In [1]:

    

import pandas as pd


    

In [2]:

    

fileName = '../Data/StreamCat/NLCD2006_NC.zip'


    

In [11]:

    

df = pd.read_csv(fileName,index_col='COMID')


    

In [13]:

    

df.head()


    

    
Out[13]:






  

    

      

      
CatAreaSqKm
      
WsAreaSqKm
      
CatPctFull
      
WsPctFull
      
PctOw2006Cat
      
PctIce2006Cat
      
PctUrbOp2006Cat
      
PctUrbLo2006Cat
      
PctUrbMd2006Cat
      
PctUrbHi2006Cat
      
...
      
PctBl2006Ws
      
PctDecid2006Ws
      
PctConif2006Ws
      
PctMxFst2006Ws
      
PctShrb2006Ws
      
PctGrs2006Ws
      
PctHay2006Ws
      
PctCrop2006Ws
      
PctWdWet2006Ws
      
PctHbWet2006Ws
    
    

      
COMID
      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

      

    
  
  

    

      
25955618
      
0.1683
      
2715.8274
      
100.0
      
100.0
      
16.577540
      
0.0
      
0.000000
      
0.000000
      
0.000000
      
0.000000
      
...
      
0.065880
      
56.027301
      
9.282784
      
2.660935
      
1.854131
      
4.971557
      
17.289516
      
0.217160
      
0.429052
      
0.020447
    
    

      
8680029
      
4.0923
      
34.3890
      
100.0
      
100.0
      
20.541016
      
0.0
      
5.080273
      
4.068617
      
4.090609
      
2.595118
      
...
      
0.013086
      
41.664486
      
11.994242
      
1.939283
      
1.240513
      
7.644596
      
20.738027
      
0.107302
      
1.002355
      
0.209369
    
    

      
8680033
      
0.7200
      
5.0850
      
100.0
      
100.0
      
8.750000
      
0.0
      
4.000000
      
0.500000
      
0.000000
      
0.000000
      
...
      
0.000000
      
43.362832
      
9.451327
      
1.699115
      
1.168142
      
7.734513
      
29.823009
      
0.000000
      
0.000000
      
0.000000
    
    

      
8673761
      
1.2267
      
4684.5945
      
100.0
      
100.0
      
6.896552
      
0.0
      
0.586941
      
0.146735
      
0.000000
      
0.000000
      
...
      
0.067953
      
57.755050
      
8.854519
      
3.048123
      
1.718928
      
4.464675
      
15.218367
      
0.187239
      
0.338917
      
0.019077
    
    

      
8680001
      
0.1053
      
14.2371
      
100.0
      
100.0
      
6.837607
      
0.0
      
0.000000
      
0.000000
      
0.000000
      
0.000000
      
...
      
0.000000
      
56.343637
      
7.187559
      
2.907896
      
2.105064
      
4.393451
      
22.125292
      
0.082180
      
0.075858
      
0.031608
    
  

5 rows × 36 columns