# 利用python进行折线图，直方图和饼图的绘制

labels   = ['USA', 'China', 'India', 'Japan', 'Germany', 'Russia', 'Brazil', 'UK', 'France', 'Italy']

quants   = [15094025.0, 11299967.0, 4457784.0, 4440376.0, 3099080.0, 2383402.0, 2293954.0, 2260803.0, 2217900.0, 1846950.0]

def draw_line(labels,quants):

ind = np.linspace(0,9,10)

fig = plt.figure(1)

ax.plot(ind,quants)

ax.set_title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5})

ax.set_xticklabels(labels)

plt.grid(True)

plt.show()

def draw_bar(labels,quants):

width = 0.4

ind = np.linspace(0.5,9.5,10)

# make a square figure

fig = plt.figure(1)

# Bar Plot

ax.bar(ind-width/2,quants,width,color='green')

# Set the ticks on x-axis

ax.set_xticks(ind)

ax.set_xticklabels(labels)

# labels

ax.set_xlabel('Country')

ax.set_ylabel('GDP (Billion US dollar)')

# title

ax.set_title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5})

plt.grid(True)

plt.show()

def draw_pie(labels,quants):

plt.figure(1, figsize=(6,6))

# For China, make the piece explode a bit

expl = [0,0.1,0,0,0,0,0,0,0,0]

# Colors used. Recycle if not enough.

colors  = ["blue","red","coral","green","yellow","orange"]

# autopct: format of "percent" string;

plt.pie(quants, explode=expl, colors=colors, labels=labels, autopct='%1.1f%%',pctdistance=0.8, shadow=True)

plt.title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5})

plt.show()

# 三、实验小结

Python的安装比较简单，但是numpymatplotlibscipy的安装并没有预期的简单，首先版本得对应安装的python版本，而且分3264位，资源不容易找，安装成功后还要装其他的东西。至于matplitlib的画图感觉还是比较方便的，初学python，虽然整体简洁了很多，但是python的格式的要求过于严格，尤其是缩进等，初学者查了好久都检查不出错误但后来就又稀里糊涂运行成功了，比较抓狂。

# -*- coding: gbk -*-

import numpy as np

import matplotlib.pyplot as plt

import matplotlib as mpl

def draw_pie(labels,quants):

# make a square figure

plt.figure(1, figsize=(6,6))

# For China, make the piece explode a bit

expl = [0,0.1,0,0,0,0,0,0,0,0]

# Colors used. Recycle if not enough.

colors  = ["blue","red","coral","green","yellow","orange"]

# Pie Plot

# autopct: format of "percent" string;

plt.pie(quants, explode=expl, colors=colors, labels=labels, autopct='%1.1f%%',pctdistance=0.8, shadow=True)

plt.title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5})

plt.show()

def draw_bar(labels,quants):

width = 0.4

ind = np.linspace(0.5,9.5,10)

# make a square figure

fig = plt.figure(1)

# Bar Plot

ax.bar(ind-width/2,quants,width,color='green')

# Set the ticks on x-axis

ax.set_xticks(ind)

ax.set_xticklabels(labels)

# labels

ax.set_xlabel('Country')

ax.set_ylabel('GDP (Billion US dollar)')

# title

ax.set_title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5})

plt.grid(True)

plt.show()

def draw_line(labels,quants):

ind = np.linspace(0,9,10)

fig = plt.figure(1)

ax.plot(ind,quants)

ax.set_title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5})

ax.set_xticklabels(labels)

plt.grid(True)

plt.show()

# quants: GDP

# labels: country name

labels   = ['USA', 'China', 'India', 'Japan', 'Germany', 'Russia', 'Brazil', 'UK', 'France', 'Italy']

quants   = [15094025.0, 11299967.0, 4457784.0, 4440376.0, 3099080.0, 2383402.0, 2293954.0, 2260803.0, 2217900.0, 1846950.0]

draw_pie(labels,quants)

#draw_bar(labels,quants)

#draw_line(labels,quants)

posted @ 2016-03-11 10:23  HUSTLX  阅读(...)  评论(... 编辑 收藏