How do I plot list of tuples in Python and change x axis into another array?

Question

Here is my data:

('2022-04-23 14:51', 'customer1', 50, 'red')
('2022-04-23 16:19', 'customer2', 50, 'red')
('2022-04-23 16:20', 'customer2', 50, 'red')
('2022-04-23 16:34', 'customer3', 50, 'red')
('2022-04-23 17:25', 'customer4', 50, 'red')
('2022-04-23 17:37', 'customer5', 50, 'red')
('2022-04-23 18:29', 'customer6', 50, 'red')
('2022-04-23 18:33', 'customer7', 50, 'red')

The x represents time, y represents customer, using this code, I have generated a picture:

import matplotlib.pyplot as plt

plt.scatter(*zip(*qr_dict)) # this is a list of tuples
plt.xlabel('time')
plt.ylabel('customer')
plt.xticks(rotation=270)
plt.subplots_adjust(bottom=0.55)
plt.grid()
plt.show()

However, I want to change x axis into a time span from 2022-04-23 00:00 to 2022-04-23 24:00, and interval is 5 minute, how am I suppose to do that?

nicc96 · Accepted Answer · 2022-04-23 13:31:24Z

2

Note: '2022-04-23 00:00' and '2022-04-23 24:00' are the same date, so your x axis can be from '2022-04-23 00:00' to '2022-04-24 00:00'.

You can obtain the x axis in this way:

from datetime import datetime, timedelta
import numpy as np

x_start = datetime.strptime('2022-04-23 00:00', "%Y-%m-%d %H:%M")
x_end = datetime.strptime('2022-04-24 00:05', "%Y-%m-%d %H:%M")

timestamps = np.arange(x_start, x_end, timedelta(minutes=5), dtype=datetime)

x_axis = [timestamp.strftime("%Y-%m-%d %H:%M") for timestamp in timestamps]

edited Apr 23, 2022 at 13:31

answered Apr 23, 2022 at 13:18

nicc96

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4 Comments

rickandmorty Over a year ago

Thank you very much, I've tried this, but it's not what I want. I want to reset the x axis like you wrote, and at the same time, I need to show these data in picture

nicc96 Over a year ago

You have to set plt.xticks to show the labels of the x axis

rickandmorty Over a year ago

Actually, I did use plt.xticks to show the labels of the x axis, but it didn't show the time interval on x axis

rickandmorty Over a year ago

I've solved this, nicc96 was right, the reason that I didn't get what I want is that I need to cluster my data

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