摘要： matplotlib 数据可视化，介绍条形图、直方图，饼状图的绘制；主要：条形图对比用，折线图变化，散点图离散度

条形图一般用作统计过的数据，进行对比

import matplotlib.pyplot as plt
plt.figure(figsize=(20,8),dpi=100)
a = ["战狼2","速度与激情8","功夫瑜伽","西游伏妖篇","变形金刚5：最后的骑士","摔跤吧！爸爸","加勒比海盗5：死无对证","金刚：骷髅岛","极限特工：终极回归","生化危机6：终章","乘风破浪","神偷奶爸3","智取威虎山","大闹天竺","金刚狼3：殊死一战","蜘蛛侠：英雄归来","悟空传","银河护卫队2","情圣","新木乃伊",]

b=[56.01,26.94,17.53,16.49,15.45,12.96,11.8,11.61,11.28,11.12,10.49,10.3,8.75,7.55,7.32,6.99,6.88,6.86,6.58,6.23]

x = range(len(a))

plt.bar(x,b,width=0.5,color='r')
# 替换成中文
plt.xticks(x,a,rotation=45)
# 标题
plt.title('电影票房数据统计')
plt.xlabel('电影')
plt.ylabel('票房')
plt.show()

plt.Figure(figsize=(20,8),dpi=100)
a = ["战狼2","速度与激情8","功夫瑜伽","西游伏妖篇","变形金刚5：最后的骑士","摔跤吧！爸爸","加勒比海盗5：死无对证","金刚：骷髅岛","极限特工：终极回归","生化危机6：终章","乘风破浪","神偷奶爸3","智取威虎山","大闹天竺","金刚狼3：殊死一战","蜘蛛侠：英雄归来","悟空传","银河护卫队2","情圣","新木乃伊",]

b=[56.01,26.94,17.53,16.49,15.45,12.96,11.8,11.61,11.28,11.12,10.49,10.3,8.75,7.55,7.32,6.99,6.88,6.86,6.58,6.23]

_x = range(len(a))
# 横着显示
plt.barh(_x,b)
plt.yticks(_x,a)

plt.title('电影票房数据统计')
# 将票房扶正 
plt.xlabel('票房',rotation=0)
plt.ylabel('电影')

plt.show()

plt.Figure(figsize=(20,8),dpi=100)
a = ["猩球崛起3：终极之战","敦刻尔克","蜘蛛侠：英雄归来","战狼2"]
b_16 = [15746,312,4497,319]
b_15 = [12357,156,2045,168]
b_14 = [2358,399,2358,362]

bar_width = 0.2

# 获取x长度
_x14 = range(len(b_14))
# 每个元素+0.2
_x15 = [i+bar_width for i in _x14]
_x16 = [i+bar_width for i in _x15]

plt.bar(_x14,b_14,width=bar_width)
plt.bar(_x15,b_15,width=bar_width)
plt.bar(_x16,b_16,width=bar_width)

# 显示中文，并显示在中间
plt.xticks(_x15,a)

plt.show()

未统计过数据用直方图

• 分布状态

# 绘制直方图
plt.Figure(figsize=(20,8),dpi=100)
a=[131,  98, 125, 131, 124, 139, 131, 117, 128, 108, 135, 138, 131, 102, 107, 114, 119, 128, 121, 142, 127, 130, 124, 101, 110, 116, 117, 110, 128, 128, 115,  99, 136, 126, 134,  95, 138, 117, 111,78, 132, 124, 113, 150, 110, 117,  86,  95, 144, 105, 126, 130,126, 130, 126, 116, 123, 106, 112, 138, 123,  86, 101,  99, 136,123, 117, 119, 105, 137, 123, 128, 125, 104, 109, 134, 125, 127,105, 120, 107, 129, 116, 108, 132, 103, 136, 118, 102, 120, 114,105, 115, 132, 145, 119, 121, 112, 139, 125, 138, 109, 132, 134,156, 106, 117, 127, 144, 139, 139, 119, 140,  83, 110, 102,123,107, 143, 115, 136, 118, 139, 123, 112, 118, 125, 109, 119, 133,112, 114, 122, 109, 106, 123, 116, 131, 127, 115, 118, 112, 135,115, 146, 137, 116, 103, 144,  83, 123, 111, 110, 111, 100, 154,136, 100, 118, 119, 133, 134, 106, 129, 126, 110, 111, 109, 141,120, 117, 106, 149, 122, 122, 110, 118, 127, 121, 114, 125, 126,114, 140, 103, 130, 141, 117, 106, 114, 121, 114, 133, 137,  92,121, 112, 146,  97, 137, 105,  98, 117, 112,  81,  97, 139, 113,134, 106, 144, 110, 137, 137, 111, 104, 117, 100, 111, 101, 110,105, 129, 137, 112, 120, 113, 133, 112,  83,  94, 146, 133, 101,131, 116, 111,  84, 137, 115, 122, 106, 144, 109, 123, 116, 111,111, 133, 150]
# 分组:组数
# 设置多少组合适
# 组数=极差/组距
# 极差 ：最大值-最小值


