Pandas operation, putting multiple results into a df column - python-3.x

Question

This is a quant work. I used my previous work to filter out some desired stocks(candidates) with technical analysis based on moving average, MACD, KDJ, and etc. And now I wanna check my candidates' fundamental values, in this case, ROE. here is my code:
root_path = '.\\__fundamentals__'
df = pd.DataFrame(pd.read_csv("C:\\candidates.csv", encoding='GBK')) # 14 candidates this time
for code in list(df['code']):
i = str(code).zfill(6)
for root, dirs, files in os.walk(root_path):
for csv in files:
if csv.startswith('{}.csv'.format(i)):
csv_path = os.path.join(root, csv) # based on candidates looking for dupont value
df1 = pd.DataFrame(pd.read_csv("{}".format(csv_path), encoding='GBK'))
df2['ROE'] = df2['净资产收益率'].str.strip("%").astype(float)/100
ROE = [df2['ROE'].mean().round(decimals=3)]
df3 = pd.DataFrame({'ROE_Mean': ROE})
print(df3)
Here is the DOM
C:\Users\Mike_Leigh\.conda\envs\LEIGH\python.exe "P:/LEIGH PYTHON/Codes/Quant/analyze_stock.py"
ROE_Mean
0 -0.218
ROE_Mean
0 0.121
ROE_Mean
0 0.043
ROE_Mean
0 0.197
ROE_Mean
0 0.095
ROE_Mean
0 0.085
...
ROE_Mean
0 0.178
Process finished with exit code 0
my desired output would be like this:
ROE_Mean
0 -0.218
1 0.121
2 0.043
3 0.197
4 0.095
5 0.085
...
14 0.178
Would you please give me a hint on this? Thanks alot, much appreciated!

Answer 1

acually I wasn't that bad solving the issue.
first, make a list outside the loop, I mean the very outside the loop, in this case, before df
roe_avg = []
df = pd.DataFrame(pd.read_csv("C:\\candidates.csv", encoding='GBK'))
....
df2['ROE'] = df2['净资产收益率'].str.strip("%").astype(float) / 100
ROE_avg = df2['ROE'].mean().round(decimals=3)
roe_avg.append(ROE_avg)
df['ROE_avg'] = roe_avg
print(df)
DOM
name code ROE_avg
1 仙鹤股份 603733 0.121
3 泸州老窖 568 0.197
4 兴蓉环境 598 0.095
...
15 濮阳惠成 300481 0.148
16 中科创达 300496 0.101
17 森霸传感 300701 0.178
Process finished with exit code 0
thanks to #filippo