99411 95.99688 2.66 99.76458 98.1613 445 101.6 1.01E-08 1.10903E+11 33.40791 96.0659 5 99.76458 98.1613 445 101.6 0
sample_88 1.07E+11 32.28092 95.95407 2.5 99.74595 98.01535 433.9 100.6 5.82E-09 1.0669E+11 31.62522 95.9834 5 99.74595 98.01535 433.9 100.6 0
sample_89 1.12E+11 33.36572 95.98309 2.61 99.76743 98.11891 437.2 101.1 1.30E-09 1.12314E+11 32.8189 96.0525 5 99.76743 98.11891 437.2 101.1 0
sample_90 1.03E+11 30.42415 95.88804 2.43 99.52558 97.59924 418.2 95 8.03E-10 1.02866E+11 29.75168 95.8063 4 99.52558 97.59924 418.2 95 0
sample_91 1.26E+11 38.03029 96.1166 3.75 99.76455 98.16839 432.9 99.6 1.07E-06 1.25675E+11 37.41665 96.2519 5 99.76455 98.16839 432.9 99.6 0
sample_92 1.32E+11 39.33902 96.14345 2.77 99.78796 98.27147 425.6 98.8 3.83E-09 1.31768E+11 38.7008 96.3025 5 99.78796 98.27147 425.6 98.8 0
sample_93 99266572540 28.77619 95.8075 2.43 99.7336 98.01659 433.9 99.1 4.99E-09 99266572540 28.32761 95.6002 4 99.7336 98.01659 433.9 99.1 0
sample_94 1.06E+11 31.0585 95.89747 2.57 99.77842 98.20429 439.6 100 2.41E-09 1.06262E+11 30.5643 95.898 4 99.77842 98.20429 439.6 100 0
sample_95 1.39E+11 41.76222 96.20041 3.13 99.70977 98.06093 451.8 104 3.40E-09 1.38828E+11 41.01108 96.3587 5 99.70977 98.06093 451.8 104 0
sample_96 1.13E+11 34.08653 95.99108 2.54 99.79491 98.17081 435.9 99 2.31E-09 1.13469E+11 33.5711 96.0856 5 99.79491 98.17081 435.9 99 0
sample_97 1.00E+11 29.98517 95.86627 2.38 99.73274 98.04362 439.6 101.7 6.33E-09 1.00316E+11 29.38303 95.7557 4 99.73274 98.04362 439.6 101.7 0
sample_98 1.14E+11 34.66174 96.01937 2.62 99.73272 98.02972 439.7 101.8 9.26E-09 1.13837E+11 33.81398 96.0889 5 99.73272 98.02972 439.7 101.8 0
sample_99 1.22E+11 36.80748 96.08722 2.73 99.70917 98.05788 441.4 101.9 1.41E-09 1.21809E+11 36.10285 96.1936 5 99.70917 98.05788 441.4 101.9 0
sample_100 1.26E+11 37.63943 96.09338 2.8 99.77074 98.15844 451.1 104.1 1.54E-06 1.25873E+11 36.97827 96.2291 5 99.77074 98.15844 451.1 104.1 0
1个回答
0
投票
投票
- 根据
和x
将列分成组，使每个列表的顺序对应于y
对，然后将xy
组合在一起。zip
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
# create the xy groups
colx_pairs = df.columns[1:10]
coly_pairs = df.columns[10:20]
col_pairs = list(zip(colx_pairs, coly_pairs))
# create a figure with 9 subplots
fig, axes = plt.subplots(3, 3, figsize=(16, 10), tight_layout=True)
# flatten the 3 x 3 axes array for easy iteration
axes = axes.flatten()
# iterate through each ax in axes, and the corresponding xy pair
for ax, (x, y) in zip(axes, col_pairs):
# plot the data
sns.scatterplot(data=df, x=x, y=y, hue='Samples', ax=ax)
# remove all except the last legend
if ax != axes[8]:
ax.get_legend().remove()
# extract the legend handles and labels
handles, labels = axes[8].get_legend_handles_labels()
# create a single figure plot
fig.legend(handles, labels, bbox_to_anchor=(1, 0.5), loc='center left', frameon=False, ncols=5)
# remove the legend from axes[8]
axes[8].get_legend().remove()
最新问题
- R data.table 测试列中的值是否在列表列中
- Firebase 功能因 Promise 而停止
- 如何使用此 Google 表格脚本将列标题值包含在电子邮件中
- Python 中最短的计算器程序
- c# 将图像转为字节数组，然后以 0x 的格式转为十六进制？
- 如果单元格值以特定字母开头，则复制并粘贴
- 在Lua中，是否可以像批处理脚本一样进行延迟扩展？
- 图像不存在时不显示下一个/图像组件
- Dagger-2 无法提供来自另一个模块的依赖项
- 如何退出或取消终端中的内联命令？
- 有序 Logit 回归的预测是如何工作的？
- Python pandas 数据框使用 apply 来调用具有列表输出的函数
- Oracle 刷新没有基表的物化视图
- 以表格形式删除文本中的多个空行
- 如何阻止数组自行更新并仅显示最后一个任务
- 我应该更喜欢使用 basic_istream::tellg() 还是 filesystem::file_size() ？
- 调试 Chrome 扩展的 popup.html？
- Python 中键盘模块面临的问题
- Django Bootstrap 卡组如果 forloop 可整除
- 使用 ErrorHandlingDeserializer 自定义日志和增量指标
© www.soinside.com 2019 - 2024. All rights reserved.