如何解析重叠的轴记号标签

import matplotlib import matplotlib.pyplot as plt import numpy as np with open("spectrum.csv", "r") as test: rawData = test.readlines() test.close() dataProcessed = [] for x in range(1, len(rawData)): line = rawData[x].split('\n') line.pop(1) # I added this because the list always had a [''] in the end so I just removed that for data in line: finalData = data.split(',') dataProcessed.append([finalData[0], finalData[2]]) x = [] y = [] for point in dataProcessed: x.append(point[0]) y.append(point[1]) plt.plot(x, y) plt.savefig("plot1.png")

示例CSV数据

Wavelength,Flux,BestFit,SkyFlux 3809.781,29.277,26.563,4.139 3810.658,28.131,25.925,4.118 3811.536,30.299,26.545,3.995 3812.414,26.515,27.773,4.162 3813.291,26.534,26.918,4.089 3814.17,30.009,27.377,4.022 3815.048,30.768,28.017,3.925 3815.926,31.629,27.321,3.812 3816.805,32.29,26.563,3.703 3817.684,30.524,26.733,3.588 3818.563,32.006,26.96,3.481 3819.443,35.618,26.816,3.376 3820.322,27.838,27.272,3.281 3821.202,28.944,26.889,3.226 3822.082,29.651,27.091,3.163 3822.962,30.12,27.965,3.177 3823.843,31.858,27.389,3.203 3824.723,30.154,27.065,3.253 3825.604,26.587,27.186,3.356 3826.485,24.657,26.922,3.518 3827.366,24.15,26.631,3.759 3828.247,24.83,27.103,4.045 3829.129,28.454,28.112,4.338 3830.011,27.9,27.816,4.695 3830.893,26.63,27.613,4.975 3831.775,25.385,27.16,5.183 3832.657,19.389,26.798,5.228 3833.54,18.346,26.861,5.02 3834.423,17.291,27.088,4.602 3835.306,13.885,27.351,4.224 3836.189,19.341,27.105,3.973 3837.072,24.488,27.506,3.772 3837.956,20.605,27.468,3.52 3838.84,17.923,26.783,3.253 3839.724,24.792,26.986,3.144 3840.608,27.875,27.21,3.351 3841.493,28.281,27.106,3.686 3842.377,26.924,27.365,3.957 3843.262,28.649,27.668,4.097 3844.147,31.422,27.66,4.197 3845.032,27.593,27.725,4.367 3845.918,36.582,28.195,4.525 3846.803,34.788,27.889,4.473 3847.689,32.116,28.016,4.212 3848.575,40.388,27.897,3.891 3849.462,40.246,27.69,3.735 3850.348,39.531,28.53,3.8 3851.235,41.553,28.021,3.895 3852.122,40.606,28.085,3.846 3853.009,39.078,28.331,3.677 3853.896,40.404,28.439,3.505 3854.784,37.674,28.335,3.481 3855.671,40.249,28.143,3.554 3856.559,33.143,28.489,3.592 3857.447,35.211,27.918,3.376 3858.336,35.984,28.307,2.946 3859.224,31.993,28.672,2.549 3860.113,30.193,28.274,2.39 3861.002,31.871,28.326,2.64 3861.891,34.52,28.605,3.182 3862.78,38.937,28.364,3.692 3863.67,37.471,28.469,3.848 3864.56,38.229,28.839,3.714 3865.449,42.878,28.906,3.509 3866.34,44.18,28.575,3.415 3867.23,39.195,28.557,3.422 3868.121,35.928,29.104,3.423 3869.011,41.08,29.793,3.267 3869.902,44.947,30.057,2.932 3870.793,37.783,29.972,2.58 3871.685,42.001,29.8,2.405 3872.576,35.932,28.642,2.47 3873.468,30.618,28.725,2.791 3874.36,32.889,28.646,3.196 3875.252,36.743,28.452,3.482 3876.145,35.698,28.355,3.549 3877.037,34.679,27.831,3.434 3877.93,34.803,27.555,3.24 3878.823,31.762,28.165,3.094 3879.717,35.486,28.789,3.025 3880.61,32.234,28.781,2.89 3881.504,43.073,28.223,2.557 3882.398,37.754,27.779,2.616 