如何按列散布子图中的成对列和颜色标记
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 - 为了通过度量分隔点，最简单的方法是将
与sns.scatterplot
参数一起使用。hue- 通过
对点进行着色没有用，因为有太多独特的类别。'Samples'
- 通过
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()
fig.savefig('figure.png')
- 不考虑着色的绘图
。Samples
# 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):
df.plot(kind='scatter', x=x, y=y, ax=ax, marker='.')
fig.savefig('figure.png')
df
dfdata =\
{'Samples': ['sample_1', 'sample_2', 'sample_3', 'sample_4', 'sample_5', 'sample_6', 'sample_7', 'sample_8', 'sample_9', 'sample_10', 'sample_11', 'sample_12', 'sample_13', 'sample_14', 'sample_15', 'sample_16', 'sample_17', 'sample_18', 'sample_19', 'sample_20', 'sample_21', 'sample_22', 'sample_23', 'sample_24', 'sample_25', 'sample_26', 'sample_27', 'sample_28', 'sample_29', 'sample_30', 'sample_31', 'sample_32', 'sample_33', 'sample_34', 'sample_35', 'sample_36', 'sample_37', 'sample_38', 'sample_39', 'sample_40', 'sample_40', 'sample_41', 'sample_42', 'sample_43', 'sample_44', 'sample_45', 'sample_46', 'sample_47', 'sample_48', 'sample_49', 'sample_50', 'sample_51', 'sample_52', 'sample_53', 'sample_54', 'sample_55', 'sample_56', 'sample_57', 'sample_58', 'sample_59', 'sample_60', 'sample_61', 'sample_62', 'sample_63', 'sample_64', 'sample_65', 'sample_66', 'sample_67', 'sample_68', 'sample_69', 'sample_70', 'sample_71', 'sample_72', 'sample_73', 'sample_74', 'sample_75', 'sample_76', 'sample_77', 'sample_78', 'sample_79', 'sample_80', 'sample_81', 'sample_82', 'sample_83', 'sample_84', 'sample_85', 'sample_86', 'sample_87', 'sample_88', 'sample_89', 'sample_90', 'sample_91', 'sample_92', 'sample_93', 'sample_94', 'sample_95', 'sample_96', 'sample_97', 'sample_98', 'sample_99', 'sample_100'],
'yield_NP': [102000000000.0, 135000000000.0, 104000000000.0, 108000000000.0, 107000000000.0, 102000000000.0, 103000000000.0, 105000000000.0, 98732711940.0, 102000000000.0, 177000000000.0, 120000000000.0, 98874217002.0, 109000000000.0, 100000000000.0, 109000000000.0, 97816752073.0, 99875608784.0, 105000000000.0, 114000000000.0, 91070755092.0, 103000000000.0, 94779004959.0, 110000000000.0, 110000000000.0, 111000000000.0, 109000000000.0, 107000000000.0, 112000000000.0, 112000000000.0, 105000000000.0, 108000000000.0, 112000000000.0, 113000000000.0, 99400525623.0, 115000000000.0, 107000000000.0, 103000000000.0, 106000000000.0, 105000000000.0, 105000000000.0, 109000000000.0, 103000000000.0, 110000000000.0, 113000000000.0, 120000000000.0, 119000000000.0, 156000000000.0, 128000000000.0, 99660967688.0, 110000000000.0, 