共用y轴的双图形绘制

实现这种形式的图形，可通过matplotlib和pandas的实现，相比下pandas实现方便的多。

我数据分析的时候主要是stacked bar、bar和line形式的放在一张图上。stacked bar若用matplotlib实现的话会比较复杂（多组）

先上图吧

def plot_stacked_bar(left_data, right_data):
    width = .3
    axe = plt.subplot(111)
    axe = left_data.plot(kind=\'bar\', stacked=True, ax=axe, width=width, use_index=True, legend=False)
    axe.set_xticklabels(left_data.index, rotation=0)

    #add patches to the stacked bar
    patterns = (\'-\', \'+\', \'x\', \'\\\', \'*\', \'o\', \'O\', \'.\', \'/\')
    bars = axe.patches
    hatches = \'\'.join(h*len(left_data) for h in patterns)
    for bar, hatch in zip(bars, hatches):
        bar.set_hatch(hatch)
    
    #plottint the line sharing the same x-axis on the secondary y-axis
    axf = axe.twinx()
    axf.plot(axe.get_xticks(), right_data, linestyle=\'-\', marker=\'o\', linewidth=2.0)
    axf.set_ylim((0, 90))

另一种形式的图形：

from matplotlib import pyplot as plt
import pandas as pd
from pandas import Series
import numpy as np
n = 50
x = pd.period_range(\'2001-01-01\', periods=n, freq=\'M\')
y1 = (Series(np.random.randn(n)) + 5).tolist()
y2 = (Series(np.random.randn(n))).tolist()
df = pd.DataFrame({\'bar\':y2, \'line\':y1}, index=x)

# let\'s plot
plt.figure(figsize=(20, 4))
ax1 = df[\'bar\'].plot(kind=\'bar\', label=\'bar\')
ax2 = ax1.twiny()
df[\'line\'].plot(kind=\'line\', label=\'line\', ax=ax2)
ax2.grid(color="red", axis="x")

def align_xaxis(ax2, ax1, x1, x2):
    "maps xlim of ax2 to x1 and x2 in ax1"
    (x1, _), (x2, _) = ax2.transData.inverted().transform(ax1.transData.transform([[x1, 0], [x2, 0]]))
    xs, xe = ax2.get_xlim()
    k, b = np.polyfit([x1, x2], [xs, xe], 1)
    ax2.set_xlim(xs*k+b, xe*k+b)

align_xaxis(ax2, ax1, 0, n-1)

#参考#