In [1]:

    

import pandas as pd
import numpy as np


    

In [3]:

    

pd.read_csv('faa-wildlife-strike-clean.csv').head()


    

    
Out[3]:






  

    

      

      
SKY
      
FLT
      
DAMAGE
      
REPORTED_NAME
      
REMAINS_COLLECTED
      
BIRDS_SEEN
      
FAAREGION
      
REPORTED_DATE
      
EFFECT_OTHER
      
REMAINS_SENT
      
...
      
COST_REPAIRS_INFL_ADJ
      
ENROUTE
      
RUNWAY
      
AIRPORT
      
COMMENTS
      
COST_OTHER_INFL_ADJ
      
REMARKS
      
NUM_ENGS
      
TIME
      
SPEED
    
  
  

    

      
0
      
 NaN
      
 NaN
      
              NaN
      
     NaN
      
  True
      
 NaN
      
 AWP
      
     NaN
      
 NaN
      
 False
      
...
      
 NaN
      
 NaN
      
 NaN
      
                             LIHUE ARPT
      
                                          NaN
      
 NaN
      
                                               NaN
      
  2
      
   NaN
      
 NaN
    
    

      
1
      
 NaN
      
 NaN
      
 Minor (Civilian)
      
     NaN
      
 False
      
 NaN
      
 ASO
      
     NaN
      
 NaN
      
 False
      
...
      
 NaN
      
 NaN
      
 NaN
      
 CINCINNATI/NORTHERN KENTUCKY INTL ARPT
      
 SOURCE = FAA AIRCRAFT ACCIDENT/INCIDENT REPT
      
 NaN
      
 HIT GULL AFTER T/O (ASSUME CLIMB). CONTD TO DE...
      
  2
      
   NaN
      
 NaN
    
    

      
2
      
 NaN
      
 NaN
      
              NaN
      
     NaN
      
  True
      
 NaN
      
 AWP
      
     NaN
      
 NaN
      
 False
      
...
      
 NaN
      
 NaN
      
 NaN
      
                             LIHUE ARPT
      
                                          NaN
      
 NaN
      
                                               NaN
      
NaN
      
   NaN
      
 NaN
    
    

      
3
      
 NaN
      
 NaN
      
  None (Military)
      
 Deleted
      
 False
      
   1
      
 ASO
      
 5/19/00
      
 NaN
      
 False
      
...
      
 NaN
      
 NaN
      
 NaN
      
                      MYRTLE BEACH INTL
      
                       SOURCE = BASH NR xxxxx
      
 NaN
      
 REMARKS -  ;  AIRCRAFT -  A - 10 - ;  IMPACT -...
      
NaN
      
 09:10
      
 138
    
    

      
4
      
 NaN
      
 NaN
      
  None (Military)
      
 Deleted
      
  True
      
   1
      
 ASO
      
 5/19/00
      
 NaN
      
  True
      
...
      
 NaN
      
 NaN
      
 NaN
      
                      JACKSONVILLE INTL
      
                       SOURCE = BASH NR xxxxx
      
 NaN
      
 REMARKS -  ;  AIRCRAFT -  F - 16 - ;  IMPACT -...
      
NaN
      
 09:40
      
 200
    
  

5 rows × 42 columns

In [4]:

    

df = pd.read_csv('faa-wildlife-strike-clean.csv')


    

In [8]:

    

df.COST_OTHER_INFL_ADJ.apply(lambda x: np.float(x))


    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-8-84a28d0983ff> in <module>()
----> 1 df.COST_OTHER_INFL_ADJ.apply(lambda x: np.float(x))

/Library/Python/2.7/site-packages/pandas/core/series.pyc in apply(self, func, convert_dtype, args, **kwds)
   2049             values = lib.map_infer(values, lib.Timestamp)
   2050 
-> 2051         mapped = lib.map_infer(values, f, convert=convert_dtype)
   2052         if len(mapped) and isinstance(mapped[0], Series):
   2053             from pandas.core.frame import DataFrame

/Library/Python/2.7/site-packages/pandas/lib.so in pandas.lib.map_infer (pandas/lib.c:56671)()

<ipython-input-8-84a28d0983ff> in <lambda>(x)
----> 1 df.COST_OTHER_INFL_ADJ.apply(lambda x: np.float(x))

ValueError: invalid literal for float(): 753,021

In [ ]:

    

df.groupby(')