101000000000.0, 121000000000.0, 112000000000.0, 110000000000.0, 108000000000.0, 102000000000.0, 110000000000.0, 101000000000.0, 139000000000.0, 149000000000.0, 94358139331.0, 102000000000.0, 101000000000.0, 108000000000.0, 96776159556.0, 126000000000.0, 131000000000.0, 99308534044.0, 104000000000.0, 120000000000.0, 172000000000.0, 100000000000.0, 102000000000.0, 112000000000.0, 155000000000.0, 97089503358.0, 109000000000.0, 103000000000.0, 102000000000.0, 125000000000.0, 101000000000.0, 99173169979.0, 104000000000.0, 97704382884.0, 115000000000.0, 106000000000.0, 111000000000.0, 107000000000.0, 112000000000.0, 103000000000.0, 126000000000.0, 132000000000.0, 99266572540.0, 106000000000.0, 139000000000.0, 113000000000.0, 100000000000.0, 114000000000.0, 122000000000.0, 126000000000.0],
'mean_NP': [30.85476, 39.54372, 31.5023, 32.88599, 30.952, 30.32588, 30.8906, 32.29805, 29.64056, 30.22417, 52.53136, 35.07535, 29.67494, 32.06474, 29.80763, 32.91384, 28.99877, 29.8512, 31.18936, 34.54803, 28.08189, 30.18906, 28.32233, 32.6702, 32.51392, 33.18012, 31.75891, 32.02777, 33.64239, 32.99544, 32.27342, 31.67663, 32.50864, 34.29474, 30.81942, 34.29637, 32.37888, 31.53656, 30.28286, 31.52802, 31.52802, 31.29889, 30.35667, 32.5761, 33.22374, 34.19891, 35.68893, 47.59501, 37.59036, 29.62502, 32.38506, 30.60525, 36.92763, 31.55724, 34.16102, 30.76239, 31.01334, 32.27204, 29.63566, 41.53544, 43.58239, 29.02033, 30.73124, 30.26892, 31.847, 30.06908, 37.48715, 39.26691, 29.89997, 31.11425, 36.34303, 51.99843, 30.48683, 30.7607, 32.35504, 46.32393, 29.48785, 32.97904, 30.14343, 30.40873, 37.91671, 31.53161, 29.89573, 30.49102, 29.88968, 33.95192, 30.3987, 33.99411, 32.28092, 33.36572, 30.42415, 38.03029, 39.33902, 28.77619, 31.0585, 41.76222, 34.08653, 29.98517, 34.66174, 36.80748, 37.63943],
'pct_NP': [95.83108, 96.13075, 95.87788, 95.94028, 95.87643, 95.82636, 95.87171, 95.91017, 95.79516, 95.78791, 96.31651, 95.99761, 95.79408, 95.89239, 95.78573, 95.90146, 95.80532, 95.84741, 95.8826, 95.99543, 95.69757, 95.80496, 95.74401, 95.93303, 95.91561, 95.9421, 95.89965, 95.92396, 95.93847, 95.93774, 95.90836, 95.87933, 95.92867, 96.00631, 95.8387, 95.97148, 95.9508, 95.93194, 95.87534, 95.91706, 95.91706, 95.91489, 95.89239, 95.94972, 96.00668, 96.00994, 96.07089, 96.27841, 96.09955, 95.82274, 95.96205, 95.90146, 96.11334, 95.92106, 96.00414, 95.87498, 95.8884, 95.93738, 95.83362, 96.18445, 96.22036, 95.80859, 95.88949, 95.83543, 95.94573, 95.84777, 96.11951, 96.14926, 95.8387, 95.90001, 96.09302, 96.35387, 95.86119, 95.9011, 95.93339, 96.26027, 95.82201, 95.97475, 95.87208, 95.86446, 96.09157, 95.90328, 95.85684, 95.88768, 95.84995, 95.99579, 95.86954, 95.99688, 95.95407, 95.98309, 95.88804, 96.1166, 96.14345, 95.8075, 95.89747, 96.20041, 95.99108, 95.86627, 96.01937, 96.08722, 96.09338],
