notebook.community

Edit and run



In [1]:

    
import pandas as pd



In [2]:

    
df = pd.read_csv('features.csv')



In [3]:

    
df.sample(10)









    Out[3]:







  
    
      
      match_id
      start_time
      lobby_type
      r1_hero
      r1_level
      r1_xp
      r1_gold
      r1_lh
      r1_kills
      r1_deaths
      ...
      dire_boots_count
      dire_ward_observer_count
      dire_ward_sentry_count
      dire_first_ward_time
      duration
      radiant_win
      tower_status_radiant
      tower_status_dire
      barracks_status_radiant
      barracks_status_dire
    
  
  
    
      70150
      82508
      1448671932
      7
      51
      4
      1310
      875
      9
      0
      2
      ...
      3
      3
      1
      -39.0
      2679
      1
      1830
      0
      63
      0
    
    
      71601
      84212
      1448753140
      1
      50
      2
      484
      549
      1
      0
      1
      ...
      5
      2
      1
      -34.0
      1916
      0
      1792
      1974
      51
      63
    
    
      76742
      90284
      1449061992
      1
      106
      4
      1693
      1621
      27
      0
      0
      ...
      3
      3
      1
      -37.0
      1402
      1
      2047
      1536
      63
      12
    
    
      7694
      9090
      1433934166
      7
      112
      2
      334
      756
      1
      0
      1
      ...
      2
      2
      0
      -37.0
      2731
      0
      0
      1956
      0
      63
    
    
      65144
      76608
      1448334645
      7
      72
      3
      1124
      1349
      16
      1
      0
      ...
      2
      3
      0
      -33.0
      2632
      1
      1972
      0
      63
      0
    
    
      42935
      50494
      1445091491
      7
      99
      3
      1202
      677
      4
      0
      0
      ...
      3
      2
      0
      42.0
      2854
      0
      0
      1828
      0
      63
    
    
      38990
      45863
      1444314851
      1
      75
      3
      1003
      1051
      11
      0
      0
      ...
      4
      4
      0
      7.0
      1634
      0
      1926
      2046
      51
      63
    
    
      64818
      76232
      1448310820
      0
      50
      3
      601
      847
      0
      1
      0
      ...
      2
      2
      1
      9.0
      2091
      0
      4
      2046
      3
      63
    
    
      80820
      95069
      1449277774
      1
      47
      3
      1057
      1325
      15
      0
      1
      ...
      2
      3
      0
      -14.0
      1198
      1
      2046
      6
      63
      3
    
    
      57102
      67099
      1447269895
      0
      55
      3
      1404
      1003
      12
      0
      0
      ...
      1
      2
      1
      -7.0
      1569
      1
      1980
      0
      63
      0
    
  

10 rows × 109 columns



In [4]:

    
%pylab inline









    



Populating the interactive namespace from numpy and matplotlib



In [5]:

    
pylab.plot([1,2,3,67,3,4,8,9,7,5,4,3,2])









    Out[5]:





[<matplotlib.lines.Line2D at 0x2724e059cc0>]



In [21]:

    
pylab.plot(np.random.random(200),np.random.random(200),c="red",label="line1",alpha=0.2)
pylab.plot(np.random.random(200),np.random.random(200),c="green",label="line2",alpha=0.2,lw=4)
pylab.title("Some graph")
pylab.xlabel("X")
pylab.ylabel("Y")
pylab.legend()









    Out[21]:





<matplotlib.legend.Legend at 0x2724f0f8cf8>



In [ ]:

	match_id	start_time	lobby_type	r1_hero	r1_level	r1_xp	r1_gold	r1_lh	r1_kills	r1_deaths	...	dire_boots_count	dire_ward_observer_count	dire_ward_sentry_count	dire_first_ward_time	duration	radiant_win	tower_status_radiant	tower_status_dire	barracks_status_radiant	barracks_status_dire
70150	82508	1448671932	7	51	4	1310	875	9	0	2	...	3	3	1	-39.0	2679	1	1830	0	63	0
71601	84212	1448753140	1	50	2	484	549	1	0	1	...	5	2	1	-34.0	1916	0	1792	1974	51	63
76742	90284	1449061992	1	106	4	1693	1621	27	0	0	...	3	3	1	-37.0	1402	1	2047	1536	63	12
7694	9090	1433934166	7	112	2	334	756	1	0	1	...	2	2	0	-37.0	2731	0	0	1956	0	63
65144	76608	1448334645	7	72	3	1124	1349	16	1	0	...	2	3	0	-33.0	2632	1	1972	0	63	0
42935	50494	1445091491	7	99	3	1202	677	4	0	0	...	3	2	0	42.0	2854	0	0	1828	0	63
38990	45863	1444314851	1	75	3	1003	1051	11	0	0	...	4	4	0	7.0	1634	0	1926	2046	51	63
64818	76232	1448310820	0	50	3	601	847	0	1	0	...	2	2	1	9.0	2091	0	4	2046	3	63
80820	95069	1449277774	1	47	3	1057	1325	15	0	1	...	2	3	0	-14.0	1198	1	2046	6	63	3
57102	67099	1447269895	0	55	3	1404	1003	12	0	0	...	1	2	1	-7.0	1569	1	1980	0	63	0