3883.292,34.786,28.093,2.948 3884.186,30.06,29.004,3.198 3885.08,30.07,28.547,3.302 3885.975,32.837,28.299,3.163 3886.87,29.607,29.131,2.91 3887.765,28.113,29.173,2.814 3888.66,16.369,28.23,2.882 3889.556,21.369,29.077,3.014 3890.451,20.612,28.845,3.129 3891.347,25.129,28.5,3.115 3892.243,30.816,29.227,3.174 3893.14,31.399,29.674,3.409 3894.036,29.617,29.363,3.613 3894.933,31.307,29.641,3.614 3895.83,35.675,29.588,3.572 3896.727,36.238,29.645,3.66 3897.625,35.882,29.691,3.968 3898.522,39.471,29.125,4.297 3899.42,38.397,30.324,4.497 3900.318,41.237,30.222,4.637 3901.216,36.932,30.664,4.659 3902.114,36.238,30.745,4.653 3903.013,36.594,30.212,4.819 3903.912,32.248,30.775,5.054 3904.811,36.856,30.942,5.201 3905.71,38.369,30.493,5.355 3906.609,38.184,30.431,5.707 3907.509,36.815,31.033,6.334 3908.409,37.914,31.328,6.872 3909.309,36.776,30.553,6.705 3910.209,36.994,30.814,6.463 3911.11,37.82,30.853,6.565 3912.01,36.776,31.642,7.134 3912.911,36.912,31.803,8.193 3913.812,39.5,31.268,9.088 3914.714,38.868,32.019,9.052 3915.615,42.118,32.426,8.034 3916.517,40.479,31.817,6.491 3917.419,35.879,32.422,5.464 3918.321,39.773,33.025,5.005 3919.223,38.837,32.53,4.686 3920.126,34.566,32.046,4.408 3921.029,37.092,31.854,4.105 3921.931,38.079,32.648,3.795 3922.835,32.465,32.191,3.699 3923.738,35.779,32.131,3.76 3924.642,39.949,33.002,3.834 3925.545,36.507,32.641,3.776 3926.449,34.673,32.499,3.662 3927.354,32.44,32.241,3.448 3928.258,31.061,32.264,3.239 3929.163,29.86,31.924,3.06 3930.067,25.365,31.592,3.027 3930.972,20.285,32.406,3.079 3931.878,16.108,32.333,2.974 3932.783,8.464,31.719,2.772 3933.689,11.901,31.579,2.503 3934.595,9.105,31.809,2.348 3935.501,11.3,31.973,2.347 3936.407,15.472,31.981,2.424 3937.314,17.697,31.882,2.613 3938.22,21.475,31.802,2.97 3939.127,29.22,32.342,3.451 3940.034,34.875,32.428,3.933 3940.942,29.443,31.979,4.368 3941.849,32.863,32.395,4.742 3942.757,35.122,32.861,4.893 3943.665,32.882,33.195,4.755 3944.573,35.849,32.836,4.58 3945.481,39.137,32.545,4.517 3946.39,35.423,32.952,4.599 3947.299,32.631,33.38,4.732 3948.208,38.07,32.772,4.752 3949.117,40.492,33.452,4.547 3950.026,39.244,33.013,4.062 3950.936,35.841,32.668,3.783 3951.846,42.711,33.383,3.89 3952.756,37.955,33.559,4.046 3953.666,36.864,33.373,4.021 3954.577,37.677,33.836,3.947 3955.487,37.635,33.676,3.989 3956.398,38.832,33.578,4.03 3957.309,37.419,33.807,3.839 3958.221,35.287,33.42,3.354 3959.132,37.323,33.486,2.917 3960.044,37.807,33.547,2.986 3960.956,39.042,33.348,3.52 3961.868,37.46,33.185,3.983 3962.78,29.059,33.335,3.918 3963.693,28.458,33.511,3.482 3964.606,30.056,33.015,3.037 3965.519,24.355,33.21,2.801 3966.432,20.804,33.176,2.755 3967.345,14.581,32.796,2.65 3968.259,10.035,32.722,2.465 3969.173,6.802,33.192,2.385 3970.087,11.351,33.121,2.308 3971.001,12.799,33.371,2.415 3971.915,14.969,33.086,2.601 3972.83,21.03,32.677,2.828 3973.745,27.162,32.513,3.109 3974.66,30.147,32.153,3.459 3975.575,32.133,31.959,3.831 3976.491,35.522,32.74,4.172 3977.407,34.37,33.436,4.41 