根據熊貓數據幀的行數動態添加字典值

Question

我正在重寫我的一些代碼，並覺得必須有更好的更動態的方式來執行下面的操作。目前正如您所看到的，我正在根據行數創建條件並從中添加值。不過，我不想爲多個值製作靜態條件if row_count == 3:if row_count == 4:等等。我認爲肯定有更高效的方法來實現這一點。任何指針將不勝感激。

for root, dirs, files in os.walk(main): 
    filters = '*specificname*.csv' 
    for filename in fnmatch.filter(files, filters): 
     df = pd.read_csv(os.path.join(root, filename),error_bad_lines=False) 
     row_count = len(df.index) 
     device_dic = collections.defaultdict() 
     if row_count == 2: 
      device_dic[df.iloc[0][1]] = {} 
      device_dic[df.iloc[0][1]]['item1'] = df.iloc[0][2] 
      device_dic[df.iloc[0][1]]['item2'] = df.iloc[0][3] 
      device_dic[df.iloc[1][1]] = {} 
      device_dic[df.iloc[1][1]]['item1'] = df.iloc[1][2] 
      device_dic[df.iloc[1][1]]['item2'] = df.iloc[1][3] 
      for key in device_dic.iterkeys(): 
       device.append(key) 

Answer 1

def func1(device_dict): 

    device_dic[df.iloc[0][1]] = {} 
    device_dic[df.iloc[0][1]]['item1'] = df.iloc[0][2] 
    device_dic[df.iloc[0][1]]['item2'] = df.iloc[0][3] 
    device_dic[df.iloc[1][1]] = {} 
    device_dic[df.iloc[1][1]]['item1'] = df.iloc[1][2] 
    device_dic[df.iloc[1][1]]['item2'] = df.iloc[1][3] 
    for key in device_dic.iterkeys(): 
     device.append(key) 

    # Or whatever you want to return 
    return device 

def func2(device_dict): 
    # your code here 
    pass 



# Store each function in a dict 
process_map = {2 : func1, 3: func2, 4: func2, ...} 


for root, dirs, files in os.walk(main): 
    filters = '*specificname*.csv' 
    for filename in fnmatch.filter(files, filters): 
     df = pd.read_csv(os.path.join(root, filename),error_bad_lines=False) 
     row_count = len(df.index) 
     device_dic = collections.defaultdict() 

     # Could also use get() to provide a default processing func 
     process_func = process_map[row_count] 

     result = process_func(device_dict)