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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#
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原文地址：http://www.cnblogs.com/nju2014/p/5049208.html
