) result_lm['department']=result.index[i] #將部門名稱添加到數(shù)據(jù)框中 frames.append(result_lm) return pd.concat(frames)

調(diào)用上述函數(shù)得到每個部門下影響最大的類目：

final=max_lm(result,df)

如果我們想把結(jié)果導出到excel表中，可以這樣寫：

writer=pd.ExcelWriter('output_today.xlsx')result.to_excel(writer, sheet_name='max_departments')final.to_excel(writer, sheet_name='max_itemcats')writer.save()

總結(jié)

1. 準備好python開發(fā)環(huán)境，即 “代碼編輯器＋ipython”；

2. 寫代碼前清晰定義實現(xiàn)最終目標的每個步驟；

3. 寫代碼的過程中識別做事的模式，創(chuàng)造工具簡化復(fù)用性操作；

4. 利用for循環(huán)遍歷列表。

最終代碼

 

import pandas as pd import datetimetoday="%s"%(datetime.date.today())yesterday="%s"%(datetime.date.today()-datetime.timedelta(days=1))qiantian="%s"%(datetime.date.today()-datetime.timedelta(days=2))print("昨天和前天的日期分別是：")print(yesterday,qiantian)df=pd.read_excel('/Users/xiangzhendong/Downloads/income_data.xls')def max_change(df, rows):    df_pivot=df.pivot_table('income',index=rows,columns='date',aggfunc='sum')    df_pivot['change_amt']=df_pivot[yesterday]-df_pivot[qiantian]    df_pivot['change_pct']=abs(df_pivot['change_amt']/df_pivot['change_amt'].sum())    return df_pivot[df_pivot['change_pct']>=0.1]result=max_change(df,'department')print(result)def max_lm(result,df):    frames=[]    for i in range(len(result)):        result_lm=max_change(df[df['department']==result.index[i]],'itemcats')        result_lm['department']=result.index[i]

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