Principle:TA Lib Ta lib python Price Data Preparation
| Knowledge Sources | |
|---|---|
| Domains | Data_Preparation, Technical_Analysis |
| Last Updated | 2026-02-09 22:00 GMT |
Overview
A data preparation pattern that ensures price data is in the correct format (float64 numpy arrays) for technical analysis indicator computation.
Description
Technical analysis indicators operate on numerical time series data, typically OHLCV (Open, High, Low, Close, Volume) price data. The TA-Lib library requires input data as numpy float64 arrays. This principle covers the conversion of various input formats (raw Python lists, pandas Series, polars Series) into the required numpy array format.
The key constraint is that all input arrays must be of dtype float64. Integer arrays will raise exceptions. The library provides transparent conversion for pandas and polars types through its _wrapper decorator pattern, but the underlying C functions always operate on float64 arrays.
Usage
Apply this principle whenever preparing price data for any TA-Lib indicator computation. This is the mandatory first step in all TA-Lib workflows. The data must be:
- Numeric (float64 dtype)
- Contiguous numpy arrays
- Of sufficient length for the desired indicator's lookback period
Theoretical Basis
Price data preparation involves type coercion and validation:
- Type conversion: pandas Series and polars Series are converted to numpy via .to_numpy().astype(float)
- Index preservation: For pandas inputs, the original index is captured before conversion and reattached to the output
- Validation: Input arrays must contain float64 values; integer dtypes are rejected by the C layer
- Length requirement: Arrays must have at least lookback + 1 elements for meaningful output
Pseudo-code:
# Abstract data preparation algorithm
if input is pandas.Series:
save index for output reconstruction
data = input.to_numpy().astype(float)
elif input is polars.Series:
data = input.to_numpy().astype(float)
else:
data = numpy.array(input, dtype=float)
# data is now ready for indicator functions