plotting a beautiful timeseries plot-CodePudding

I have three columns of time series data. I would like to plot the three time series one upon another beautifully in one plot. A star needs to be placed in the respective 5th, 8th, and 10th data points of each time series. My goal is to implement it in Python. I would appreciate if Experts could offer a more efficient method of doing it.

My code:

import matplotlib.pyplot as plt
import numpy as np
data=np.loadtxt("data_3_timeseries")
data.plot()
plt.show()

data_3_timeseries is attached here

-0.00831 -0.0213 -0.0182
0.0105 -0.00767 -0.012
0.00326 0.0148 -0.00471
-0.0263 -0.00318 0.011
0.012 0.0398 0.0117
-0.0156 -0.0133 0.02
-0.0482 -0.00783 -0.0162
0.0103 -0.00639 0.0103
0.0158 0.000788 -0.00484
-0.000704 -0.0236 0.00579
0.00151 -0.0135 -0.0195
-0.0163 -0.00185 0.00722
0.0207 0.00998 -0.0387
-0.0246 -0.0274 -0.0108
0.0123 -0.0155 0.0137
-0.00963 0.0023 0.0305
-0.0147 0.0255 -0.00806
0.000488 -0.0187 5.29e-05
-0.0167 0.0105 -0.0204
0.00653 0.0176 -0.00643
0.0154 -0.0136 0.00415
-0.0147 -0.00339 0.0175
-0.0238 -0.00284 0.0204
-0.00629 0.0205 -0.017
0.00449 -0.0135 -0.0127
0.00843 -0.0167 0.00903
-0.00331 7.2e-05 -0.00281
-0.0043 0.0047 0.00681
-0.0356 0.0214 0.0158
-0.0104 -0.0165 0.0092
0.00599 -0.0128 -0.0202
0.015 -0.0272 0.0117
0.012 0.0258 -0.0154
-0.00509 -0.0194 0.00219
-0.00154 -0.00778 -0.00483
-0.00152 -0.0451 0.0187
0.0271 0.0186 -0.0133
-0.0146 -0.0416 0.0154
-0.024 0.00295 0.006
-0.00889 -0.00501 -0.028
-0.00555 0.0124 -0.00406
-0.0185 -0.0114 0.0224
0.0143 0.0204 -0.0193
-0.0168 -0.00608 0.00178
-0.0159 0.0189 0.0109
-0.0213 -0.007 -0.0323
0.0031 0.0207 -0.00333
-0.0202 -0.0157 -0.0105
0.0159 0.00216 -0.0262
0.0105 -0.00292 0.00447
0.0126 0.0163 -0.0141
0.01 0.00679 0.025
0.0237 -0.0142 -0.0149
0.00394 -0.0379 0.00905
-0.00803 0.0186 -0.0176
-0.013 0.0162 0.0208
-0.00197 0.0313 -0.00804
0.0218 -0.0249 0.000412
-0.0164 0.00681 -0.0109
-0.0162 -0.00795 -0.00279
-0.01 -0.00977 -0.0194
-0.00723 -0.0464 0.00453
-0.000533 0.02 -0.0193
0.00706 0.0391 0.0194

CodePudding user response：

Something like this? Note: I did not use your columns correctly, but the principle stands.

markers = [5, 8, 10]

plt.plot(data[:len(data) // 3],
        color='Blue',)

for marker in markers:
    plt.plot(marker,
             data[:len(data) // 3][marker],
             marker="*",
             color='blue')

plt.plot(data[len(data) // 3 : len(data) // 3 * 2],
        color='orange')

plt.plot(data[len(data) // 3 * 2 : len(data) // 3 * 3],
        color='green')

I only placed markers for the first data column, but you can do the same for all the columns.

Output:

You can of course further prettify your plot. Enough options with Matplot.

CodePudding user response：

Due to your identical columns, the lines are lining one over the other.

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

data = pd.DataFrame(np.loadtxt("data_3_timeseries"), columns=list('ABC'))
ax = data.plot()
for col, place, line in zip(list('ABC'), [5, 8, 10], ax.lines):
    ax.plot(place, data[col][place], marker="*", c=line.get_color())
plt.show()

"NORMALIZED"

data = pd.DataFrame(np.loadtxt("data_3_timeseries"), columns=list('ABC'))
data['B'] = data['B'].apply(lambda x: x   0.3)
data['C'] = data['C'].apply(lambda x: x   0.6)
ax = data.plot()
for col, place, line in zip(list('ABC'), [5, 8, 10], ax.lines):
    ax.plot(place, data[col][place], marker="*", c=line.get_color())
plt.show()