3978.323,37.396,33.547,4.564 3979.239,37.756,33.418,4.677 3980.155,36.92,33.69,4.684 3981.072,39.976,34.481,4.662 3981.988,40.462,35.254,4.552 3982.905,37.624,34.921,4.43 3983.823,36.675,34.309,4.408 3984.74,36.654,34.394,4.398 3985.658,36.696,34.9,4.316 3986.576,37.889,35.089,4.15 3987.494,40.251,35.655,4.096 3988.412,42.696,35.514,4.292 3989.33,39.619,35.239,4.582 3990.249,39.883,35.171,4.602 3991.168,41.244,35.079,4.274 3992.087,42.856,36.629,3.956 3993.006,45.244,36.256,4.056 3993.926,43.965,36.159,4.491 3994.846,41.298,36.398,4.589 3995.766,36.343,36.138,4.375 3996.686,38.971,35.784,4.233 3997.606,43.331,36.191,4.353 3998.527,39.317,36.806,4.659 3999.447,37.275,36.643,4.82 4000.369,43.458,36.351,4.834 4001.29,45.568,36.296,4.839 4002.211,41.534,36.107,4.822 4003.133,43.445,36.789,4.52 4004.055,42.207,36.874,4.218 4004.977,40.576,37.235,4.147 4005.899,40.38,36.997,4.513 4006.822,39.185,36.367,4.866 4007.744,41.485,37.101,4.933 4008.667,43.623,37.592,5.019 4009.59,42.611,36.833,5.293 4010.514,40.328,36.528,5.563 4011.437,42.963,36.917,5.569 4012.361,49.276,37.322,5.36 4013.285,46.849,37.412,5.33 4014.209,45.608,37.479,5.35 4015.134,43.334,37.084,5.264 4016.058,46.71,37.03,5.012 4016.983,45.108,37.337,4.727 4017.908,40.795,37.498,4.592 4018.833,42.07,37.422,4.679 4019.759,45.844,37.999,5.029 4020.685,43.795,38.164,5.458 4021.61,40.672,37.96,5.798 4022.537,47.036,37.873,5.918 4023.463,46.003,37.821,5.656 4024.389,45.833,37.525,5.687 4025.316,41.975,38.038,5.684 4026.243,43.889,37.968,5.394 4027.17,46.096,37.946,5.133 4028.098,49.21,38.021,5.005 4029.025,46.863,38.248,4.95 4029.953,40.897,38.79,4.927 4030.881,41.755,38.537,4.851 4031.809,41.409,38.437,4.936 4032.738,38.708,38.165,4.773 4033.667,41.513,37.874,4.693 4034.596,40.048,37.881,4.782 4035.525,40.512,38.07,4.765 4036.454,45.941,38.057,4.573 4037.383,45.672,38.557,4.729 4038.313,46.59,38.569,4.983 4039.243,48.504,38.275,5.079 4040.173,43.773,38.182,5.036 4041.104,43.953,38.344,5.181 4042.034,42.36,38.887,5.638 4042.965,46.581,38.868,5.943 4043.896,42.815,38.715,5.882 4044.827,41.355,39.108,6.316 4045.759,40.698,39.5,8.308 4046.691,35.173,38.809,11.222 4047.622,38.985,38.558,12.702 4048.555,45.635,39.071,11.698 4049.487,42.769,38.734,9.016 4050.419,45.247,38.082,6.842 4051.352,44.861,38.379,5.857 4052.285,46.624,39.325,5.623 4053.218,42.318,38.625,5.466 4054.152,46.103,38.631,5.493 4055.085,42.241,38.788,5.759 4056.019,40.872,38.873,5.717 4056.953,43.14,38.725,5.231 4057.887,44.023,38.097,4.769 4058.822,42.515,38.113,4.796 4059.757,41.349,39.372,5.1 4060.692,45.422,39.138,5.305 4061.627,40.033,38.308,5.452 4062.562,43.366,38.315,5.532 4063.498,41.838,38.616,5.512 4064.433,40.254,38.697,5.542 4065.369,39.571,38.823,5.698 4066.305,42.905,38.511,5.702 4067.242,43.824,38.489,5.706 4068.178,42.651,39.051,5.501 4069.115,46.305,39.323,5.718 4070.052,45.754,39.109,6.186 4070.99,39.927,38.662,6.008 4071.927,39.61,38.669,5.499 4072.865,41.419,39.077,5.208 