Python使用熊貓和str.strip崩潰

Question

這個最小的代碼崩潰了我的Python。 （環境：熊貓0.13.0，蟒2.7.3 AMD64，Win7的。）

import pandas as pd 
input_file = r"c3.csv" 
input_df = pd.read_csv(input_file) 
for col in input_df.columns: # strip whitespaces from string values 
    if input_df[col].dtype == object: 
     input_df[col] = input_df[col].apply(lambda x: x.strip()) 
print 'start' 
for idx in range(len(input_df)): 
    input_df['LL'].iloc[idx] = 3 
    print idx 
print 'finished' 

輸出：

start 
0 

Process finished with exit code -1073741819 

什麼防止碰撞：

1. 卸下從c3.csv線。
2. 從代碼中刪除.strip()。
3. 更改c3.csv更改for迭代的數量，直到意外崩潰。

內容c3.csv的：

Size , B/S , Symbol , Type , BN , Duration , VR , Time , SR ,LL, 
0, xxxx , xxxx0 , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
00, xxxx , xxxxx , ,, xxx , 00000 , 00:00:00 , 000000000 , 00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 
0, xxxx , xxxxx , ,, xxx , 00000 , 00-00:00:00 , 000000000 , 00-00:00:00 , 

Answer 1

你正在做一個鏈接分配可以以意想不到的方式表現。請看這裏：http://pandas.pydata.org/pandas-docs/dev/indexing.html#indexing-view-versus-copy。這是固定在主，並將工作在0.13.1（即將推出）。在這裏看到：https://github.com/pydata/pandas/pull/6031

這是不正確的事：

input_df['LL'].iloc[idx] = 3 

而是做：

input_df.ix[ix,'LL'] = 3 

更好

甚至（因爲你是指派所有行3）

input_df['LL'] = 3 

如果你正在分配一些行（並且說有一個整數/布爾型索引器）

input_df.ix[indexer,'LL'] = 3 

你也應該只是這樣做剝奪了空白：

input_df[col] = input_df[col].str.strip()