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Historical data

Plot a candlestick chart

Overview

In this example we will use the Historical client to retrieve AAPL pre-market one-minute OHLCV bars and plot a candlestick chart. A candlestick chart graphs the opening, high, low, and closing price at regular intervals. This is a common method for graphing price movements.

OHLCV-1m schema

We'll demonstrate this example using the OHLCV-1m schema. The OHLCV family of schemas contain the opening, high, low and closing prices as well as the aggregated volume of trades within a time interval. We'll use an interval of one minute, a typical charting frequency, which is specified by the suffix -1m.

Dependencies

This example will use the mplfinance package to plot a candlestick chart. This dependency can be installed with the following:

Python
$ pip install mplfinance

Example

Python
import databento as db
import mplfinance as mpf

# First, create a historical client
client = db.Historical(key="$YOUR_API_KEY")

# Next, we will request OHLCV-1m data for AAPL pre-market
data = client.timeseries.get_range(
    dataset="XNAS.ITCH",
    schema="ohlcv-1m",
    symbols=["AAPL"],
    start="2023-08-28T08:00:00-4",
    end="2023-08-28T09:30:00-4",
)

# Then, convert to a pandas DataFrame
df = data.to_df()

# Convert the index to the US/Eastern timezone
df.index = df.index.tz_convert("US/Eastern")

# Finally, plot the candlestick chart
mpf.plot(
    df,
    type="candle",
    volume=True,
    title="Nasdaq TotalView AAPL pre-market",
    ylabel="OHLCV-1M Candles",
    ylabel_lower="Volume",
    xlabel="Time",
)

Result

AAPL pre-market candlestick

Python C++ Rust HTTP/Raw