pandas-ta with multiindex dataframe

I am wanting to use pandas-ta. Although most aspects of this library seem easier for technical analysis I can only make it function on single ticker dataframes.

I would like to figure out how to get pandas-ta to work over multiple tickers in a multiindex dataframe.

I get the data using: - where [stocks] come from a csv list.

df = yf.download[stocks], '2021-1-1', interval='1d')

the pandas-ta download method below only creates a single ticker dataframe and only iterates the first ticker when using [stocks].

df.ta.ticker('GOOG', period = '1y', interval = "1h")

My current dataframe appears something like below. (where the list of tickers will change)

    Adj Close   Close   High    Low Open    Volume
BTC-USD ETH-USD BTC-USD ETH-USD BTC-USD ETH-USD BTC-USD ETH-USD BTC-USD ETH-USD BTC-USD ETH-USD
Date                                                
2020-12-31  29001.720703    737.803406  29001.720703    737.803406  29244.876953    754.299438  28201.992188    726.511902  28841.574219    751.626648  46754964848 13926846861
2021-01-01  29374.152344    730.367554  29374.152344    730.367554  29600.626953    749.201843  28803.585938    719.792236  28994.009766    737.708374  40730301359 13652004358
2021-01-02  32127.267578    774.534973  32127.267578    774.534973  33155.117188    786.798462  29091.181641    718.109497  29376.455078    730.402649  67865420765 19740771179
2021-01-03  32782.023438    975.507690  32782.023438    975.507690  34608.558594    1006.565002 32052.316406    771.561646  32129.408203    774.511841  78665235202 45200463368
2021-01-04  31971.914062    1040.233032 31971.914062    1040.233032 33440.218750    1153.189209 28722.755859    912.305359  32810.949219    977.058838  81163475344 56945985763

When I try to apply a pandas-ta function such as:

df[stocks] = data[stocks].ta.sma(length=10)

I get the error. AttributeError: 'Series' object has no attribute 'ta'

When I use the documentation standard method

sma10 = ta.sma(df["Close"], length=10)

I don't know how to target the specific (BTC-USD)'Close' columns for all tickers in the .csv list - ie. (df['Close']

In both examples pandas-ta sma is using the 'close' value but I'm hoping to be able to apply all pandas-ta methods to a multiindex.

I can download 'Close' only data -

data = yf.download[stocks], '2021-1-1', interval='1d')['Close']

however the columns will be the 'ticker names' containing 'Close' data and I still have the same issue with pandas-ta trying to find the 'close' column data.

I don't know how to make pandas-ta function over multiple tickers in the same dataframe. Is there a solution to this?

Thanks for any help!

Since each column of multi-column consists of a tuple, it is possible to deal with data frames in horizontal format by specifying them in tuple format using .loc, etc. Two types of technical analysis are added by loop processing. The last step is to reorder the columns. If you need to handle more than just the closing price, you can use the closing price as the target of the loop.

import pandas as pd
import pandas_ta as ta
import yfinance as yf

stocks = 'BTC-USD ETH-USD XRP-USD XEM-USD'

df = yf.download(stocks, '2021-1-1', interval='1d',)

technicals = ['sma10', 'sma25', 'vwma']
tickers = stocks.split(' ')

for ticker in tickers:
  for t in technicals:
    if t[:2] == 'sma':
      l = int(t[3:])
      df[(t, ticker)] = ta.sma(df.loc[:,('Close', ticker)], length=l)
    else:
      df[(t, ticker)] = ta.vwma(df.loc[:,('Close', ticker)], df.loc[:,('Volume', ticker)])