2017-04-20 74 views
1

我試圖將幾個列重新格式化爲字符串(它們包含NaN,所以我不能只以整數讀取它們)。所有的列目前都是float64,我想這樣做,所以他們沒有小數。熊貓:列必須與密鑰長度相同

下面是數據:

{'crash_id': {0: 201226857.0, 
    1: 201226857.0, 
    2: 2012272611.0, 
    3: 2012272611.0, 
    4: 2012298998.0}, 
'driver_action1': {0: 1.0, 1: 1.0, 2: 29.0, 3: 1.0, 4: 3.0}, 
'driver_action2': {0: 99.0, 1: 99.0, 2: 1.0, 3: 99.0, 4: 99.0}, 
'driver_action3': {0: 99.0, 1: 99.0, 2: 99.0, 3: 99.0, 4: 99.0}, 
'driver_action4': {0: 99.0, 1: 99.0, 2: 99.0, 3: 99.0, 4: 99.0}, 
'harmful_event1': {0: 14.0, 1: 14.0, 2: 14.0, 3: 14.0, 4: 14.0}, 
'harmful_event2': {0: 99.0, 1: 99.0, 2: 99.0, 3: 99.0, 4: 99.0}, 
'harmful_event3': {0: 99.0, 1: 99.0, 2: 99.0, 3: 99.0, 4: 99.0}, 
'harmful_event4': {0: 99.0, 1: 99.0, 2: 99.0, 3: 99.0, 4: 99.0}, 
'most_damaged_area': {0: 14.0, 1: 2.0, 2: 14.0, 3: 14.0, 4: 3.0}, 
'most_harmful_event': {0: 14.0, 1: 14.0, 2: 14.0, 3: 14.0, 4: 14.0}, 
'point_of_impact': {0: 15.0, 1: 1.0, 2: 14.0, 3: 14.0, 4: 1.0}, 
'vehicle_id': {0: 20121.0, 1: 20122.0, 2: 20123.0, 3: 20124.0, 4: 20125.0}, 
'vehicle_maneuver': {0: 3.0, 1: 1.0, 2: 4.0, 3: 1.0, 4: 1.0}} 

當我嘗試那些列轉換爲字符串,這是發生了什麼:

>> df[['crash_id','vehicle_id','point_of_impact','most_damaged_area','most_harmful_event','vehicle_maneuver','harmful_event1','harmful_event2','harmful_event3','harmful_event4','driver_action1','driver_action2','driver_action3','driver_action4']] = df[['crash_id','vehicle_id','point_of_impact','most_damaged_area','most_harmful_event','vehicle_maneuver','harmful_event1','harmful_event2','harmful_event3','harmful_event4','driver_action1','driver_action2','driver_action3','driver_action4']].applymap(lambda x: '{:.0f}'.format(x)) 

File "C:\Users\<name>\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\core\frame.py", line 2376, in _setitem_array 
     raise ValueError('Columns must be same length as key') 

ValueError: Columns must be same length as key 

我從來沒有見過這個錯誤之前,感覺像這樣是簡單的...我做錯了什麼?

+1

,你可以使用'data.to_dict提供樣品()',使一些人可以嘗試輕鬆重現 – muon

+1

固定!謝謝,我不知道這是可能的! – ale19

回答

1

你的代碼爲你提供的字典爲我運行。嘗試創建一個函數來分別處理NaN情況;我認爲他們正在造成你的問題。

一些基本的東西象下面這樣:

def formatter(x): 
    if x == None: 
     return None 
    else: 
     return '{:.0f}'.format(x) 
相關問題