61 lines
1.9 KiB
Python
61 lines
1.9 KiB
Python
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#!/usr/bin/env python3
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import pandas as pd
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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from datetime import timedelta, datetime
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# this script loads data from a csv file
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# with headers id, created_at, time, title, url, author, ndescendants, score, rank
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# and then saves a plot with score, ndescendants and rank for each id
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# load data from csv file
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df = pd.read_csv('hacker_news.csv', index_col='created_at')
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# group pandas dataframe by id
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grouped = df.groupby(['id'])
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# create one chart per id and plot score, ndescendants and rank in each chart
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for [hn_id], group in grouped:
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# sort group by created_at ascending
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group = group.sort_values(by='created_at', ascending=True)
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# this is the time when the item was created on HN
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item_created_at = datetime.utcfromtimestamp(group['time'].values[0])
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# use relative time for x axis
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def date_to_relative(d1):
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date_fmt = '%Y-%m-%d %H:%M:%S'
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current = datetime.strptime(d1, date_fmt)
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return (current - item_created_at) / timedelta(hours=1)
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group.index = group.index.map(date_to_relative)
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# title generation
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hn_item_title = group['title'].values[0]
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hn_item_url = group['url'].values[0]
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hn_item_link = f'https://news.ycombinator.com/item?id={hn_id}'
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plot_title = f'{hn_item_title}\n{hn_item_url}\n{hn_item_link}'
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fig, ax1 = plt.subplots(figsize=(10, 5))
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ax1.set_title(plot_title)
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ax1.set_xlabel('hours')
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ax1.set_ylabel('score, comments')
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ax1.plot(group['score'], label='score', color='blue')
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ax1.plot(group['ndescendants'], label='comments', color='orange')
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ax1.legend()
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# show every 50th date
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# TODO: do something more clever here
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plt.xticks(group.index[::50], rotation=45)
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ax2 = ax1.twinx()
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ax2.set_ylabel('rank')
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ax2.set_ylim(1, 30)
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ax2.plot(group['rank'], label='rank', color='green')
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ax2.legend(loc='upper right')
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plt.tight_layout()
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plt.savefig(f'hn_{hn_id}.png')
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