数据可视化—各种基础图
文章目录
- 一、matplotlib练习
- 二、matplotlib练习二
- 三、legend()函数和plot的线条样式
- 四、总结
- 五、散点图
- 六、条形图
- 六、多条形图
- 六、直方图
- 七、饼图
- 总结
一、matplotlib练习
假设大家在30岁的时候,根据自己的实际情况,统计出来了从11岁到30岁每年交的女(男)朋友的数量如列表a,请绘制出该数据的折线图,以便分析自己每年交女(男)朋友的数量走势
a =[1,0,1,1,2,4,3,2,3,4,4,5,6,5,4,3,3,1,1,1]
要求:
y轴表示个数
x轴表示岁数,比如11岁,12岁等
import matplotlib.pyplot as plt
from matplotlib import font_manager
plt.rcParams['font.sans-serif']=['SimHei']
y = [1,0,1,1,2,4,3,3,3,4,4,5,6,5,4,3,3,1,1,1]
x = range(11,31)
plt.plot(x,y)
plt.figure(figsize=(20,8),dpi=80)
plt.plot(x,y)
_xtick_labels = ["{}岁".format(i) for i in x]
plt.xticks(x,_xtick_labels)
plt.yticks(range(0,9))
#设置网格
plt.grid(linestyle=":",color="r",alpha=0.4)
plt.show()
二、matplotlib练习二
假设大家在30岁的时候,根据自己的实际情况,统计出来了你和你同桌各
自从11岁到30岁每年交的女(男)朋友的数量如列表a和b,请在一个图中绘制出该数据的折线图,以便比较自己和同桌20年间的差异,同时分析每年交女(男)朋友的数量走势
a = [1,0,1,1,2,4,3,2,3,4,4,5,6,5,4,3,3,1,1,1]b = [1,0,3,1,2,2,3,3,2,1,2,1,1,1,1,1,1,1,1,1]
要求:
y轴表示个数
x轴表示岁数,比如11岁,12岁等
import matplotlib.pyplot as plt
from matplotlib import font_manager
plt.rcParams['font.sans-serif']=['SimHei']
y_1 = [1,0,1,1,2,4,3,3,3,4,4,5,6,5,4,3,3,1,1,1]
y_2 = [1,0,3,1,2,2,3,3,2,1,2,1,1,1,1,1,1,1,1,1]
x = range(11,31)
plt.plot(x,y_1,label="自己")
plt.plot(x,y_2,label="同桌")
# plt.figure(figsize=(20,8),dpi=50)
_xtick_labels = ["{}岁".format(i) for i in x]
plt.xticks(x,_xtick_labels)
plt.yticks(range(0,9))
#设置网格
plt.grid(linestyle=":",color="r",alpha=0.4)
# 添加图例
plt.legend(loc = "upper left")
plt.show()
三、legend()函数和plot的线条样式
import matplotlib.pyplot as plt
from matplotlib import font_manager
plt.rcParams['font.sans-serif']=['SimHei']
y_1 = [1,0,1,1,2,4,3,3,3,4,4,5,6,5,4,3,3,1,1,1]
y_2 = [1,0,3,1,2,2,3,3,2,1,2,1,1,1,1,1,1,1,1,1]
x = range(11,31)
plt.plot(x,y_1,label="自己",c="c",lw=2,ls="-.")
plt.plot(x,y_2,label="同桌",c="orange",lw=2,ls="--")
# plt.figure(figsize=(20,8),dpi=50)
_xtick_labels = ["{}岁".format(i) for i in x]
plt.xticks(x,_xtick_labels)
plt.yticks(range(0,9))
#设置网格
plt.grid(linestyle=":",color="r",alpha=0.4)
# 添加图例
plt.legend(loc = "upper left")
plt.show()
四、总结
1.绘制了折线图(plt.plot)
2．设置了图片的大小和分辨率(plt.figure)
3．实现了图片的保存(plt.savefig)
4．设置了x轴上的刻度和字符串(xticks)
5．解决了刻度稀疏和密集的问题(xticks)
6．设置了标题,xy轴的lable(title,xlable,ylable)
7．设置了字体(font …manager. fontProperties.matplotlib.rc)
8.在一个图上绘制多个图形(plt多次plot即可)
9．为不同的图形添加图例
五、散点图
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif']=['SimHei']
y_3 = [11,17,16,11,12,11,12,6,6,7,8,9,12,15,14,17,18,21,16,17,20,14,15,15,15,19,21,22,22,22,23]
y_10 = [26,26,28,19,21,17,16,19,18,20,20,19,22,23,17,20,21,20,22,15,11,15,5,13,17,10,11,13,12,13,6]
x_3 = range(1,32)
x_10 = range(51,82)
plt.figure(figsize=(20,8),dpi=80)
plt.scatter(x_3,y_3,label="3月份")
plt.scatter(x_10,y_10,label="10月份")
_x = list(x_3)+list(x_10)
_xtick_labels = ["3月{}日".format(i) for i in x_3]
_xtick_labels += ["10月{}日".format(i-50) for i in x_10]
plt.xticks(_x[::3],_xtick_labels[::3],rotation = 45)
# plt.yticks(range(0,9))
#添加图例
plt.legend(loc = "upper left")
# plt.grid(linestyle=":",color="r",alpha=0.4)
# 添加描述信息
plt.xlabel("时间")
plt.ylabel("温度")
plt.title("天气")
plt.show()
六、条形图
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif']=['SimHei']
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]
plt.figure(figsize=(20,8),dpi=80)
plt.bar(range(len(a)),b,width=0.3)
plt.xticks(range(len(a)),a,rotation=45)
plt.show()
六、多条形图
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif']=['SimHei']
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
x_14 = list(range(len(a)))
x_15 = [i+0.2 for i in x_14]
x_16 = [i+0.2*2 for i in x_14]
plt.figure(figsize=(20,8),dpi=80)
plt.bar(range(len(a)),b_14,width=bar_width,label="9月14日")
plt.bar(x_15,b_15,width=bar_width,label="9月14日")
plt.bar(x_16,b_16,width=bar_width,label="9月14日")
plt.xticks(x_15,a)
plt.legend()
plt.show()
六、直方图
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif']=['SimHei']
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 = 3
num_bins = (max(a)-min(a))//d
plt.hist(a,num_bins)
plt.xticks(range(min(a),max(a)+d,d))
plt.grid()
plt.show()
七、饼图
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif']=['SimHei']
kinds = "简易箱","保温箱","行李箱","密封箱"
colors= ["red","green","yellow","blue"]
soldNums = [0.05,0.45,0.15,0.35]
plt.pie(soldNums,labels=kinds,autopct="%3.1f%%",startangle=60,colors=colors)
plt.title("不同类型的箱子销售数量占比")
plt.show()
总结
1．应该选择那种图形来呈现数据
2. matplotlib.plot(xy)
3. matplotlib.bar(x.y)
4. 4. matplotlib.scatter(x.y)
5. matplotlib.hist(data,bins.normed)
6. 6. xticks和yticks的设置
7. label和titile,grid的设置
8. 8.绘图的大小和保存图片