Buckets:
| import json | |
| import os | |
| import numpy as np | |
| import pandas as pd | |
| import requests | |
| from io import BytesIO | |
| YEAR = 2018 | |
| events = [ | |
| "Bahrain Grand Prix", | |
| "Chinese Grand Prix", | |
| "Azerbaijan Grand Prix", | |
| "Spanish Grand Prix", | |
| "Monaco Grand Prix", | |
| "Canadian Grand Prix", | |
| "French Grand Prix", | |
| "Austrian Grand Prix", | |
| "British Grand Prix", | |
| "German Grand Prix", | |
| "Hungarian Grand Prix", | |
| "Belgian Grand Prix", | |
| "Italian Grand Prix", | |
| "Singapore Grand Prix", | |
| "Mexican Grand Prix", | |
| "Brazilian Grand Prix", | |
| "Abu Dhabi Grand Prix", | |
| "Russian Grand Prix", | |
| "Japanese Grand Prix", | |
| "United States Grand Prix", | |
| ] | |
| def get_overtakes(year: int, event: str) -> any: | |
| def get_overtakes_df(year, event): | |
| if year == 2023: | |
| url = "https://docs.google.com/spreadsheets/d/1M4aepPJaIfdqE9oU3L-2CQqKIyubLXG4Q4cqWnyqxp4/export?format=csv" | |
| if year == 2022: | |
| url = "https://docs.google.com/spreadsheets/d/1cuS3B6hk4iQmMaRQoMTcogIInJpavnV7rKuEsiJnEbU/export?format=csv" | |
| if year == 2021: | |
| url = "https://docs.google.com/spreadsheets/d/1ANQnPVkefRmvzrmGvEqXoqQ4dBfgcI_R9FPg-0BcM34/export?format=csv" | |
| if year == 2020: | |
| url = "https://docs.google.com/spreadsheets/d/1eG9WTkXKzFT4NMh-WqHOMs5G0UuPGnb6wP4CnFD8uzY/export?format=csv" | |
| if year == 2019: | |
| url = "https://docs.google.com/spreadsheets/d/10nHg7BIs5ySh_dE9uuIz2lq-gRWcg02tIMr0EPgPvJs/export?format=csv" | |
| if year == 2018: | |
| url = "https://docs.google.com/spreadsheets/d/1MyAwQdczccdca_FAIiZKkqZNauNh3ts99JZ278S2OKc/export?format=csv" | |
| response = requests.get(url, timeout=10) | |
| df = pd.read_csv(BytesIO(response.content)) | |
| df = df[["Driver", event]] | |
| # replace NaNs with 0s | |
| df = df.fillna(0) | |
| # convert numbers to ints | |
| df[event] = df[event].astype(int) | |
| # replace event with "overtakes" | |
| df = df.rename(columns={event: "overtakes"}) | |
| return df | |
| def get_overtaken_df(year, event): | |
| if year == 2023: | |
| url = "https://docs.google.com/spreadsheets/d/1wszzx694Ot-mvA5YrFCpy3or37xMgnC0XpE8uNnJLWk/export?format=csv" | |
| if year == 2022: | |
| url = "https://docs.google.com/spreadsheets/d/19_XFDD3BZDIQVkNE4bG6dwuKvMaO4g5HNaUARGaJwhE/export?format=csv" | |
| if year == 2021: | |
| url = "https://docs.google.com/spreadsheets/d/1dQBHnd3AXEPNH5I75cjbzAAzi9ipqGk3v9eZT9eYKS4/export?format=csv" | |
| if year == 2020: | |
| url = "https://docs.google.com/spreadsheets/d/1snyntPMxYH4_KHSRI96AwBoJQrPbX6OanJAcqbYyW-Y/export?format=csv" | |
| if year == 2019: | |
| url = "https://docs.google.com/spreadsheets/d/11FfFkXErJg7F22iVwJo9XfLFAWucMBVlzL1qUGWxM3s/export?format=csv" | |
| if year == 2018: | |
| url = "https://docs.google.com/spreadsheets/d/1XJXAEyRpRS_UwLHzEtN2PdIaFJYGWSN6ypYN8Ecwp9A/export?format=csv" | |
| response = requests.get(url, timeout=10) | |
| df = pd.read_csv(BytesIO(response.content)) | |
| df = df[["Driver", event]] | |
| # replace NaNs with 0s | |
| df = df.fillna(0) | |
| # convert numbers to ints | |
| df[event] = df[event].astype(int) | |
| df = df.rename(columns={event: "overtaken"}) | |
| return df | |
| overtakes = get_overtakes_df(year, event) | |
| overtaken = get_overtaken_df(year, event) | |
| df = overtakes.merge(overtaken, on="Driver") | |
| # remove drivers with 0 overtakes and 0 overtaken | |
| df = df[(df["overtakes"] != 0) | (df["overtaken"] != 0)] | |
| # sort in the decreasing order of overtakes | |
| df = df.sort_values( | |
| by=["overtakes", "overtaken"], ascending=[False, True] | |
| ).reset_index(drop=True) | |
| # convert to dictionary | |
| df_dict = df.to_dict(orient="records") | |
| return {"overtakes": df_dict} | |
| # Your list of events | |
| events_list = events | |
| # Loop through each event | |
| for event in events_list: | |
| session = "Race" | |
| overtakes_dict = get_overtakes(YEAR, event) | |
| # Specify the file path where you want to save the JSON data | |
| file_path = f"{event}/{session}/overtakes.json" | |
| # Save the dictionary to a JSON file | |
| with open(file_path, "w") as json_file: | |
| json.dump(overtakes_dict, json_file) | |
| print(f"Dictionary saved to {file_path}") | |
Xet Storage Details
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- 4.39 kB
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