#!/usr/bin/env python from pathlib import Path import matplotlib.pyplot as plt import numpy as np import pandas as pd from loguru import logger logger.add( Path("logs", "data.log"), format="{time} | {level} | {message}", level="DEBUG", rotation="1 MB", compression="zip", ) BASE_PATH = Path(__file__).parent WIND_GUSTS_PATH = BASE_PATH.joinpath("data", "vejaAtrumsBrazmas.xlsx") WIND_SPEED_PATH = BASE_PATH.joinpath("data", "vejaAtrumsFaktiskais.xlsx") AIR_TEMP_PATH = BASE_PATH.joinpath("data", "gaisaTemperatura2022.xlsx") def read_data(path: Path) -> pd.DataFrame: dataframe = pd.read_excel(path, date_parser="Datums", index_col="Datums") return dataframe def get_season(month: int) -> str | None: if month in [12, 1, 2]: return "Ziema" elif month in [3, 4, 5]: return "Pavasaris" elif month in [6, 7, 8]: return "Vasara" elif month in [9, 10, 11]: return "Rudens" else: return None def bar_chart() -> None: df_avg = read_data(WIND_SPEED_PATH).mean(axis=1) df_max = read_data(WIND_GUSTS_PATH).max(axis=1) - df_avg df_combined = pd.concat( [df_avg, df_max], axis=1, ) df_combined.columns = ["Vidējais", "Maksimālais"] df_combined.plot.bar(stacked=True, figsize=(12, 8), color=["#ff7f0e", "#1f77b4"], width=0.6) plt.yticks(np.arange(0, df_combined.max().max() + 2.5, 2.5)) plt.xticks(rotation=45) plt.title("Vidējais un maksimālais vēja ātrums 2023. gada augustā") plt.xlabel("Mērījumu Datums") plt.ylabel("Vēja ātrums (m/s)") plt.show() SEASONS = { 1: "Ziema", 2: "Pavasaris", 3: "Vasara", 4: "Rudens", } def box_plot() -> None: df = read_data(AIR_TEMP_PATH) df.index = pd.to_datetime(df.index, format="%d.%m.%Y") df["Season"] = df.index.month % 12 // 3 + 1 df["Season"] = df["Season"].map(SEASONS) plt.title("Gaisa temperatūra Rīgā četros gadalaikos") plt.ylabel("Gaisa temperatūra (Celsija grādos)") # plt.show() @logger.catch def main() -> None: # bar_chart() box_plot() if __name__ == "__main__": main()