'mad_NP': [2.4, 2.69, 2.53, 2.58, 2.85, 2.32, 2.41, 2.54, 2.26, 2.41, 3.73, 2.87, 2.28, 2.47, 2.42, 2.51, 2.52, 2.3, 2.51, 2.5, 2.39, 2.32, 2.26, 2.45, 2.58, 2.51, 2.54, 2.57, 2.7, 2.53, 2.44, 2.51, 2.61, 2.78, 2.48, 2.82, 2.61, 2.64, 2.45, 2.47, 2.47, 2.35, 2.41, 2.74, 2.89, 3.05, 2.56, 3.11, 2.62, 2.36, 2.4, 2.37, 2.85, 2.5, 2.69, 2.76, 2.44, 2.77, 2.49, 2.95, 3.1, 2.23, 2.55, 2.38, 2.5, 2.45, 2.79, 3.08, 2.41, 2.53, 2.69, 3.62, 2.45, 2.51, 2.43, 3.47, 2.86, 2.63, 2.51, 2.43, 2.74, 3.29, 2.47, 2.7, 2.4, 2.86, 2.49, 2.66, 2.5, 2.61, 2.43, 3.75, 2.77, 2.43, 2.57, 3.13, 2.54, 2.38, 2.62, 2.73, 2.8],
'pct-act_NP': [99.72261, 99.7348, 99.79733, 99.80831, 99.73196, 99.74506, 99.72588, 99.78956, 99.73939, 99.69657, 99.74559, 99.76128, 99.74523, 99.71998, 99.75593, 99.70689, 99.77984, 99.77063, 99.71659, 99.73037, 99.49053, 99.7367, 99.75454, 99.79297, 99.69296, 99.68512, 99.74522, 99.72103, 99.74315, 99.73674, 99.72944, 99.74561, 99.68827, 99.83226, 99.78345, 99.77035, 99.7133, 99.77947, 99.75018, 99.79558, 99.79558, 99.73194, 99.73659, 99.71097, 99.77643, 99.76761, 99.7517, 99.77304, 99.7544, 99.76129, 99.73501, 99.71151, 99.693, 99.71733, 99.72714, 99.80626, 99.71137, 99.74261, 99.73006, 99.8092, 99.7331, 99.72827, 99.75763, 99.7678, 99.72622, 99.52316, 99.74966, 99.74451, 99.79687, 99.75409, 99.75035, 99.745, 99.70088, 99.70653, 99.72186, 99.75905, 99.74503, 99.71645, 99.72748, 99.74403, 99.74695, 99.71049, 99.74151, 99.73246, 99.78704, 99.7469, 99.73811, 99.76458, 99.74595, 99.76743, 99.52558, 99.76455, 99.78796, 99.7336, 99.77842, 99.70977, 99.79491, 99.73274, 99.73272, 99.70917, 99.77074],
'pct-pp_NP': [97.95775, 97.92363, 98.28176, 98.3348, 97.89158, 98.09959, 97.97383, 98.12378, 97.91273, 97.78881, 98.03557, 98.045, 97.95379, 97.89142, 97.87908, 97.85116, 98.11997, 98.227, 97.8446, 97.95208, 97.29799, 98.0612, 98.06741, 98.24325, 97.88712, 97.88962, 97.79328, 97.78891, 97.92744, 97.98786, 98.04976, 97.88388, 97.78834, 98.27716, 98.20671, 98.02257, 97.98365, 98.19387, 98.05562, 98.06771, 98.06771, 97.99713, 98.03721, 97.89525, 98.12726, 98.08657, 98.01643, 98.13004, 98.08099, 98.06697, 98.05385, 97.85232, 97.84396, 97.94133, 98.20101, 98.26043, 98.02674, 98.04745, 98.03498, 98.30391, 98.18926, 98.04585, 98.1358, 98.10769, 97.99772, 97.58877, 98.10085, 97.95533, 98.15405, 98.01168, 97.97297, 98.13036, 97.77195, 97.88851, 97.94937, 98.11215, 97.916, 97.81641, 97.94631, 98.04649, 98.07409, 97.88596, 98.05292, 97.92362, 98.23961, 98.20643, 98.12377, 98.1613, 98.01535, 98.11891, 97.59924, 98.16839, 98.27147, 98.01659, 98.20429, 98.06093, 98.17081, 98.04362, 98.02972, 98.05788, 98.15844],
