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Let's test the logic with hardcoded values from the second data point (1.86 meters of elevation gained over 87.59 meters): (1.86 / 87.59) * 100 We can estimate the average gradient between two data points by dividing the elevation difference between them with the distance covered and multiplying the results by 100. We'll do our best, but everything you'll see from this point is just an estimation. Our data is quite limited, as we only have 835 data points spread over 36 kilometers.
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How to Calculate Gradient from a Strava RouteĪ gradient is nothing but a slope of the surface you're riding on. We can use the elevation difference and distance data to estimate average gradients on each of 835 individual segments.
To recap, there are 835 data points in total on this 36,4-kilometer route, so there are on average 43,6 meters between data points. Read the last week's article if you don't have the route dataset in this format. Route_df.head() Image 1 - Strava route dataset with distance and elevation data (image by author) Plt.rcParams = Falseįrom here, load the route dataset: route_df = pd.read_csv('./data/route_df_elevation_distance.csv') To start, import the usual suspects and tweak Matplotlib's default styling: import numpy as np We won’t bother with GPX files today, as we already have route data points, elevation, and distance extracted to a CSV file.
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You can download the source code on GitHub. We have a lot to cover today, so let's dive straight in.ĭon't feel like reading? Watch my video instead: These represent the slope of the surface you're riding on.Īs it turns out, you can estimate them effortlessly with basic Python and math skills. One thing cyclists love talking about is gradients. It was a step in the right direction, as you'll need both elevation and distance data today. Last week you've seen how easy it is to calculate the elevation difference and distance of a Strava route. Track your workouts using GPS, analyze your stats, reach your fitness goals, and be part of our global community of millions of fitness enthusiasts and athletes.Part 4/6 - Calculate and visualize gradients of a Strava route GPX files with Python Get the most out of your runs, walks, rides, and other workouts with our top-rated fitness tracking and personal training app. Come experience our passion to make riding easy, safe and fun for cyclists worldwide.
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