Candlestick Chart in Python with mplfinance

Library

Author

Daniel Goldfarb

Candlestick charts represent the evolution of the price of an asset: each candle shows the opening, the highest, the lowest and the closing price of a period. The mplfinance library, built on matplotlib, creates them from a pandas data frame with a date index and the columns Open, High, Low, Close and, optionally, Volume.

Candlestick chart with `mpf.plot`

Pass the data frame to mpf.plot and set type = "candle".

import numpy as np
import pandas as pd
import mplfinance as mpf

rng = np.random.default_rng(21)
close = 50 + rng.normal(0, 1, 60).cumsum()
df = pd.DataFrame({"Open": close + rng.normal(0, 0.5, 60),
                   "Close": close,
                   "Volume": rng.integers(1000, 5000, 60)},
                  index = pd.bdate_range("2025-03-03", periods = 60))
df["High"] = df[["Open", "Close"]].max(axis = 1) + rng.uniform(0, 1, 60)
df["Low"] = df[["Open", "Close"]].min(axis = 1) - rng.uniform(0, 1, 60)

mpf.plot(df, type = "candle", figsize = (4, 4))

Candlestick chart in Python with mplfinance

OHLC bars and line

Other values of type are "ohlc" (bars with ticks for the opening and closing prices), "line" and "renko".

import numpy as np
import pandas as pd
import mplfinance as mpf

rng = np.random.default_rng(21)
close = 50 + rng.normal(0, 1, 60).cumsum()
df = pd.DataFrame({"Open": close + rng.normal(0, 0.5, 60),
                   "Close": close,
                   "Volume": rng.integers(1000, 5000, 60)},
                  index = pd.bdate_range("2025-03-03", periods = 60))
df["High"] = df[["Open", "Close"]].max(axis = 1) + rng.uniform(0, 1, 60)
df["Low"] = df[["Open", "Close"]].min(axis = 1) - rng.uniform(0, 1, 60)

mpf.plot(df, type = "ohlc", figsize = (4, 4))

OHLC chart in Python with mplfinance

Volume

Set volume = True to add a panel with the traded volume below the candles.

import numpy as np
import pandas as pd
import mplfinance as mpf

rng = np.random.default_rng(21)
close = 50 + rng.normal(0, 1, 60).cumsum()
df = pd.DataFrame({"Open": close + rng.normal(0, 0.5, 60),
                   "Close": close,
                   "Volume": rng.integers(1000, 5000, 60)},
                  index = pd.bdate_range("2025-03-03", periods = 60))
df["High"] = df[["Open", "Close"]].max(axis = 1) + rng.uniform(0, 1, 60)
df["Low"] = df[["Open", "Close"]].min(axis = 1) - rng.uniform(0, 1, 60)

mpf.plot(df, type = "candle", volume = True, figsize = (4, 4))

Candlestick chart with volume in mplfinance

Moving averages

The mav argument adds simple moving averages of the number of periods you specify. Pass a tuple to add several.

import numpy as np
import pandas as pd
import mplfinance as mpf

rng = np.random.default_rng(21)
close = 50 + rng.normal(0, 1, 60).cumsum()
df = pd.DataFrame({"Open": close + rng.normal(0, 0.5, 60),
                   "Close": close,
                   "Volume": rng.integers(1000, 5000, 60)},
                  index = pd.bdate_range("2025-03-03", periods = 60))
df["High"] = df[["Open", "Close"]].max(axis = 1) + rng.uniform(0, 1, 60)
df["Low"] = df[["Open", "Close"]].min(axis = 1) - rng.uniform(0, 1, 60)

mpf.plot(df, type = "candle", mav = (5, 20), volume = True,
         style = "yahoo", figsize = (4, 4))

Candlestick chart with moving averages in mplfinance

Styles and colors

mplfinance includes several styles, such as "yahoo", "charles", "nightclouds" or "binance" (see them all with mpf.available_styles()). To choose the colors of the candles create a style with make_marketcolors and make_mpf_style.

import numpy as np
import pandas as pd
import mplfinance as mpf

rng = np.random.default_rng(21)
close = 50 + rng.normal(0, 1, 60).cumsum()
df = pd.DataFrame({"Open": close + rng.normal(0, 0.5, 60),
                   "Close": close,
                   "Volume": rng.integers(1000, 5000, 60)},
                  index = pd.bdate_range("2025-03-03", periods = 60))
df["High"] = df[["Open", "Close"]].max(axis = 1) + rng.uniform(0, 1, 60)
df["Low"] = df[["Open", "Close"]].min(axis = 1) - rng.uniform(0, 1, 60)

colors = mpf.make_marketcolors(up = "#2A9D8F", down = "#E76F51", inherit = True)
style = mpf.make_mpf_style(marketcolors = colors, gridstyle = ":")

mpf.plot(df, type = "candle", style = style, figsize = (4, 4))

Custom candle colors in mplfinance

Title and labels

import numpy as np
import pandas as pd
import mplfinance as mpf

rng = np.random.default_rng(21)
close = 50 + rng.normal(0, 1, 60).cumsum()
df = pd.DataFrame({"Open": close + rng.normal(0, 0.5, 60),
                   "Close": close,
                   "Volume": rng.integers(1000, 5000, 60)},
                  index = pd.bdate_range("2025-03-03", periods = 60))
df["High"] = df[["Open", "Close"]].max(axis = 1) + rng.uniform(0, 1, 60)
df["Low"] = df[["Open", "Close"]].min(axis = 1) - rng.uniform(0, 1, 60)

mpf.plot(df, type = "candle", style = "nightclouds", figsize = (4, 4),
         title = "Stock price", ylabel = "Price ($)")

Candlestick chart with title in mplfinance