'mean_NP.1': [440.6, 446.7, 450.1, 452.7, 436.1, 443.9, 442.1, 447.3, 437.9, 437.3, 440.9, 432.6, 445.2, 443.9, 435.1, 445.6, 426.5, 443.8, 443.5, 446.9, 424.5, 444.0, 440.1, 458.0, 438.9, 449.1, 439.7, 454.0, 447.5, 442.8, 441.8, 435.8, 449.6, 446.4, 446.0, 441.1, 444.5, 439.4, 439.9, 427.3, 427.3, 427.2, 438.7, 454.2, 437.6, 444.4, 439.8, 441.7, 436.8, 424.5, 442.5, 440.7, 428.1, 427.6, 434.0, 434.2, 438.1, 425.5, 429.5, 436.1, 441.1, 442.6, 440.8, 440.7, 433.5, 422.8, 430.1, 432.0, 434.1, 430.9, 437.9, 435.3, 433.9, 424.1, 431.1, 422.0, 434.2, 437.2, 431.7, 437.3, 440.2, 433.1, 437.1, 425.7, 441.2, 435.9, 437.2, 445.0, 433.9, 437.2, 418.2, 432.9, 425.6, 433.9, 439.6, 451.8, 435.9, 439.6, 439.7, 441.4, 451.1],
'insert_NP': [99.7, 103.7, 101.8, 102.2, 99.2, 99.4, 99.5, 100.8, 97.7, 97.8, 100.9, 100.8, 99.5, 99.9, 99.1, 100.7, 99.9, 99.0, 101.0, 100.4, 97.7, 99.9, 101.9, 102.7, 100.3, 103.5, 99.9, 104.8, 103.1, 100.9, 100.3, 99.6, 102.8, 101.6, 101.2, 101.1, 100.5, 101.0, 100.9, 98.4, 98.4, 97.5, 101.2, 103.2, 100.0, 101.3, 100.2, 100.9, 100.2, 99.1, 101.1, 101.0, 99.3, 96.6, 99.7, 99.4, 100.1, 96.9, 98.5, 101.0, 101.4, 102.0, 101.0, 101.3, 97.6, 98.0, 99.5, 100.3, 100.5, 99.0, 101.2, 100.3, 98.2, 98.2, 97.9, 98.0, 99.3, 100.9, 98.7, 99.9, 101.0, 100.6, 101.0, 96.3, 102.0, 99.7, 99.8, 101.6, 100.6, 101.1, 95.0, 99.6, 98.8, 99.1, 100.0, 104.0, 99.0, 101.7, 101.8, 101.9, 104.1],
'rate_NP': [5.97e-09, 1.12e-06, 3.98e-06, 1.351e-06, 1.28e-06, 3.82e-09, 7.48e-07, 1.63e-06, 2.95e-09, 1.92e-06, 7.83e-07, 1.31e-06, 6.72e-09, 1.05e-06, 2.39e-09, 1.88e-06, 3.42e-09, 3.9e-10, 4.05e-09, 3.05e-09, 7.58e-10, 1.45e-06, 4.55e-09, 2.48e-09, 8.8e-07, 3.25e-09, 2.67e-09, 9.02e-09, 4.11e-09, 1.2e-06, 1.47e-06, 8.24e-07, 9.57e-09, 2.75e-09, 1.08e-06, 1.04e-06, 1.34e-09, 1.5e-09, 1.37e-06, 1.18e-08, 1.18e-08, 9.77e-09, 8.28e-07, 2.21e-09, 1.59e-09, 1.33e-09, 2.04e-09, 5.48e-07, 1.94e-09, 1.82e-09, 3.24e-09, 4.59e-06, 8.65e-07, 7.64e-10, 5.51e-06, 1.75e-09, 4.23e-10, 1.02e-06, 1.75e-09, 7.78e-07, 1.45e-06, 3.49e-09, 1.91e-08, 1.58e-06, 1.79e-06, 1.25e-09, 3.11e-09, 8.28e-07, 4.05e-09, 6.05e-07, 4.16e-09, 4.9e-07, 2.17e-09, 4.36e-09, 6.83e-10, 1.1e-06, 8.99e-09, 1.95e-06, 1.47e-09, 1.5e-06, 1.56e-06, 9.41e-07, 1.35e-09, 8.54e-09, 4.37e-09, 2.1e-06, 3.98e-09, 1.01e-08, 5.82e-09, 1.3e-09, 8.03e-10, 1.07e-06, 3.83e-09, 4.99e-09, 2.41e-09, 3.4e-09, 2.31e-09, 6.33e-09, 9.26e-09, 1.41e-09, 1.54e-06],
