使用numpy從CSV文件中提取數據

Question

我正在與numpy一起工作，並試圖找到哪個平臺銷售的NA區域中的副本數量最多。

我有一個CSV文件來保存大量的數據看起來像這樣的：

Rank,Name,Platform,Year,Genre,Publisher,NA_Sales,EU_Sales,JP_Sales,Other_Sales,Global_Sales 
1,Wii Sports,Wii,2006,Sports,Nintendo,41.49,29.02,3.77,8.46,82.74 
2,Super Mario Bros.,NES,1985,Platform,Nintendo,29.08,3.58,6.81,0.77,40.24 
3,Mario Kart Wii,Wii,2008,Racing,Nintendo,15.85,12.88,3.79,3.31,35.82 
4,Wii Sports Resort,Wii,2009,Sports,Nintendo,15.75,11.01,3.28,2.96,33 
5,Pokemon Red/Pokemon Blue,GB,1996,Role-Playing,Nintendo,11.27,8.89,10.22,1,31.37 
6,Tetris,GB,1989,Puzzle,Nintendo,23.2,2.26,4.22,0.58,30.26 
7,New Super Mario Bros.,DS,2006,Platform,Nintendo,11.38,9.23,6.5,2.9,30.01 
8,Wii Play,Wii,2006,Misc,Nintendo,14.03,9.2,2.93,2.85,29.02 
9,New Super Mario Bros. Wii,Wii,2009,Platform,Nintendo,14.59,7.06,4.7,2.26,28.62 
10,Duck Hunt,NES,1984,Shooter,Nintendo,26.93,0.63,0.28,0.47,28.31 
11,Nintendogs,DS,2005,Simulation,Nintendo,9.07,11,1.93,2.75,24.76 

我想用最銷售及NA區域售電量打印平臺。我怎樣才能做到這一點？

Answer 1

隨着熊貓，這是相當直接。

代碼：

# read csv data into a dataframe 
df = pd.read_csv(data, skipinitialspace=True) 

# roll up by NA Sales 
platform_roll_up = df.groupby('Platform')['NA_Sales'].sum() 

# find row with max sales 
idx_max = platform_roll_up.idxmax() 

# show platform and sales for max 
print(idx_max, platform_roll_up[idx_max]) 

結果：

Wii 101.71 

測試數據：

data = StringIO(u""" 
    Rank,Name,Platform,Year,Genre,Publisher,NA_Sales,EU_Sales,JP_Sales,Other_Sales,Global_Sales 
    1,Wii Sports,Wii,2006,Sports,Nintendo,41.49,29.02,3.77,8.46,82.74 
    2,Super Mario Bros.,NES,1985,Platform,Nintendo,29.08,3.58,6.81,0.77,40.24 
    3,Mario Kart Wii,Wii,2008,Racing,Nintendo,15.85,12.88,3.79,3.31,35.82 
    4,Wii Sports Resort,Wii,2009,Sports,Nintendo,15.75,11.01,3.28,2.96,33 
    5,Pokemon Red/Pokemon Blue,GB,1996,Role-Playing,Nintendo,11.27,8.89,10.22,1,31.37 
    6,Tetris,GB,1989,Puzzle,Nintendo,23.2,2.26,4.22,0.58,30.26 
    7,New Super Mario Bros.,DS,2006,Platform,Nintendo,11.38,9.23,6.5,2.9,30.01 
    8,Wii Play,Wii,2006,Misc,Nintendo,14.03,9.2,2.93,2.85,29.02 
    9,New Super Mario Bros. Wii,Wii,2009,Platform,Nintendo,14.59,7.06,4.7,2.26,28.62 
    10,Duck Hunt,NES,1984,Shooter,Nintendo,26.93,0.63,0.28,0.47,28.31 
    11,Nintendogs,DS,2005,Simulation,Nintendo,9.07,11,1.93,2.75,24.76 
""") 

Answer 2

與加載此是直截了當：

In [280]: data=np.genfromtxt('stack42602390.csv',delimiter=',',names=True, dtype=None) 

In [281]: data 
Out[281]: 
array([ (1, b'Wii Sports', b'Wii', 2006, b'Sports', b'Nintendo', 41.49, 29.02, 3.77, 8.46, 82.74), 
     (2, b'Super Mario Bros.', b'NES', 1985, b'Platform', b'Nintendo', 29.08, 3.58, 6.81, 0.77, 40.24), 
     (3, b'Mario Kart Wii', b'Wii', 2008, b'Racing', b'Nintendo', 15.85, 12.88, 3.79, 3.31, 35.82), 
.... 
     (11, b'Nintendogs', b'DS', 2005, b'Simulation', b'Nintendo', 9.07, 11. , 1.93, 2.75, 24.76)], 
     dtype=[('Rank', '<i4'), ('Name', 'S25'), ('Platform', 'S3'), ('Year', '<i4'), ('Genre', 'S12'), ('Publisher', 'S8'), ('NA_Sales', '<f8'), ('EU_Sales', '<f8'), ('JP_Sales', '<f8'), ('Other_Sales', '<f8'), ('Global_Sales', '<f8')]) 

的b'string'只是顯示字節串的Python3方式，從genfromtxt默認的字符串格式。他們不會在Py2中顯示。

結果是一個結構化數組，具有不同的字段名稱和類型。它不是包含行和列的2d數組。

的NA_Sales數據：

In [282]: data['NA_Sales'] 
Out[282]: 
array([ 41.49, 29.08, 15.85, 15.75, 11.27, 23.2 , 11.38, 14.03, 
     14.59, 26.93, 9.07]) 

和最大的這些：

In [283]: np.argmax(data['NA_Sales']) 
Out[283]: 0 

和相應的記錄：

In [284]: data[0] 
Out[284]: (1, b'Wii Sports', b'Wii', 2006, b'Sports', b'Nintendo', 41.49, 29.02, 3.77, 8.46, 82.74) 

爲了最大限度地利用這個數組你」的你必須閱讀結構化數組。