Dataframe get max() from multiple columns in a rolling window

EDIT 2:

Considier the question closed. After I gave the example in the first EDIT I have realised that I am senslessly looking through all of the columns looking for Highest value, since the High column will always have the highest value and the following code is sufficient:

_high[f'Highest {n1}'] = price_df['High'].rolling(n1).max()

I am trying to get max from multiple columns with this code:

_high[f'Highest {n1}'] = price_df[['Open', 'Close', 'High', 'Low']].rolling(n1).max()

, but I am getting this error:

  File "C:\Users\...\main.py", line 1282, in chop_zone
    _high[f'Highest {n1}'] = price_df[['Open', 'Close', 'High', 'Low']].rolling(n1).max()
  File "C:\Users\...\venv\lib\site-packages\pandas\core\frame.py", line 3968, in __setitem__
    self._set_item_frame_value(key, value)
  File "C:\Users\...\venv\lib\site-packages\pandas\core\frame.py", line 4098, in _set_item_frame_value
    raise ValueError("Columns must be same length as key")
ValueError: Columns must be same length as key

Process finished with exit code 1

And I don't know why, how can I fix this?

EDIT:

What I expect the output to be:

Lets say I have the following dataframe (it is price_df[['Open', 'Close', 'High', 'Low']].tail(10))

         Open     Close      High       Low
5168  14010.0  14016.00  14024.05  14005.50
5169  14016.0  14018.00  14018.50  14007.50
5170  14018.0  14015.50  14021.50  14012.50
5171  14015.5  14007.00  14018.00  14004.50
5172  14007.0  14013.00  14013.50  13999.50
5173  14013.0  14007.00  14013.50  14002.00
5174  14007.0  14009.60  14017.60  14003.55
5175  14009.6  14013.60  14015.00  14004.60
5176  14013.6  14020.00  14021.60  14009.00
5177  14020.0  14015.55  14022.60  14013.60

So I expect a single column with the maximum value from the rolling window of size n1 along all columns. For example if the rolling window would be 3 the first maximal value would be 14024.5 from column High across all columns from index 5168 to 5170, the next maximal value would be 14021.5 from the high column across from indices 5169 to 5171.

CodePudding user response：

you are trying to assign a rolling maximum of a dataframe to a new column in the same dataframe which is not allowed. You can try this:

rolling_max = price_df[['Open', 'Close', 'High', 'Low']].rolling(n1).max()
#_high[f'Highest {n1}'] = rolling_max
_high[f'Highest {n1}'] = rolling_max['Open']