# 组距
d = 5

# 必须是一个整数
num_bins=(max(a)-min(a))//d

plt.hist(a,num_bins,color='b')

# x轴改变
plt.xticks(range(min(a),max(a)+d)[::5])

# 网格添加
plt.grid(alpha=0.4,linestyle='-.')

plt.show()

# 绘制直方图
plt.Figure(figsize=(20,8),dpi=100)
a=[131,  98, 125, 131, 124, 139, 131, 117, 128, 108, 135, 138, 131, 102, 107, 114, 119, 128, 121, 142, 127, 130, 124, 101, 110, 116, 117, 110, 128, 128, 115,  99, 136, 126, 134,  95, 138, 117, 111,78, 132, 124, 113, 150, 110, 117,  86,  95, 144, 105, 126, 130,126, 130, 126, 116, 123, 106, 112, 138, 123,  86, 101,  99, 136,123, 117, 119, 105, 137, 123, 128, 125, 104, 109, 134, 125, 127,105, 120, 107, 129, 116, 108, 132, 103, 136, 118, 102, 120, 114,105, 115, 132, 145, 119, 121, 112, 139, 125, 138, 109, 132, 134,156, 106, 117, 127, 144, 139, 139, 119, 140,  83, 110, 102,123,107, 143, 115, 136, 118, 139, 123, 112, 118, 125, 109, 119, 133,112, 114, 122, 109, 106, 123, 116, 131, 127, 115, 118, 112, 135,115, 146, 137, 116, 103, 144,  83, 123, 111, 110, 111, 100, 154,136, 100, 118, 119, 133, 134, 106, 129, 126, 110, 111, 109, 141,120, 117, 106, 149, 122, 122, 110, 118, 127, 121, 114, 125, 126,114, 140, 103, 130, 141, 117, 106, 114, 121, 114, 133, 137,  92,121, 112, 146,  97, 137, 105,  98, 117, 112,  81,  97, 139, 113,134, 106, 144, 110, 137, 137, 111, 104, 117, 100, 111, 101, 110,105, 129, 137, 112, 120, 113, 133, 112,  83,  94, 146, 133, 101,131, 116, 111,  84, 137, 115, 122, 106, 144, 109, 123, 116, 111,111, 133, 150]
# 分组:组数
# 设置多少组合适
# 组数=极差/组距
# 极差 ：最大值-最小值


# 组距
d = 5

result = round((max(a)-min(a))/d)+1

# 必须是一个整数
num_bins=[78+i*d for i in range(result)]

plt.hist(a,num_bins)

# x轴改变
plt.xticks(num_bins)

# 网格添加
plt.grid(alpha=0.4,linestyle='-.')

plt.show()

饼状图统计过的数据

• 占比

plt.figure(figsize=(20,8),dpi=100)
movie_name = ['雷神3：诸神黄昏','正义联盟','东方快车谋杀案','寻梦环游记','全球风暴',
'降魔传','追捕','七十七天','密战','狂兽','其它']

place_count = [60605,54546,45819,28243,13270,
9945,7679,6799,6101,4621,20105]

plt.pie(place_count,labels=movie_name,autopct='%3.2f%%',colors=['b','r','g','y','c','m','y','k','c','g','g'])

# 保证饼状图是圆的
plt.axis('equal')
# 添加图例
plt.legend(loc='upper left')

plt.show()