4073.803,41.941,39.278,5.209 4074.741,42.379,38.857,5.32 4075.679,44.267,38.518,5.487 4076.618,43.886,38.73,5.837 4077.557,41.524,38.786,6.292 4078.496,40.525,38.787,6.399 4079.435,40.138,38.895,6.128 4080.374,42.298,38.856,5.952 4081.314,43.228,38.854,6.049 4082.254,42.203,38.989,6.065 4083.194,43.848,38.352,5.762 4084.134,42.291,38.03,5.33 4085.075,37.586,38.621,5.098 4086.015,39.919,38.861,5.25 4086.956,42.652,38.163,5.59 4087.898,41.081,38.48,5.772 4088.839,44.652,38.593,5.537 4089.781,45.476,38.672,5.067 4090.722,41.455,38.698,4.821 4091.664,45.812,38.131,4.977 4092.607,44.837,38.804,5.247 4093.549,39.137,38.664,5.35 4094.492,40.314,38.39,5.179 4095.435,41.128,38.299,5.01 4096.378,41.231,38.208,4.828 4097.321,41.45,38.042,4.531 4098.265,38.232,37.959,4.268 4099.208,34.352,38.176,4.298 4100.152,31.64,38.115,4.414 4101.097,28.752,37.866,4.405 4102.041,25.474,37.974,4.177 4102.986,24.102,38.476,3.986 4103.931,28.525,38.125,4.07 4104.876,30.506,38.05,4.289 4105.821,34.475,37.751,4.462 4106.766,40.342,37.952,4.559 4107.712,41.022,38.315,4.664 4108.658,37.885,37.691,4.787 4109.604,37.741,38.663,4.843 4110.551,39.544,39.078,4.743 4111.497,41.135,38.882,4.555 4112.444,40.906,38.726,4.503 4113.391,41.507,38.868,4.667 4114.338,41.845,38.969,4.815 4115.286,45.769,38.77,4.825 4116.233,46.959,39.107,4.859 4117.181,44.247,39.577,5.003 4118.13,44.074,39.735,5.014 4119.078,44.291,39.689,4.661 4120.026,42.701,39.861,4.206 4120.975,41.609,40.091,4.186 4121.924,45.817,40.64,4.557 4122.873,46.467,40.681,4.863 4123.823,43.872,40.222,4.808 4124.772,41.118,40.022,4.74 4125.722,45.17,40.53,5.004 4126.672,46.659,40.748,5.249 4127.623,41.615,41.434,5.137 4128.573,40.681,41.107,5.002 4129.524,42.41,40.543,5.125 4130.475,44.146,40.516,5.03 4131.426,41.064,40.426,4.953 4132.378,46.715,40.514,5.224 4133.329,44.575,40.415,5.285 4134.281,41.993,40.947,5.025 4135.233,44.816,41.065,4.874 4136.185,43.665,40.913,4.998 4137.138,42.762,41.978,5.071 4138.091,44.96,41.998,4.965 4139.044,44.864,41.806,5.003 4139.997,52.098,41.81,5.163 4140.95,50.878,41.705,5.254 4141.904,48.602,41.545,5.086 4142.858,42.453,41.728,4.599 4143.812,45.305,41.595,4.344 4144.766,40.753,41.938,4.477 4145.72,44.908,41.568,4.734 4146.675,48.721,41.642,4.839 4147.63,46.285,42.043,4.781 4148.585,46.712,41.12,4.667 4149.54,45.368,41.707,4.483 4150.496,47.069,41.828,4.229 4151.452,46.886,42.14,4.222 4152.408,46.696,42.195,4.424 4153.364,44.849,42.081,4.548 4154.321,42.092,42.744,4.539 4155.277,41.254,42.76,4.646 4156.234,43.866,42.704,4.889 4157.191,45.11,41.949,5.07 4158.149,44.321,41.953,5.095 4159.106,44.915,42.638,5.068 4160.064,44.457,42.077,5.087 4161.022,42.469,42.309,5.162 4161.98,43.024,42.093,5.191 4162.939,46.248,42.476,5.28 4163.897,48.0,43.005,5.588 4164.856,45.245,42.881,5.973 4165.815,47.182,42.547,6.091 4166.775,49.668,43.119,5.929 4167.734,49.06,42.436,5.763 4168.694,47.05,42.376,5.747 4169.654,43.81,42.646,5.668 4170.614,42.28,42.689,5.559 4171.574,46.025,42.913,5.573 