Skip to main content

Data transformation for conditional multicolour line matplotlib

This question has been asked around but I could not adapt any of the previous answers and I am looking for help. I have the following df:

myf = {'A': {0: 0.118905, 1: 0.116909, 2: 0.114422, 3: 0.111605, 4: 0.108002, 5: 0.103467, 6: 0.0982083, 7: 0.0938204, 8: 0.090206, 9: 0.0871905, 10: 0.084656, 11: 0.08252, 12: 0.0807242, 13: 0.0792274, 14: 0.0780016, 15: 0.0770298, 16: 0.0763054, 17: 0.0758326, 18: 0.0756302, 19: 0.075625, 20: 0.075625}, 'B': {0: 0.13157894736842105, 1: 0.12597030386740332, 2: 0.12036337209302327, 3: 0.1147584355828221, 4: 0.10915584415584415, 5: 0.10355603448275864, 6: 0.09795955882352941, 7: 0.09236712598425198, 8: 0.08677966101694914, 9: 0.08119839449541284, 10: 0.07562500000000003, 11: 0.07006181318681318, 12: 0.06451219512195122, 13: 0.05898116438356164, 14: 0.053476562500000005, 15: 0.04801136363636364, 16: 0.042608695652173914, 17: 0.0373141891891892, 18: 0.03223214285714286, 19: 0.02766447368421054, 20: 0.025000000000000022}, 'x': {0: 0.0, 1: 0.05, 2: 0.1, 3: 0.15, 4: 0.2, 5: 0.25, 6: 0.3, 7: 0.35, 8: 0.4, 9: 0.45, 10: 0.5, 11: 0.55, 12: 0.6, 13: 0.65, 14: 0.7, 15: 0.75, 16: 0.8, 17: 0.85, 18: 0.9, 19: 0.95, 20: 1.0}, 'y1': {0: 0.17835797265337505, 1: 0.172319328520723, 2: 0.16536874055499218, 3: 0.15767532547570168, 4: 0.1486735047377635, 5: 0.1381930294843873, 6: 0.12929509857138935, 7: 0.12325030886953686, 8: 0.11846218212072777, 9: 0.11466787144642454, 10: 0.11169732155818163, 11: 0.10944101957114595, 12: 0.10783327222854425, 13: 0.10684294528516422, 14: 0.10647160435074597, 15: 0.10675591390692067, 16: 0.10777718512747676, 17: 0.10978722893656234, 18: 0.11271967393192793, 19: 0.11343739518387072, 20: 0.11343715663665711}, 'y2': {0: 0.16620498614958448, 1: 0.16014563810628496, 2: 0.1541069497025419, 3: 0.1480924667845986, 4: 0.1421065947039973, 5: 0.1361548751486326, 6: 0.13024437716262977, 7: 0.12438426126852255, 8: 0.11858661304222927, 9: 0.11286770894705835, 10: 0.10725000000000004, 11: 0.1017653363120395, 12: 0.09646044021415827, 13: 0.09140668981047104, 14: 0.08671875000000016, 15: 0.08259297520661152, 16: 0.07939508506616252, 17: 0.07788988312636966, 18: 0.07997448979591827, 19: 0.09188019390581716, 20: 0.15000000000000116}}

I want to plot y1 line of one color if A>=B and plot y2 of a different color if A<B

I am using this code:

plt.figure()
line1,=plt.plot(myf[myf["A"]>= myf["B"]].x,
                myf[myf["A"]>= myf["B"]].y1,label=r'$y_1$')
line2,=plt.plot(myf[myf["A"]< myf["B"]].x,
                myf[myf["A"]< myf["B"]].y2,label=r'$y_2$', color='r')

however the line comes back as broken segment since the df is sparse. Someone suggests to shift and manipulate data, but I am not able to understand how I shall shift it. Do you have any idea to have the line not broken?

My approach has been to create a unique column y with the one to plot and then overlap this with y2 using a different color. But this works only when there are not discontinuities among y1 and y2.



source https://stackoverflow.com/questions/74944154/data-transformation-for-conditional-multicolour-line-matplotlib

Labels

Labels:

Comments

Post a Comment

Popular posts from this blog

Why is my reports service not connecting?

I am trying to pull some data from a Postgres database using Node.js and node-postures but I can't figure out why my service isn't connecting. my routes/index.js file: const express = require('express'); const router = express.Router(); const ordersCountController = require('../controllers/ordersCountController'); const ordersController = require('../controllers/ordersController'); const weeklyReportsController = require('../controllers/weeklyReportsController'); router.get('/orders_count', ordersCountController); router.get('/orders', ordersController); router.get('/weekly_reports', weeklyReportsController); module.exports = router; My controllers/weeklyReportsController.js file: const weeklyReportsService = require('../services/weeklyReportsService'); const weeklyReportsController = async (req, res) => { try { const data = await weeklyReportsService; res.json({data}) console...
Post a Comment
Read more

How to show number of registered users in Laravel based on usertype?

i'm trying to display data from the database in the admin dashboard i used this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count(); echo $users; ?> and i have successfully get the correct data from the database but what if i want to display a specific data for example in this user table there is "usertype" that specify if the user is normal user or admin i want to user the same code above but to display a specific usertype i tried this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count()->WHERE usertype =admin; echo $users; ?> but it didn't work, what am i doing wrong? source https://stackoverflow.com/questions/68199726/how-to-show-number-of-registered-users-in-laravel-based-on-usertype
Post a Comment
Read more

ValueError: X has 10 features, but LinearRegression is expecting 1 features as input

So, I am trying to predict the model but its throwing error like it has 10 features but it expacts only 1. So I am confused can anyone help me with it? more importantly its not working for me when my friend runs it. It works perfectly fine dose anyone know the reason about it? cv = KFold(n_splits = 10) all_loss = [] for i in range(9): # 1st for loop over polynomial orders poly_order = i X_train = make_polynomial(x, poly_order) loss_at_order = [] # initiate a set to collect loss for CV for train_index, test_index in cv.split(X_train): print('TRAIN:', train_index, 'TEST:', test_index) X_train_cv, X_test_cv = X_train[train_index], X_test[test_index] t_train_cv, t_test_cv = t[train_index], t[test_index] reg.fit(X_train_cv, t_train_cv) loss_at_order.append(np.mean((t_test_cv - reg.predict(X_test_cv))**2)) # collect loss at fold all_loss.append(np.mean(loss_at_order)) # collect loss at order plt.plot(np.log(al...
Post a Comment
Read more