'Creating a Dictionary and then a dataframe from different Types

I'm having a problem manipulating different types. Here is what I'm doing:

   row_list=[]
     for x in a:
        df=selectinfo(x)
        analysis=df[['Sales']].copy()
        
        decompose_result_mult = seasonal_decompose(analysis, model="additive")

        date = decompose_result_mult.trend.to_frame()
        date.reset_index(inplace=True)
        date=date.iloc[:,0]
        
        trend = decompose_result_mult.trend
        trend = decompose_result_mult.trend.to_frame()
        trend.reset_index(inplace=True)
        trend=trend.iloc[:,1]

        seasonal = decompose_result_mult.seasonal
        seasonal = decompose_result_mult.seasonal.to_frame()
        seasonal.reset_index(inplace=True)
        seasonal=seasonal.iloc[:,1]

        residual = decompose_result_mult.resid
        residual = decompose_result_mult.resid.to_frame()
        residual.reset_index(inplace=True)
        residual=residual.iloc[:,1]

        observed=decompose_result_mult.observed
        observed=decompose_result_mult.observed.to_frame()
        observed.reset_index(inplace=True)
        observed=observed.iloc[:,1]

        dict= {'Date':date,'region':x,'Trend':trend,'Seasonal':seasonal,'Residual':residual,'Sales':observed}

        row_list.append(dict)

  pandasTable=pd.DataFrame(row_list)

The problem with this is that when I run my code I get the next result:

Output

It is a dataframe that have inside Series... Any help? I would like to have 1 value per row and not 1 list per row.

Thank you!

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'Creating a Dictionary and then a dataframe from different Types

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