4172.535,41.371,42.372,5.448 4173.496,40.295,43.106,5.25 4174.457,39.916,42.924,5.203 4175.418,43.529,42.528,5.229 4176.38,42.327,42.747,5.138 4177.342,43.5,42.535,5.022 4178.304,44.608,42.143,5.056 4179.266,42.908,43.058,5.122 4180.228,44.382,43.003,5.125 4181.191,44.824,42.572,5.226 4182.154,43.957,42.867,5.081 4183.117,44.89,43.143,4.657 4184.08,44.32,42.636,4.448 4185.044,44.225,44.027,4.649 4186.007,44.878,43.833,4.648 4186.971,40.515,43.353,4.433 4187.936,41.693,43.819,4.302 4188.9,44.672,43.453,4.34 4189.865,44.577,43.121,4.441 4190.83,45.397,43.519,4.519 4191.795,43.017,43.561,4.689 4192.76,45.472,43.797,4.889 4193.725,45.144,44.25,4.895 4194.691,49.689,43.938,4.772 4195.657,46.484,44.202,4.638 4196.623,43.691,43.941,4.376 4197.59,43.344,43.524,4.183 4198.556,40.786,43.813,4.009 4199.523,42.307,44.315,3.913 4200.49,46.108,43.914,4.059 4201.458,44.772,44.366,4.262 4202.425,45.285,44.185,4.129 4203.393,44.683,43.843,3.93 4204.361,48.758,43.965,4.146 4205.329,42.15,44.256,4.286 4206.298,44.895,44.063,4.402 4207.266,46.958,44.224,4.736 4208.235,46.017,44.422,5.063 4209.204,46.044,45.001,5.088 4210.174,45.227,45.07,4.814 4211.143,45.647,44.552,4.559 4212.113,50.86,44.655,4.524 4213.083,51.639,44.845,4.57 4214.053,43.285,44.814,4.628 4215.023,45.655,44.955,4.551 4215.994,43.27,44.964,4.388 4216.965,44.799,44.561,4.313 4217.936,47.043,44.171,4.436 4218.907,44.311,44.441,4.487 4219.879,44.773,44.61,4.432 4220.851,47.821,45.088,4.433 4221.823,48.352,45.101,4.519 4222.795,44.853,44.378,4.551 4223.767,42.696,44.16,4.46 4224.74,46.553,45.173,4.35 4225.713,41.253,45.469,4.222 4226.686,39.142,45.08,3.905 4227.659,41.498,44.523,3.664 4228.633,41.016,44.053,3.774 4229.607,46.526,43.766,4.159 4230.581,47.547,44.052,4.442 4231.555,48.304,44.563,4.455 4232.53,47.861,44.376,4.404 4233.504,44.356,44.344,4.388 4234.479,43.337,44.796,4.321 4235.454,42.488,44.8,4.224 4236.43,41.989,44.911,4.371 4237.405,45.706,44.492,4.528 4238.381,42.583,44.437,4.317 4239.357,45.088,44.37,4.109 4240.333,43.99,44.16,3.921 4241.31,45.802,44.503,4.158 4242.287,45.739,44.741,4.433 4243.263,45.605,45.204,4.305 4244.241,45.592,45.273,4.293 4245.218,44.803,45.089,4.696 4246.196,45.524,45.086,5.215 4247.173,44.026,45.2,5.437 4248.152,48.12,44.813,5.622 4249.13,42.682,44.491,5.411 4250.108,44.889,45.34,4.66 4251.087,44.127,45.687,4.462 4252.066,44.367,44.905,4.727 4253.045,46.884,44.836,4.92 4254.025,49.188,45.359,4.895 4255.004,46.829,45.522,4.813 4255.984,44.365,45.7,4.774 4256.964,47.708,45.629,4.774 4257.945,48.823,45.41,4.92 4258.925,47.565,45.66,5.022 4259.906,45.549,45.487,4.708 4260.887,48.647,44.794,4.328 4261.868,42.064,44.919,4.257 4262.849,47.205,45.381,4.421 4263.831,50.772,45.396,4.523 4264.813,46.59,45.286,4.562 4265.795,43.715,45.68,4.773 4266.778,44.791,45.736,5.105 4267.76,45.026,46.235,5.124 4268.743,44.621,46.081,4.86 4269.726,46.467,45.267,4.824 4270.709,45.637,45.544,4.824 4271.693,40.917,45.649,4.604 4272.676,43.478,44.88,4.4 4273.66,43.376,44.912,4.469

