matplotlib绘制直方图
假设你获取了250部电影的时长(列表a中),希望统计出这些电影时长的分布状态(比如时长为100分钟到120分钟电影的数量,出现的频率)等信息,你应该如何呈现这些数据?
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]
把数据分成多少组进行统计？
组数要适当,太少会有较大的统计误差,大多规律不明显。
代码如下：
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname="C:/Windows/Fonts/SIMYOU.TTF")
plt.figure(figsize=(20,8),dpi=80)
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]
# 计算组数
# d:组距
d = 3
num_bins = (max(a)-min(a))//d
print(min(a),max(a),max(a)-min(a))
plt.hist(a,num_bins,normed=True)
# 设置x轴的刻度
plt.xticks(range(min(a),max(a)+d,d))
# 绘制网格
plt.grid(alpha=0.4)
plt.xlabel("电影时长",fontproperties=my_font)
plt.ylabel("数量",fontproperties=my_font)
plt.title("标题",fontproperties=my_font)
plt.show()
显示结果：
例题：
在美国2004年人口普查发现有124 million的人在离家相对较远的地方工作。根据他们从家到上班地点所需要的时间,通过抽样统计(最后一列)出了下表的数据,这些数据能够绘制成直方图么?
interval = [0,5,10,15,20,25,30,35,40,45,60,90]
width = [5,5,5,5,5,5,5,5,5,15,30,60]
quantity = [836,2737,3723,3926,3596,1438,3273,642,824,613,215,47]
代码如下：
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname="C:/Windows/Fonts/SIMYOU.TTF")
x_interval = [0,5,10,15,20,25,30,35,40,45,60,90]
width = [5,5,5,5,5,5,5,5,5,15,30,60]
y_quantity = [836,2737,3723,3926,3596,1438,3273,642,824,613,215,47]
plt.figure(figsize=(20,8),dpi=80)
plt.bar(range(len(y_quantity)),y_quantity,width=1)
# 设置x轴的刻度
_x = [i-0.5 for i in range(12)]
_xticks_labels = x_interval + [150]
plt.xticks(_x,_xticks_labels)
plt.grid(alpha=0.4)
plt.xlabel("从家到上班地点所需要的时间",fontproperties=my_font)
plt.ylabel("人数",fontproperties=my_font)
plt.title("标题",fontproperties=my_font)
plt.show()
结果显示：
那些数据能够绘制直方图
前面的问题给出的数据都是统计之后的数据，所以为了达到直方图的效果，需要绘制条形图。
所以，一般来说能够使用plt.hist方法的的hi那些没有统计过的数据。
直方图的应用场景
- 用户的年龄分布状态
- 一段时间内用户点击次数的分布状态
- 用户活跃的分布状态
matplotlib常见问题总结
- 应该选择那种图形来呈现数据
- 折线图：matplotlib.plot(x,y)
- 条形图：matplotlib.bar(x,y)
- 柱状图：matplotlib.hist(data,bins,normed)
- 散点图：matplotlib.scatter(x,y)
- xticks和yticks的设置
- label和title,grid的设置
- 绘图大小和保存图片
matplotlib使用流程总结
- 明确问题
- 选择图形的呈现形式
- 准备数据
- 绘图和图形完善
matplotlib更多的图形样式
matplotlib支持的图形非常多，如果有其他需求，可以查看下面url地址：http://matplotlib.org/gallery/index.html
plotly
可视化工具的github,相比于matplotlib更加简单，图形更加漂亮，同时兼容matplotlib和pandas。
使用用法：简单，照着文档即可
文档地址：https://plot.ly/python/