Pandas内置的十种画图方法

df = pd.DataFrame({
    'sales': [3, 3, 3, 9, 10, 6],
    'signups': [4, 5, 6, 10, 12, 13],
    'visits': [20, 42, 28, 62, 81, 50],
}, index=pd.date_range(start='2018/01/01', end='2018/07/01', freq='M'))
 
# 方法1，这种方法是高层api，需要制定kind
df.plot(kind='area')
 
# 方法2，这种方法是底层API
df.plot.area()

# 默认为面积堆叠
df.plot(kind='area')

# 设置面积不堆叠
df.plot.area(stacked=False)

# 手动指定坐标轴
df.plot.area(y='sales', x='signups')

df = pd.DataFrame({'lab':['A', 'B', 'C'], 'val':[10, 30, 20]})
# 手动设置坐标轴
ax = df.plot.bar(x='lab', y='val', rot=0)

# 并排绘制
df.plot.bar(rot=0)

# 堆叠绘制
df.plot.bar(stacked=True)

# 分图绘制
axes = df.plot.bar(rot=0, subplots=True)
axes[0].legend(loc=2)
axes[1].legend(loc=2)  

# 并排绘制
df.plot.barh(rot=0)

# 堆叠绘制
df.plot.barh(stacked=True)

age_list = [8, 10, 12, 14, 72, 74, 76, 78, 20, 25, 30, 35, 60, 85]
df = pd.DataFrame({"gender": list("MMMMMMMMFFFFFF"), "age": age_list})
ax = df.plot.box(column="age", by="gender", figsize=(10, 8))

s = pd.Series([1, 2, 2.5, 3, 3.5, 4, 5])
ax = s.plot.kde()

df = pd.DataFrame({
    'x': [1, 2, 2.5, 3, 3.5, 4, 5],
    'y': [4, 4, 4.5, 5, 5.5, 6, 6],
})
ax = df.plot.kde()

n = 10000
df = pd.DataFrame({'x': np.random.randn(n),
                   'y': np.random.randn(n)})
ax = df.plot.hexbin(x='x', y='y', gridsize=20)

df = pd.DataFrame(
    np.random.randint(1, 7, 6000),
    columns = ['one'])
df['two'] = df['one'] + np.random.randint(1, 7, 6000)
ax = df.plot.hist(bins=12, alpha=0.5)

s = pd.Series([1, 3, 2])
s.plot.line()

df = pd.DataFrame({
   'pig': [20, 18, 489, 675, 1776],
   'horse': [4, 25, 281, 600, 1900]
   }, index=[1990, 1997, 2003, 2009, 2014])
 
lines = df.plot.line()

df = pd.DataFrame({'mass': [0.330, 4.87 , 5.97],
                   'radius': [2439.7, 6051.8, 6378.1]},
                  index=['Mercury', 'Venus', 'Earth'])
 
plot = df.plot.pie(y='mass', figsize=(5, 5))

# 默认使用index进行分组
df.plot.pie(subplots=True, figsize=(11, 6))

df = pd.DataFrame([[5.1, 3.5, 0], [4.9, 3.0, 0], [7.0, 3.2, 1],
                   [6.4, 3.2, 1], [5.9, 3.0, 2]],
                  columns=['length', 'width', 'species'])
 
ax1 = df.plot.scatter(x='length',y='width', c='DarkBlue')