1条回答

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1楼 · 发布于 2024-10-05 10:34:47

使用OP中的数据和问题中的代码，会产生与问题中所示相同的意外绘图
给出了读取数据的原始方法
有许多不必要的步骤
绘图不起作用，因为数据从未从str转换为float。
使用x.append(float(point[0]))&y.append(float(point[1]))
一旦数据位于正确的dtype中，API将更好地分隔轴刻度标签。当轴值为字符串时，每个值都显示为记号标签
此问题是将string{}数据传递到绘图API的结果。
通过将数据转换为正确的type（例如int、float、datetime）来解决此问题
另见What is plotted when string data is passed to the matplotlib API?
原来的实施是固定的
可以使用^{}模块，但是下面修复了现有代码
data = 'spectrum.csv' with open(data, "r") as f: rawData = [line.strip().split(',') for line in f] # remove \n from each string and split into a list wavelength = list() bestfit = list() for x in rawData[1:]: # iterate through the raw data rows wavelength.append(float(x[0])) # add data to list and convert to float bestfit.append(float(x[2])) # add data to list and convert to float # plot p = plt.plot(wavelength, bestfit) # generates plot of BestFit line as above
使用pandas
使用^{}自动读取带有正确dtype的float的数据，然后生成所需的绘图
import pandas as pd import matplotlib.pyplot as plt # created dataframe df = pd.read_csv('spectrum.csv') # display dataframe Wavelength Flux BestFit SkyFlux 0 3809.781 29.277 26.563 4.139 1 3810.658 28.131 25.925 4.118 2 3811.536 30.299 26.545 3.995 3 3812.414 26.515 27.773 4.162 4 3813.291 26.534 26.918 4.089 # print(df.info()) <class 'pandas.core.frame.DataFrame'> RangeIndex: 3840 entries, 0 to 3839 Data columns (total 4 columns): # Column Non-Null Count Dtype - - 0 Wavelength 3840 non-null float64 1 Flux 3840 non-null float64 2 BestFit 3840 non-null float64 3 SkyFlux 3840 non-null float64 dtypes: float64(4) memory usage: 120.1 KB # plot dataframe ax = df.plot(x='Wavelength') ax.set_yscale('log') plt.show()
作为子地块
axes = df.plot(x='Wavelength', subplots=True, layout=(3, 1), sharey=True) axes = axes.ravel() for ax in axes: ax.set_yscale('log') plt.show()

示例CSV数据

原来的实施是固定的

使用`pandas`

作为子地块

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