'yield_Arg': [101940000000.0, 134815000000.0, 104348000000.0, 108016000000.0, 106915000000.0, 101891000000.0, 102859000000.0, 104712000000.0, 98732711940.0, 101992000000.0, 176540000000.0, 119786000000.0, 98874217002.0, 108950000000.0, 100279000000.0, 109404000000.0, 97816752073.0, 99875608784.0, 105462000000.0, 114368000000.0, 91070755092.0, 102681000000.0, 94779004959.0, 109683000000.0, 109664000000.0, 110539000000.0, 109450000000.0, 107001000000.0, 111869000000.0, 112014000000.0, 104834000000.0, 108499000000.0, 111538000000.0, 112849000000.0, 99400525623.0, 114885000000.0, 107473000000.0, 102917000000.0, 105871000000.0, 105336000000.0, 105336000000.0, 109490000000.0, 103284000000.0, 110059000000.0, 113200000000.0, 119803000000.0, 119052000000.0, 155554000000.0, 128106000000.0, 99660967688.0, 110417000000.0, 100502000000.0, 120533000000.0, 111613000000.0, 110452000000.0, 107891000000.0, 101508000000.0, 109992000000.0, 101204000000.0, 138829000000.0, 148519000000.0, 94358139331.0, 101922000000.0, 101125000000.0, 107840000000.0, 96776159556.0, 125599000000.0, 131475000000.0, 99308534044.0, 104154000000.0, 119703000000.0, 172425000000.0, 100050000000.0, 102104000000.0, 112015000000.0, 155011000000.0, 97089503358.0, 109002000000.0, 102866000000.0, 102082000000.0, 125097000000.0, 101411000000.0, 99173169979.0, 104393000000.0, 97704382884.0, 114548000000.0, 106286000000.0, 110903000000.0, 106690000000.0, 112314000000.0, 102866000000.0, 125675000000.0, 131768000000.0, 99266572540.0, 106262000000.0, 138828000000.0, 113469000000.0, 100316000000.0, 113837000000.0, 121809000000.0, 125873000000.0],
'mean_Arg': [30.30078, 38.89375, 30.95051, 32.25406, 30.4547, 29.77961, 30.33201, 31.69718, 29.11294, 29.69243, 51.61069, 34.61427, 29.14371, 31.49802, 29.29912, 32.29913, 28.57639, 29.30749, 30.71611, 33.94012, 27.16736, 29.65553, 27.79295, 32.10852, 31.98217, 32.59671, 31.30704, 31.52126, 33.10581, 32.51, 31.37597, 31.18913, 31.97458, 33.82919, 29.98714, 33.74547, 31.76157, 31.02146, 29.79179, 30.91472, 30.91472, 30.81643, 29.88501, 32.00364, 32.77427, 33.77175, 35.17978, 46.80516, 37.08409, 29.11601, 31.8706, 30.02358, 35.97378, 31.0624, 33.24734, 30.31996, 30.26782, 31.78231, 29.13839, 40.87246, 42.89485, 28.40806, 30.14433, 29.77872, 31.35237, 29.2151, 36.84727, 38.58257, 29.4153, 30.60253, 35.73808, 51.06496, 29.95496, 30.15563, 31.8753, 45.5614, 28.95893, 32.38335, 29.69167, 29.92895, 37.29407, 30.83368, 29.40804, 30.01485, 29.30928, 33.36085, 29.92345, 33.40791, 31.62522, 32.8189, 29.75168, 37.41665, 38.7008, 28.32761, 30.5643, 41.01108, 33.5711, 29.38303, 33.81398, 36.10285, 36.97827],
