為幾個 excel 表運行此腳本（FOR 循環功能）

Question

所以我想為幾個excel文件運行這個腳本，所以我將導入幾個excel文件而不是df3，並將所有結果合並到一個dataframe中。

這是主要的代碼示例

import pandas as pd

d = {'City': ['Tokyo','Tokyo','Lisbon','Tokyo','Tokyo','Lisbon','Lisbon','Lisbon','Tokyo','Lisbon','Tokyo','Tokyo','Tokyo','Lisbon','Tokyo','Tokyo','Lisbon','Lisbon','Lisbon','Tokyo','Lisbon','Tokyo'], 
     'Card': ['Visa','Visa','Master Card','Master Card','Visa','Master Card','Visa','Visa','Master Card','Visa','Master Card','Visa','Visa','Master Card','Master Card','Visa','Master Card','Visa','Visa','Master Card','Visa','Master Card'],
     'Colateral':['Yes','No','Yes','No','No','No','No','Yes','Yes','No','Yes','Yes','No','Yes','No','No','No','Yes','Yes','No','No','No'],
     'Client Number':[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22],
     'DebtPaid':[0.8,0.1,0.5,0.30,0,0.2,0.4,1,0.60,1,0.5,0.2,0,0.3,0,0,0.2,0,0.1,0.70,0.5,0.1]}

df = pd.DataFrame(data=d)

df2=df.groupby(['City','Card','Colateral'])['DebtPaid'].\
           value_counts(bins=[-0.001,0,0.25,0.5,0.75,1,1.001,2],normalize=True)

d = {'City': ['Tokyo','Tokyo','Lisbon','Tokyo','Tokyo','Lisbon','Lisbon','Lisbon','Tokyo','Lisbon','Tokyo','Tokyo','Tokyo','Lisbon','Tokyo','Tokyo','Lisbon','Lisbon','Lisbon','Tokyo','Lisbon','Tokyo'], 
     'Card': ['Visa','Visa','Master Card','Master Card','Visa','Master Card','Visa','Visa','Master Card','Visa','Master Card','Visa','Visa','Master Card','Master Card','Visa','Master Card','Visa','Visa','Master Card','Visa','Master Card'],
     'Colateral':['Yes','No','Yes','No','No','No','No','Yes','Yes','No','Yes','Yes','No','Yes','No','No','No','Yes','Yes','No','No','No'],
     'Client Number':[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44],
     'Total Debt':[100,240,200,1000,50,20,345,10,600,40,50,20,100,30,100,600,200,200,150,700,50,120]}

df3 = pd.DataFrame(data=d)

#First merge dataframes
df_out = df2.rename('Prob').reset_index().merge(df3, on=['City', 'Card', 'Colateral'])

#Use the right and left attributes of pd.Interval
df_out['lower'] = [x.left for x in df_out['DebtPaid']]
df_out['upper'] = [x.right for x in df_out['DebtPaid']]

#Calculate lower and upper partial prices
df_out['l_partial'] = df_out[['lower', 'Prob', 'Total Debt']].prod(axis=1)
df_out['u_partial'] = df_out[['upper', 'Prob', 'Total Debt']].prod(axis=1)

#Sum partial prices to get lower and upper price grouped on Client Number
final = df_out.groupby('Client Number')[['l_partial', 'u_partial']]\
      .agg(lower_price=('l_partial', 'sum'),
           upper_price=('u_partial', 'sum')).clip(0,np.inf)



w = (final['upper_price'].sum() + final['lower_price'].sum()) / 2 
y = 1000
z = ((w/y)-1)*100

d1 = {'1': [w,y,z],
     'Index':['Estimate','Real','Error']}
     
results = pd.DataFrame(data=d1).set_index('Index')
results

問題是這個腳本只運行一個 dataframe。

這是我試圖用幾個 excel 文件運行腳本但沒有成功：

files = [1,2,3,4,5]

for x in files:
    df3 = pd.read_excel(str(x) + '.xlsx')

#First merge dataframes
    df_out = df2.rename('Prob').reset_index().merge(df3, on=['City', 'Card', 'Colateral'])

#Use the right and left attributes of pd.Interval
    df_out['lower'] = [x.left for x in df_out['DebtPaid']]
    df_out['upper'] = [x.right for x in df_out['DebtPaid']]

#Calculate lower and upper partial prices
    df_out['l_partial'] = df_out[['lower', 'Prob', 'Total Debt']].prod(axis=1)
    df_out['u_partial'] = df_out[['upper', 'Prob', 'Total Debt']].prod(axis=1)

#Sum partial prices to get lower and upper price grouped on Client Number
    final = df_out.groupby('Client Number')[['l_partial', 'u_partial']]\
      .agg(lower_price=('l_partial', 'sum'),
           upper_price=('u_partial', 'sum')).clip(0,np.inf)


    w = (final['upper_price'].sum() + final['lower_price'].sum()) / 2 
    y = 1000
    z = ((w/y)-1)*100

    d1 = {x : [w,y,z],
     'Index':['Estimate','Real','Error']}
     
    results = pd.DataFrame(data=d1).set_index('Index')

results

它僅顯示一個 excel 文件的結果。 你知道我怎么能解決這個問題嗎？

Answer 1

不確定您是否正在尋找這個

files = [1,2,3,4,5]
df = pd.concat([pd.read_excel(str(file) + '.xlsx') for file in files])

或類似的地方

df = pd.concat([function_returning_df(file) for file in files])