一：Series柱狀圖
flg,axes = plt.subplots(2,1)
data =Series( np.random.rand(10),index = "abcdefghij")
data.plot(kind = 'bar',ax = axes[0],color = 'k',alpha = 0.7)
data.plot(kind = 'barh',ax = axes[1],color = 'k',alpha = 0.7)
利用value_counts圖形化顯示Series中各值的出現頻率
data.value_counts().plot(kind ="bar")
二：DataFrame柱狀圖
data = {'state':['ohio','ohio','ohio','Nevada','Nevada'],
'year':[2000,2001,2001,2002,2003],
'pop':[1.5,2.7,3.9,3.4,2.9]}
frame = DataFrame(data) #DataFrame 會自動加上索引，會被全部有序排列
#指定列序列，按照制定順序進行排序(數據，列名)
DataFrame(data,columns = ['year','pop','state'])
指定預期的行名和列名進行排序
frame2 = DataFrame(data,columns = ['year','pop','state','debt'],
index = ['one','two','three','four','five'])
frame2
給相應的某一列進行隨機賦值
frame2['debt'] = np.arange(5)
frame2