'pct_Arg': [95.7618, 96.2904, 95.8694, 95.9667, 95.8471, 95.7173, 95.8008, 95.9272, 95.6311, 95.6681, 96.5147, 96.1337, 95.6212, 95.8792, 95.6557, 95.9107, 95.6557, 95.7026, 95.8931, 96.0641, 95.1967, 95.6822, 95.4909, 95.947, 95.9614, 96.0175, 95.9617, 95.959, 96.0227, 96.0109, 95.8615, 95.9151, 95.9779, 96.1052, 95.7308, 96.0615, 95.9864, 95.951, 95.8127, 95.9214, 95.9214, 95.9266, 95.8842, 95.9879, 96.1141, 96.1266, 96.227, 96.4836, 96.2848, 95.6862, 96.0418, 95.8872, 96.2246, 95.9483, 96.0308, 95.8528, 95.8255, 95.998, 95.7239, 96.3519, 96.407, 95.5737, 95.8251, 95.7721, 95.991, 95.6652, 96.2503, 96.2912, 95.755, 95.8799, 96.2123, 96.5405, 95.795, 95.8511, 96.0092, 96.4486, 95.6086, 96.0309, 95.8327, 95.8244, 96.2274, 95.8225, 95.7447, 95.8424, 95.7342, 96.0645, 95.8407, 96.0659, 95.9834, 96.0525, 95.8063, 96.2519, 96.3025, 95.6002, 95.898, 96.3587, 96.0856, 95.7557, 96.0889, 96.1936, 96.2291],
'mad_Arg': [4, 5, 5, 5, 5, 4, 4, 5, 4, 4, 6, 5, 4, 5, 4, 5, 4, 4, 4, 5, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 4, 4, 5, 5, 4, 5, 5, 5, 4, 4, 4, 4, 4, 5, 5, 5, 5, 6, 5, 4, 4, 4, 5, 4, 5, 5, 4, 5, 4, 5, 5, 4, 4, 4, 4, 4, 5, 5, 4, 4, 5, 6, 4, 4, 4, 6, 5, 5, 4, 4, 5, 5, 4, 5, 4, 5, 4, 5, 5, 5, 4, 5, 5, 4, 4, 5, 5, 4, 5, 5, 5],
'pct-act_Arg': [99.72261, 99.7348, 99.79733, 99.80831, 99.73196, 99.74506, 99.72588, 99.78956, 99.73939, 99.69657, 99.74559, 99.76128, 99.74523, 99.71998, 99.75593, 99.70689, 99.77984, 99.77063, 99.71659, 99.73037, 99.49053, 99.7367, 99.75454, 99.79297, 99.69296, 99.68512, 99.74522, 99.72103, 99.74315, 99.73674, 99.72944, 99.74561, 99.68827, 99.83226, 99.78345, 99.77035, 99.7133, 99.77947, 99.75018, 99.79558, 99.79558, 99.73194, 99.73659, 99.71097, 99.77643, 99.76761, 99.7517, 99.77304, 99.7544, 99.76129, 99.73501, 99.71151, 99.693, 99.71733, 99.72714, 99.80626, 99.71137, 99.74261, 99.73006, 99.8092, 99.7331, 99.72827, 99.75763, 99.7678, 99.72622, 99.52316, 99.74966, 99.74451, 99.79687, 99.75409, 99.75035, 99.745, 99.70088, 99.70653, 99.72186, 99.75905, 99.74503, 99.71645, 99.72748, 99.74403, 99.74695, 99.71049, 99.74151, 99.73246, 99.78704, 99.7469, 99.73811, 99.76458, 99.74595, 99.76743, 99.52558, 99.76455, 99.78796, 99.7336, 99.77842, 99.70977, 99.79491, 99.73274, 99.73272, 99.70917, 99.77074],
