podcast_statistics.py

import pandas as pd
from tqdm import tqdm
import math

## Function to convert duration to seconds
def uniform_duration(duration):
    try:
        if isinstance(duration, float) or (":" not in duration and '"' not in duration and "'" not in duration):
                return int(duration)
        else:
            parts = duration.split(":")
            if len(parts) == 1:
                parts = parts[0].split("'")
                if len(parts) == 1:
                    return int(parts[0])
                elif len(parts) == 2:
                    if parts[1] == '':
                        parts[1] = '0"'
                    return int(parts[0])*60 + int(parts[1][:-1])
            elif len(parts) == 2:
                minutes, seconds = parts
                return int(minutes)*60 + int(seconds)
            elif len(parts) == 3:
                hours, minutes, seconds = parts
                return int(hours)*3600 + int(minutes)*60 + int(seconds)
    except Exception as e:
        print(e)
        return 0

if __name__ == "__main__":

    ## Read data
    df = pd.read_csv('data/news_episodes.csv')
    print(df.columns)

    ## Convert duration to seconds by using uniform_duration function
    ud = []
    for i, d in enumerate(tqdm(list(df.episode_duration))):
        ud.append(uniform_duration(d))
    df["uniform_duration"] = ud

    ## Sum uniform duration group by podcast_name
    print("grouping...")
    groups = df.groupby("podcast_name")
    for i, tuple in enumerate(groups):
        name, group = tuple
        print(i, " - ", name, " - ", group.uniform_duration.sum()/3600)