折线图示例
#!/usr/bin/python2.7import numpy as npfrom matplotlib import pyplot as pltfrom dbtools import raw_datafrom utils import moving_sumdef moving_sum(array, window): if type(array) is not np.ndarray: raise TypeError('Expected one dimensional numpy array.') remainder = array.size % window if 0 != remainder: array = array[remainder:] array = array.reshape((array.size/window,window)) sum_arr = np.sum(array,axis=1) return sum_arrdef run(): window = 3 y_lst = raw_data('2018-08-03 00:00:00', length=3600*24) raw_arr = np.array(y_lst) sum_arr = moving_sum(raw_arr,window) res = np.true_divide(sum_arr[1:],sum_arr[:-1]) threshold = 0.5 upper = np.array([1+threshold]*res.size) lower = np.array([1-threshold]*res.size) plt.plot(upper,lw=1,color='red',label='Upper') plt.plot(res,lw=1,color='blue',label='Trend') plt.plot(lower,lw=1,color='red',label='Lower') r_idx = np.argwhere(np.abs(res-1) > 0.5) plt.plot(r_idx, res[r_idx], 'ro') plt.legend() plt.show() return (r_idx,res[r_idx]) 
画布和子图
import numpy as npimport matplotlib.pyplot as pltfig = plt.figure(figsize=[10,8])ax1 = fig.add_subplot(2,1,1)x1 = np.linspace(0.1,10,99,endpoint = False)y1 = np.log(x1)ax1.plot(x1,y1)ax1.set_title('Logarithmic function')x2 = np.linspace(0, 5, num = 100)y2 = np.e**x2ax2 = fig.add_subplot(2,1,2)ax2.plot(x2,y2)ax2.set_title('Exponential function')plt.subplots_adjust(hspace =0.2)fig.show() 
柱状图
import numpy as npimport matplotlib.pyplot as pltdata = [32,48,19,85]labels = ['Jan','Feb','Mar','Apr']plt.bar(np.arange(len(data)),data,color='lightgreen')plt.xticks(np.arange(len(data)),labels)plt.show()
饼状图
import numpy as npimport matplotlib.pyplot as pltdata = [35,47,13,5]labels = ['Bili','iQiYi','Tencent','YouKu']plt.pie(data,labels=labels,autopct="%.2f%%",explode=[0.1,0,0,0],shadow=True)plt.show()
K线图
1 pip3.6 install https://github.com/matplotlib/mpl_finance/archive/master.zip2 3 from mpl_finance import candlestick_ochl
matplotlib.finance has been deprecated 1 # https://github.com/Gypsying/iPython/blob/master/601318.csv 2 3 In [2]: import pandas as pd 4 5 In [3]: df = pd.read_csv('601318.csv', index_col='date', parse_dates=['date']) 6 7 In [4]: df.head() 8 Out[4]: 9 Unnamed: 0 open close high low volume code10 date 11 2007-03-01 0 21.878 20.473 22.302 20.040 1977633.51 60131812 2007-03-02 1 20.565 20.307 20.758 20.075 425048.32 60131813 2007-03-05 2 20.119 19.419 20.202 19.047 419196.74 60131814 2007-03-06 3 19.253 19.800 20.128 19.143 297727.88 60131815 2007-03-07 4 19.817 20.338 20.522 19.651 287463.78 60131816 17 In [5]: from matplotlib.dates import date2num 18 19 In [6]: df['time'] = date2num(df.index.to_pydatetime()) 20 21 In [7]: df.head() 22 Out[7]: 23 Unnamed: 0 open close high low volume code time24 date 25 2007-03-01 0 21.878 20.473 22.302 20.040 1977633.51 601318 732736.026 2007-03-02 1 20.565 20.307 20.758 20.075 425048.32 601318 732737.027 2007-03-05 2 20.119 19.419 20.202 19.047 419196.74 601318 732740.028 2007-03-06 3 19.253 19.800 20.128 19.143 297727.88 601318 732741.029 2007-03-07 4 19.817 20.338 20.522 19.651 287463.78 601318 732742.030 31 In [8]: df.shape 32 Out[8]: (2563, 8)33 34 In [9]: df.size 35 Out[9]: 2050436 37 In [10]: 2563*8 38 Out[10]: 2050439 40 In [11]: 数据源 import numpy as npimport pandas as pdfrom matplotlib.dates import date2numfrom mpl_finance import candlestick_ochl# 构建 candlestick_ochl 的sequence of (time, open, close, high, low, ...)df = pd.read_csv('601318.csv', index_col='date', parse_dates=['date'])# time must be in float days format - see date2numdf['time'] = date2num(df.index.to_pydatetime())# 原始数据比较多，截取一部分做展示df = df.iloc[:300,:]arr = df[['time','open','close','high','low']].valuesfig = plt.figure(figsize=[14,7])ax = fig.add_subplot(1,1,1)candlestick_ochl(ax,arr)plt.grid(True, which='major', c='gray', ls='-', lw=1, alpha=0.2)fig.show() 