Pandas Keyerror after extracting the file(.csv format) using get_dummies
#### A small, complete example of the issue

import numpy as np
import pandas as pd
import timeit
from   sklearn import preprocessing
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from sklearn.ensemble import RandomForestClassifier
from sklearn.cross_validation import train_test_split
from sklearn.metrics import accuracy_score
from sklearn.metrics import classification_report,roc_auc_score
from sklearn.externals import joblib
from sklearn.metrics import (precision_score, recall_score,f1_score)
from sklearn.metrics import confusion_matrix
import os
import psutil
from sklearn.preprocessing import Imputer



 
start_time = timeit.default_timer()
np.set_printoptions(suppress=True)

df=pd.read_csv('/Users/sudarshan/Desktop/masterproject/SampleDatasets/dataset.csv')
print (df.isnull().any())
df.dropna(inplace=True)
print (df.isnull().any())

#df['flag'] = df['A'].str.extract('([A])', expand=True)
just_dummies = pd.Series(df['flags'])
values = just_dummies.str.get_dummies(sep='|')

#s = df['flags'].apply(pd.Series)

#dfMod= pd.concat([df,pd.DataFrame(s.values.tolist())], axis=1)


dfMod = pd.concat([df, values], axis=1) 

print dfMod.head()
print(dfMod.columns.tolist())

dfMod['A'] = dfMod['A'].astype(float)
dfMod['F'] = dfMod['F'].astype(float)
dfMod['P'] = dfMod['P'].astype(float)
dfMod['R'] = dfMod['R'].astype(float)
dfMod['S'] = dfMod['S'].astype(float)

print(dfMod.columns.tolist())
X = df.as_matrix(columns=['packets','bytes','duration','A','F','P','R','S'])

#### Expected Output

output should be if the flag is having a value of FPA it should be processed as separate,like 
'F','P','A'

#### Output of ``pd.show_versions()``

<details>
# Paste the output here pd.show_versions() here

</details>
