Pandas TA Classic

0.5.44 verified Fri May 01 auth: no python

A maintained fork of the popular pandas-ta library, providing an extensive collection of technical analysis indicators and TA-Lib patterns as Pandas DataFrame extensions. Current version is 0.5.44, with a monthly release cadence and active development.

pip install pandas-ta-classic

Common errors

error ModuleNotFoundError: No module named 'pandas_ta' ↓

cause Installed package as 'pandas-ta-classic' but imported as 'pandas_ta'? Or not installed.

fix

Run: pip install pandas-ta-classic, then import pandas_ta

error 'DataFrame' object has no attribute 'ta' ↓

cause pandas_ta not imported or imported incorrectly.

fix

Ensure 'import pandas_ta as ta' is executed before using df.ta.

error ValueError: length must be greater than 0 ↓

cause Incorrect parameters passed to indicator (e.g., length=0 or negative).

fix

Check indicator parameters; e.g., df.ta.sma(length=10) requires length >= 2.

Warnings

breaking pandas-ta-classic is a fork; breaking changes from original pandas-ta may exist. Always check migration guide. ↓

fix Review changelog at https://github.com/xgboosted/pandas-ta-classic/releases

deprecated TA-Lib pattern functions are deprecated in favor of native pandas-ta implementations. TA-Lib must be installed separately if needed. ↓

fix Use pandas-ta built-in patterns (e.g., df.ta.cdl_pattern(name='doji')) instead of TA-Lib.

gotcha Indicator methods may modify the DataFrame in-place even without append=True if the method is called with default kwargs. ↓

fix Always pass append=True explicitly to avoid silent column overwrites.

gotcha Some indicators require specific column names (open, high, low, close, volume). Missing columns raise KeyError. ↓

fix Rename columns to lowercase before using df.ta.

Imports

ta
wrong
```
import pandas-ta as ta
```
correct
```
import pandas_ta as ta
```
Hyphen in package name is invalid in Python; use underscore.
DataFrame.ta
wrong
```
df.ta.<indicator>(...) with old import style
```
correct
```
df.ta.<indicator>(...)
```
Extension is automatically available after importing pandas_ta.

Quickstart

Calculate a simple moving average (SMA) and append it to the DataFrame.

import pandas as pd
import pandas_ta as ta

df = pd.DataFrame({'close': [1.1, 1.2, 1.3, 1.4, 1.5]})
df.ta.sma(length=4, append=True)
print(df)