📘 Article 6: Freqtrade - "Visualize Your Data with Charts! Plot-Dataframe Visualization Tutorial"

During strategy development, backtest results are often presented in tabular form, making it hard to quickly identify issues. The plot-dataframe command visualizes buy/sell points, indicator lines, and price trends as charts, helping you instantly understand strategy performance.

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🎯 1. Basic Usage: Generating Charts

freqtrade plot-dataframe \
  --config user_data/config.json \
  --strategy MyStrategy \
  --timerange 20230101-20230201

This command generates an .html file in the user_data/plot/ directory, which you can open in a browser to view:

• Candlestick price trends
• Buy/Sell points (marked with arrows)
• Technical indicators (e.g., EMA, MACD)

🧾 2. Parameter Breakdown

Parameter	Description
--config	Path to the configuration file (includes trading pairs, timeframes, etc.)
--strategy	Strategy class name (e.g., MyStrategy)
--timerange	Time range for the chart (e.g., 20230101-20230201)
--indicators1	Indicators for the main chart (e.g., EMA, close)
--indicators2	Indicators for the subplot (e.g., RSI, MACD)
--exportfilename	Output file path (supports .html or .png)
--userdir	Custom user_data directory (default is fine)

📐 3. Adding Custom Indicators

You can include additional indicators in the chart to validate signal logic:

Code Example:

def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
    dataframe['ema'] = ta.EMA(dataframe['close'], timeperiod=20)
    dataframe['fast_ema'] = ta.EMA(dataframe['close'], timeperiod=10)
    dataframe['slow_ema'] = ta.EMA(dataframe['close'], timeperiod=50)
    dataframe['rsi'] = ta.RSI(dataframe['close'], timeperiod=14)
    macd, macdsignal, macdhist = ta.MACD(dataframe['close'])
    dataframe['macd'] = macd
    return dataframe

• --indicators1 plots on the main chart (price chart), e.g., EMA lines.
• --indicators2 plots on the subplot, e.g., RSI, MACD.

Complete Example:

freqtrade plot-dataframe \
  --config user_data/config.json \
  --strategy MyStrategy \
  --timerange 20230101-20230201 \
  --indicators1 close ema fast_ema slow_ema \
  --indicators2 rsi macd

❗ Note:

• Indicator names must match the column names in the DataFrame created in the populate_indicators() method of your strategy.
• Mismatched names won’t cause errors, but the indicators won’t appear on the chart.
• Indicators must be defined in populate_indicators() to take effect.

💾 4. Exporting to HTML / PNG

By default, the output is an HTML file. To specify:

--exportfilename user_data/plot/myplot.html

To export as PNG (static image):

--exportfilename user_data/plot/myplot.png

📌 Note: Exporting to PNG requires additional tools like Puppeteer or headless Chrome. Beginners should stick to HTML format.

🐳 5. Running in a Docker Environment

To use the command in Docker:

docker compose run --rm freqtrade plot-dataframe \
  --config /quants/freqtrade/user_data/config.json \
  --strategy MyStrategy \
  --timerange 20230101-20230201

Ensure the /quants/freqtrade/user_data directory is correctly mounted in docker-compose.yml.

✅ 6. Usage Tips

Purpose	Method
Verify strategy logic	Check if buy/sell points are correctly positioned
Debugging	Compare indicators with signal logic
Strategy sharing	Export charts as HTML for easy presentation
Evaluate indicator performance	Plot multiple indicators to check for redundancy

📌 Summary

plot-dataframe is a powerful visualization tool in Freqtrade, ideal for debugging complex strategies and validating buy/sell logic.

Recommended Workflow:

1. Run Backtest:

freqtrade backtesting \
  --config user_data/config.json \
  --strategy MyStrategy \
  --timeframe 15m \
  --timerange 20220101-20230101

1. Generate Chart:

freqtrade plot-dataframe \
  --config user_data/config.json \
  --strategy MyStrategy \
  --timerange 20250601-20250626

1. Analyze Chart:
2. Are buy signals triggered too early or too late?
3. Are there frequent false signals?
4. Are the indicators effective?

Master plot-dataframe to optimize strategies efficiently with data-driven insights!