'pct-pp_Arg': [97.95775, 97.92363, 98.28176, 98.3348, 97.89158, 98.09959, 97.97383, 98.12378, 97.91273, 97.78881, 98.03557, 98.045, 97.95379, 97.89142, 97.87908, 97.85116, 98.11997, 98.227, 97.8446, 97.95208, 97.29799, 98.0612, 98.06741, 98.24325, 97.88712, 97.88962, 97.79328, 97.78891, 97.92744, 97.98786, 98.04976, 97.88388, 97.78834, 98.27716, 98.20671, 98.02257, 97.98365, 98.19387, 98.05562, 98.06771, 98.06771, 97.99713, 98.03721, 97.89525, 98.12726, 98.08657, 98.01643, 98.13004, 98.08099, 98.06697, 98.05385, 97.85232, 97.84396, 97.94133, 98.20101, 98.26043, 98.02674, 98.04745, 98.03498, 98.30391, 98.18926, 98.04585, 98.1358, 98.10769, 97.99772, 97.58877, 98.10085, 97.95533, 98.15405, 98.01168, 97.97297, 98.13036, 97.77195, 97.88851, 97.94937, 98.11215, 97.916, 97.81641, 97.94631, 98.04649, 98.07409, 97.88596, 98.05292, 97.92362, 98.23961, 98.20643, 98.12377, 98.1613, 98.01535, 98.11891, 97.59924, 98.16839, 98.27147, 98.01659, 98.20429, 98.06093, 98.17081, 98.04362, 98.02972, 98.05788, 98.15844],
'mean_Arg.1': [440.6, 446.7, 450.1, 452.7, 436.1, 443.9, 442.1, 447.3, 437.9, 437.3, 440.9, 432.6, 445.2, 443.9, 435.1, 445.6, 426.5, 443.8, 443.5, 446.9, 424.5, 444.0, 440.1, 458.0, 438.9, 449.1, 439.7, 454.0, 447.5, 442.8, 441.8, 435.8, 449.6, 446.4, 446.0, 441.1, 444.5, 439.4, 439.9, 427.3, 427.3, 427.2, 438.7, 454.2, 437.6, 444.4, 439.8, 441.7, 436.8, 424.5, 442.5, 440.7, 428.1, 427.6, 434.0, 434.2, 438.1, 425.5, 429.5, 436.1, 441.1, 442.6, 440.8, 440.7, 433.5, 422.8, 430.1, 432.0, 434.1, 430.9, 437.9, 435.3, 433.9, 424.1, 431.1, 422.0, 434.2, 437.2, 431.7, 437.3, 440.2, 433.1, 437.1, 425.7, 441.2, 435.9, 437.2, 445.0, 433.9, 437.2, 418.2, 432.9, 425.6, 433.9, 439.6, 451.8, 435.9, 439.6, 439.7, 441.4, 451.1],
'insert_Arg': [99.7, 103.7, 101.8, 102.2, 99.2, 99.4, 99.5, 100.8, 97.7, 97.8, 100.9, 100.8, 99.5, 99.9, 99.1, 100.7, 99.9, 99.0, 101.0, 100.4, 97.7, 99.9, 101.9, 102.7, 100.3, 103.5, 99.9, 104.8, 103.1, 100.9, 100.3, 99.6, 102.8, 101.6, 101.2, 101.1, 100.5, 101.0, 100.9, 98.4, 98.4, 97.5, 101.2, 103.2, 100.0, 101.3, 100.2, 100.9, 100.2, 99.1, 101.1, 101.0, 99.3, 96.6, 99.7, 99.4, 100.1, 96.9, 98.5, 101.0, 101.4, 102.0, 101.0, 101.3, 97.6, 98.0, 99.5, 100.3, 100.5, 99.0, 101.2, 100.3, 98.2, 98.2, 97.9, 98.0, 99.3, 100.9, 98.7, 99.9, 101.0, 100.6, 101.0, 96.3, 102.0, 99.7, 99.8, 101.6, 100.6, 101.1, 95.0, 99.6, 98.8, 99.1, 100.0, 104.0, 99.0, 101.7, 101.8, 101.9, 104.1],
'rate_Arg': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}
df = pd.DataFrame(data)
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