@@ -3016,8 +3016,7 @@ fig.add_trace(
30163016fig.show()
30173017```
30183018
3019- 
3020- 3019+ < img src=" ./img/plotly1.png" alt=" Sample" width=" 600" height=" 300" >
30213020
30223021
30233022# ### 5 seaborn热力图
@@ -3041,10 +3040,7 @@ plt.show()
30413040```
30423041
30433042
3044- 3045- 
3046- 3047- 3043+ < img src=" ./img/heatmap.png" alt=" Sample" width=" 600" height=" 300" >
30483044
30493045# ### 6 matplotlib折线图
30503046
@@ -3073,7 +3069,7 @@ def label(ax, text, y=0):
30733069 ec = ' #8B7E66' ))
30743070```
30753071
3076- 
3072+ < img src= " https://mmbiz.qpic.cn/mmbiz_png/FQd8gQcyN25BicBcb6EQVsWlJcZwBJyQzH3RRjsHl5TELibR1AiaVc8VdTpe4SuKiagibdqqjNV8R5iclic44AZnTjPzg/640?wx_fmt=png&tp=webp&wxfrom=5&wx_lazy=1&wx_co=1" alt= " Sample " width= " 600 " height= " 300 " >
30773073
30783074```python
30793075import numpy as np
@@ -3154,7 +3150,7 @@ plt.show()
31543150
31553151# ### 8 matplotlib柱状图
31563152
3157- 
3153+ < img src= " https://mmbiz.qpic.cn/mmbiz_png/FQd8gQcyN25BicBcb6EQVsWlJcZwBJyQzzBv3R8fHsVV6mEcV1KALF5u927OjdAwyhS4NUVHAAhlsBeC24zCricg/640?wx_fmt=png&tp=webp&wxfrom=5&wx_lazy=1&wx_co=1" alt= " Sample " width= " 600 " height= " 300 " >
31583154
31593155对应代码:
31603156
@@ -3213,7 +3209,8 @@ main()
32133209
32143210# ### 9 matplotlib等高线图
32153211
3216- 
3212+ 3213+ < img src=" https://mmbiz.qpic.cn/mmbiz_png/FQd8gQcyN25BicBcb6EQVsWlJcZwBJyQzMGnSAHhCHG1bNEWHh1VJcmYN8E1ZBjPaL5iclH2HrvyYmCuDeibbfV3A/640?wx_fmt=png&tp=webp&wxfrom=5&wx_lazy=1&wx_co=1" alt=" Sample" width=" 600" height=" 300" >
32173214
32183215对应代码:
32193216
@@ -3248,7 +3245,7 @@ plt.show()
32483245
32493246# ### 10 imshow图
32503247
3251- [ ](https:// camo.githubusercontent.com/ 7d73ce5053864430bc8b2d7191870889c848106b / 68747470733a2f2f6d6d62697a2e717069632e636e2f6d6d62697a5f706e672f46516438675163794e32354269634263623645515673576c4a635a77424a79517a6b4647626963707879753858727774784d73314e466177656d35696369627a6f4c716f356d7364353847343965477a6e3455304247554261772f3634303f77785f666d743d706e672674703d7765627026777866726f6d3d352677785f6c617a793d312677785f636f3d31 )
3248+ 
32523249
32533250对应代码:
32543251
@@ -3318,9 +3315,7 @@ print('ok')
33183315
33193316仪表盘中共展示三项,每项的比例为30 % ,70 % ,90 % ,如下图默认名称显示第一项:Python机器学习,完成比例为30 %
33203317
3321- 
3322- 3323- 3318+ < img src=" ./img/image-20191228194635902.png" alt=" Sample" width=" 600" height=" 450" >
33243319
33253320# ### 12 pyecharts漏斗图
33263321
@@ -3342,9 +3337,7 @@ funnel_base().render('./img/car_fnnel.html')
33423337
33433338以7 种车型及某个属性值绘制的漏斗图,属性值大越靠近漏斗的大端。
33443339
3345- 
3346- 3347- 3340+ < img src=" https://i.loli.net/2019/12/28/aCGfBp6YIvWqU84.png" alt=" Sample" width=" 600" height=" 300" >
33483341
33493342# ### 13 pyecharts日历图
33503343
@@ -3439,7 +3432,7 @@ liquid().render('./img/liquid.html')
34393432
34403433水球图的取值`[0.67 , 0.30 , 0.15 ]` 表示下图中的`三个波浪线` ,一般代表三个百分比:
34413434
3442- 
3435+ < img src= " ./img/liquid.gif" alt= " Sample " width= " 600 " height= " 450 " >
34433436
34443437# ### 16 pyecharts饼图
34453438
@@ -3460,6 +3453,8 @@ def pie_base() -> Pie:
34603453
34613454pie_base().render(' ./img/pie_pyecharts.html' )
34623455```
3456+ < img src=" ./img/20191229105841.png" alt=" Sample" width=" 600" height=" 350" >
3457+ 34633458
34643459# ### 17 pyecharts极坐标图
34653460
@@ -3482,7 +3477,8 @@ polar_scatter0().render('./img/polar.html')
34823477```
34833478
34843479极坐标表示为`(夹角,半径)` ,如(6 ,94 )表示夹角为6 ,半径94 的点:
3485- 
3480+ 3481+ < img src=" https://i.loli.net/2019/12/28/QxVOFuDB5y6wgpJ.png" alt=" Sample" width=" 600" height=" 500" >
34863482
34873483# ### 18 pyecharts词云图
34883484
@@ -3514,7 +3510,8 @@ wordcloud().render('./img/wordcloud.html')
35143510
35153511`(" C" ,65 )` 表示在本次统计中C语言出现65 次
35163512
3517- 
3513+ 3514+ < img src=" https://i.loli.net/2019/12/28/nSs8MY9Dc4I1egk.png" alt=" Sample" width=" 600" height=" 300" >
35183515
35193516# ### 19 pyecharts系列柱状图
35203517
@@ -3536,9 +3533,7 @@ def bar_series() -> Bar:
35363533bar_series().render(' ./img/bar_series.html' )
35373534```
35383535
3539- 
3540- 3541- 3536+ < img src=" https://i.loli.net/2019/12/28/egamLZw2oMHA19T.png" alt=" Sample" width=" 600" height=" 300" >
35423537
35433538# ### 20 pyecharts热力图
35443539
@@ -3568,9 +3563,8 @@ heatmap_car().render('./img/heatmap_pyecharts.html')
35683563
35693564热力图描述的实际是三维关系,x轴表示车型,y轴表示国家,每个色块的颜色值代表销量,颜色刻度尺显示在左下角,颜色越红表示销量越大。
35703565
3571- 
3572- 35733566
3567+ < img src=" ./img/image-20191229101724665.png" alt=" Sample" width=" 600" height=" 300" >
35743568
35753569# ## 七、Python实战
35763570
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