Pandas Unsuccessfully Modify - 


df=pd.read_csv('./data/reward_original_91011.csv')  ind0=df[df['datepay'].isnull()].index  df.ix[ind0]['valuepay']=0  ind1=df[~df['datepay'].isnull()].index  df['datepay'] = pd.to_datetime(df['datepay'])  df['datedue'] = pd.to_datetime(df['datedue'])  ind2=df.ix[ind1][((df.ix[ind1]['datepay']-df.ix[ind1]['datedue'])/np.timedelta64(1,'h')).astype(int)>24].index  **df.ix[ind2]['valuepay']=0**

is there can give me tips? why can modify above bold code successfully?

i think need:

df = pd.read_csv('./data/reward_original_91011.csv', parse_dates=['datepay','datedue'])  #get boolean mask nan mask = df['datepay'].isnull()  #modify column valuepay mask df.loc[mask, 'valuepay'] = 0  #get mask  mask1 = ((df['datepay'] - df['datedue']) / np.timedelta64(1,'h')) > 24  #inverted mask , mask1 -> modify valuepay df.loc[~mask & mask1, 'valuepay'] = 0

sample:

d = {'datedue': [pd.timestamp('2013-10-06 00:00:00'), pd.timestamp('2013-10-08 00:00:00'),                   pd.timestamp('2013-10-08 00:00:00'), pd.timestamp('2013-10-08 00:00:00')],       'datepay': [np.nan, pd.timestamp('2013-10-06 00:00:00'),                   pd.timestamp('2013-10-12 00:00:00'), pd.timestamp('2013-10-10 00:00:00')]} df = pd.dataframe(d)  print (df)      datedue    datepay 0 2013-10-06        nat 1 2013-10-08 2013-10-06 2 2013-10-08 2013-10-12 3 2013-10-08 2013-10-10  #get boolean mask nan mask = df['datepay'].isnull()  #modify column valuepay mask df.loc[mask, 'valuepay'] = 0  #get mask  mask1 = ((df['datepay'] - df['datedue']) / np.timedelta64(1,'h')) > 24  #inverted mask , mask1 -> modify valuepay df.loc[~mask & mask1, 'valuepay'] = 0 print (df)      datedue    datepay  valuepay 0 2013-10-06        nat       0.0 1 2013-10-08 2013-10-06       nan 2 2013-10-08 2013-10-12       0.0 3 2013-10-08 2013-10-10       0.0

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