A Python notebook to visaulize the price history of any Steem/Hive Engine token

history/marketHistorythis info).One feature that I haven't seen available at https://hive-engine.com or https://steem-engine.com is how to view historical market price charts for a token. Ironically, while working on this post, I started seeing the candlestick plots on Steem Engine. Nonetheless, the APIs have a endpoint that provides daily price summaries (thanks @dalz for

<p dir="auto">Since I often want to visualize historical price data, I created a <a href="https://colab.research.google.com/drive/1bFfEii5QAaJEaHLtBmJVq2ctpQJi2MOw?usp=sharing" target="_blank" rel="nofollow noreferrer noopener" title="This link will take you away from hive.blog" class="external_link"><strong>Python Jupyter notebook on Google Colab. The user can choose any token symbol, and the notebook does the rest. <p dir="auto"><img src="https://images.hive.blog/768x0/https://files.peakd.com/file/peakd-hive/dhimmel/LSccPCOX-image.png" alt="Notebook cell to create an interactive candlestick plot using plotly" srcset="https://images.hive.blog/768x0/https://files.peakd.com/file/peakd-hive/dhimmel/LSccPCOX-image.png 1x, https://images.hive.blog/1536x0/https://files.peakd.com/file/peakd-hive/dhimmel/LSccPCOX-image.png 2x" /> <p dir="auto">Since the figures are created using Plotly, they're interactive. For example, you can zoom in to reduce the y-axis to trading following the initial HIVEP volatility. <p dir="auto"><img src="https://images.hive.blog/768x0/https://files.peakd.com/file/peakd-hive/dhimmel/A9axU3jD-steem-hivep-history.png" alt="STEEM/HIVEP price history with rescaled axes" srcset="https://images.hive.blog/768x0/https://files.peakd.com/file/peakd-hive/dhimmel/A9axU3jD-steem-hivep-history.png 1x, https://images.hive.blog/1536x0/https://files.peakd.com/file/peakd-hive/dhimmel/A9axU3jD-steem-hivep-history.png 2x" /> <p dir="auto">We can also plot daily volume: <p dir="auto"><img src="https://images.hive.blog/768x0/https://files.peakd.com/file/peakd-hive/dhimmel/VmTe7BYe-steem-hivep-volume.png" srcset="https://images.hive.blog/768x0/https://files.peakd.com/file/peakd-hive/dhimmel/VmTe7BYe-steem-hivep-volume.png 1x, https://images.hive.blog/1536x0/https://files.peakd.com/file/peakd-hive/dhimmel/VmTe7BYe-steem-hivep-volume.png 2x" /> <p dir="auto">Looking forward to anyone building off this code and reusing the notebook, so I released it under the open CC BY License! <h2>Python code <p dir="auto">Programming in Python is lot's of fun, since you can accomplish a lot with little code. For example, here's a snippet of just the code to retrieve the market history data and transform it into a dataframe (tabular data structure) and convert the dates to a more human-friendly encoding. <pre><code>symbol = "HIVEP" url = "https://api.steem-engine.com/history/marketHistory" response = requests.get(url, params=dict(symbol=symbol)) response.raise_for_status() market_history_df = pandas.json_normalize(response.json()) market_history_df.timestamp = pandas.to_datetime(market_history_df.timestamp, unit="s")