GoogleEarthEngine/00090_python_series_plot at main · paulowpc/GoogleEarthEngine · GitHub

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"""GEE_0005_temperature_plot3.ipynb


Tutorial Code by Amirhossein Ahrari
YouTube: https://www.youtube.com/@amirhosseinahrarigee
Tutorial Video: Google Earth Engine Tutorial-95: Time Series Plot using Google Colab

This code is part of a tutorial series on Earth Engine programming techniques
presented on the Amirhossein Ahrari YouTube channel. You are free to use and modify
this code for academic and non-academic purposes. Don't forget to subscribe to
the Amirhossein Ahrari channel and follow the videos to support the instructor!

"""

import ee
import geemap as gee

ee.Authenticate()
ee.Initialize(project = 'ee-amirhosseinahrari')

temp = ee.ImageCollection("ECMWF/ERA5_LAND/MONTHLY_AGGR").filterDate('2022','2024').select('temperature_2m')

temp

map = gee.Map(basemap = 'SATELLITE')
map

roi = map.draw_last_feature.geometry()

roi

def temp_val(img):
  date = img.date().format('YYYY-MM-dd')
  temp_mean = img.reduceRegion(reducer = ee.Reducer.mean(), geometry = roi, scale = 10000).values().get(0)
  return ee.Feature(None, {'date': date, 'temp': temp_mean})

features = temp.map(temp_val)

features

data_list = features.toList(features.size()).getInfo()

data_list

date = [item['properties']['date'] for item in data_list]
temp_list = [item['properties']['temp'] for item in data_list]

temp_list

import pandas as pd

df = pd.DataFrame({'date': date, 'temp': temp_list}).round(2)

df

df.to_csv('temp_2022-2023.csv')

df['date'] = pd.to_datetime(df['date'])

import matplotlib.pyplot as plt

plt.plot(df['date'], df['temp'], lw = 2, ls = '--', color = 'red', marker = 'o')
plt.title('temperature')
plt.ylabel('K$^o$')
plt.savefig('temp_fig.png',dpi = 360)