Changing rows within MultiIndex, DataFrame within a for loop

Question

I am currently trying to iterate through a dataframe containing MultIndex and calculate a signal that will make the SIGNAL column either 1.0, -1.0 or stay at 0.

Below is an example of how the DataFrame looks. | | | | AAPL| | | | AMZN| |:-|:-------:| :--------:| :----------: |:-:|:-------:| :-----------:|---------: | | SIGNAL| close | BB_LOWER | BB_UPPER | SIGNAL | close | BB_LOWER | BB_UPPER | | | | | | | | | | |0 | 123 | 123 | 123 | 0|123 | 123 | 123 | | 0| 123 | 123 | 123 | 0|123 | 123 | 123 |

This is the code I have been trying to tinker with and create so the output is accurate.

for x in ticker_list:
    for index, row in df[x].iterrows():
        if row['close'] < row['BB_LOWER']:
            df[x, 'SIGNAL'].loc[index] = 1.0
        if row['close'] > row['BB_UPPER']:
            df[x, 'SIGNAL'].loc[index] = -1.0
 df.sort_index(axis=1)

I understand the problem is coming from these sections but I have been unable to come to a solution.

df[x, 'SIGNAL'].loc[index] = 1.0

and

df[x, 'SIGNAL'].loc[index] = -1.0

My output is, every row in the SIGNAL column is changing to -1.0

			AAPL				AMZN
SIGNAL	close	BB_LOWER	BB_UPPER	SIGNAL	close	BB_LOWER	BB_UPPER

-1	123	123	123	-1	123	123	123
-1	123	123	123	-1	123	123	123

Ideally I would like to keep this DataFrame in MultiIndex form. Any help would be greatly appreciated!

For some reason my first table is not formatting correctly. It is basically the same as the second table except the SIGNAL columns contain only 0's — TRU_K, Jul 07 '22 at 12:23
Does this answer your question? [Numpy "where" with multiple conditions](https://stackoverflow.com/questions/39109045/numpy-where-with-multiple-conditions) — Paul Brennan, Jul 07 '22 at 12:38

Changing rows within MultiIndex, DataFrame within a for loop

0 Answers0