CODEWITHSUNDEEP
pythonmatplotlibseaborndata-visualization
pfnuesel
pfnuesel

Reputation: 15320

Plot a list of tuples, consisting of a datetime object and a numeric value

I have a dictionary where the value is a list of tuples. The tuple consists of a datetime object and a numeric value, e.g.:

{
    'option1': [
        (datetime.datetime(2021, 8, 6, 6, 11, 29), 2480.82),
        (datetime.datetime(2021, 8, 6, 6, 21, 36), 2499.14),
        (datetime.datetime(2021, 8, 6, 6, 31, 40), 2488.59),
        (datetime.datetime(2021, 8, 6, 6, 41, 44), 2486.51),
    ],
    'option2': [
        (datetime.datetime(2021, 8, 6, 6, 11, 30), 560.56),
        (datetime.datetime(2021, 8, 6, 6, 21, 36), 1100.19),
        (datetime.datetime(2021, 8, 6, 6, 31, 40), 795.54),
        (datetime.datetime(2021, 8, 6, 6, 41, 44), 873.97),
    ],
}

Now I would like to plot values against time, one line for every key (in this case "option1" and "option2"). With matplotlib, I started looping over the dict.items(), nested looping over the list, and then dissecting the tuple. However, I wonder if there is a more elegant way, either in matplotlib or any other visualization library. I do not neccessarily need to use matplotlib.

Upvotes: 1

Views: 381

Answers (1)

Roman Pavelka
Roman Pavelka

Reputation: 4181

zip built-in function together with argument unpacking would do the trick:

import datetime

import matplotlib.pyplot as plt

data = {
    'option1': [
        (datetime.datetime(2021, 8, 6, 6, 11, 29), 2480.82),
        (datetime.datetime(2021, 8, 6, 6, 21, 36), 2499.14),
        (datetime.datetime(2021, 8, 6, 6, 31, 40), 2488.59),
        (datetime.datetime(2021, 8, 6, 6, 41, 44), 2486.51),
    ],
    'option2': [
        (datetime.datetime(2021, 8, 6, 6, 11, 30), 560.56),
        (datetime.datetime(2021, 8, 6, 6, 21, 36), 1100.19),
        (datetime.datetime(2021, 8, 6, 6, 31, 40), 795.54),
        (datetime.datetime(2021, 8, 6, 6, 41, 44), 873.97),
    ],
}

for option, tuples in data.items():
    x, y = zip(*tuples)
    plt.plot(x, y, label=option)

plt.legend()
plt.show()

Upvotes: 1

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