multicolored time series line plot based on condition in python using line collection

Question

Example Plot I have a dataframe that includes time series of snow-water and temperature data. I am looking to create a time series plot of snow water, that shows two colors in the snow water line plot, 'blue' if the temperature is < = 273 deg K and 'red' if the temperature is > 273 deg K. I tried to follow the matplotib documentation (https://matplotlib.org/3.1.1/gallery/lines_bars_and_markers/multicolored_line.html) but have not been successful. Would appreciate some insights. Thank you!

My dataframe is as follows: Date (datetime64[ns]); Snow-water (float64) and Temp (float64)

from matplotlib.collections import LineCollection

Date                  Snowwater  Temperature
2014-01-01 01:00:00   5           240
2014-01-01 02:00:00   10          270
2014-01-01 03:00:00   11          273
2014-01-01 04:00:00   15          279
2014-01-01 05:00:00   20          300
2014-01-01 06:00:00   25          310

I am looking for output something like in the example plot linked above but with snow-water values in the y-axis (line color blue or red depending on the temperature) and datetime on the x-axis

Please post the relevant code that you've written and explain why it didn't work. — ewokx
– ewokx, Commented Sep 10, 2020 at 4:18

esthapit · Accepted Answer · 2020-09-10 16:03:53Z

1

This did the trick although there might be better way of doing it:

colors=['blue' if x < 273 else 'red' for x in df['AIR_T[K]']]
x = mpd.date2num(df['Date'])
y = df['SWE_St'].values
points = np.array([x, y]).T.reshape(-1, 1, 2)
segments = np.concatenate([points[:-1], points[1:]], axis=1)
lc = LineCollection(segments, colors=colors)

fig, ax = plt.subplots()
ax.add_collection(lc)
ax.autoscale()
ax.xaxis.set_major_locator(mpd.MonthLocator())
ax.xaxis.set_major_locator(ticker.MultipleLocator(200))
ax.xaxis.set_major_formatter(mpd.DateFormatter('%Y-%m-%d:%H:%M:%S'))
plt.setp(ax.xaxis.get_majorticklabels(), rotation=70)
plt.show()

result plot

edited Sep 10, 2020 at 16:03

answered Sep 10, 2020 at 15:29

esthapit

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r-beginners · Accepted Answer · 2020-09-10 04:27:15Z

0

I created the data manually, but LineCollection is a This is an object that contains multiple lines, the first argument being a list of lines.

import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection

xs = [0, 1, 2, 3, 4, 5]
ys = [-2, -1, 0, 1, 5, 10]
lines = [[(x1, y1), (x2, y2)] for x1, y1, x2, y2 in zip(xs, ys, xs[1:], ys[1:])]

colors = ['r', 'r', 'b', 'b', 'b']
lc = LineCollection(lines, colors=colors)

fig, ax = plt.subplots()
ax.add_collection(lc)
ax.autoscale()
plt.show()

edited Sep 10, 2020 at 4:27

answered Sep 10, 2020 at 4:19

r-beginners

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3 Comments

esthapit Over a year ago

Thanks, I got some ideas from your post although it didn't exactly answer my question...

r-beginners Over a year ago

What's the difference? The data has been corrected after the answer and the expected graphs have been added.

esthapit Over a year ago

The data wasn't corrected, I just changed the unit of temperature from deg C to deg K, the question was still the same...the difference is that i needed time on the x-axis and y-axis depended on an another variable...i managed to get something after going through many other codes including yours... i added the graph i got so that others with similar question can benefit...i do sincerely appreciate your contribution!

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