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用 Python 绘制几张有趣的可视化图表

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用 Python 绘制几张有趣的可视化图表

作者：俊欣 2022-08-23 12:32:37
今天小编就来为大家介绍两个用于绘制流程图的模块，我们先来看第一个。
9531b7f779a57458ee2810a0c5ba58a5889d4a.jpg

流程图存在于我们生活的方方面面，对于我们追踪项目的进展，做出各种事情的决策都有着巨大的帮助，而对于万能的Python而言呢，绘制流程图也是十分轻松的，今天小编就来为大家介绍两个用于绘制流程图的模块，我们先来看第一个。

SchemDraw

那么在SchemDraw模块当中呢，有六个元素用来代表流程图的主要节点的，椭圆形代表的是决策的开始和结束，代码如下：

import schemdraw
from schemdraw.flow import *
with schemdraw.Drawing() as d:
   d += Start().label("Start")

output

e1a83d810285d936d37751a02f9741e37d3345.jpg

箭头表示的是决策的走向，用来连接各个节点的，代码如下：

with schemdraw.Drawing() as d:
   d += Arrow(w = 5).right().label("Connector")

output

f654178832286b9c1035021687f26e778d444b.jpg

平行四边形代表的是你所要去处理和解决的问题，而长方形所代表的是你所要为此做出的努力或者说是过程，代码如下：

with schemdraw.Drawing() as d:
   d += Data(w = 5).label("What's the problem")

output

23c6b7a21f4b7b28fab99872c9a7444ce52799.jpg
with schemdraw.Drawing() as d:
   d += Process(w = 5).label("Processing")

output

d5d048871753ab56c90200c80ce18d259d0b79.jpg

而菱形代表的则是决策的具体情况，代码如下：

with schemdraw.Drawing() as d:
   d += Decision(w = 5).label("Decisions")

output

84197ce760486b033ae243719508210f25d5d5.jpg

我们来绘制一个简单的流程图，假如周末的时候我们想着要不要出去露营(Camping)，那既然要去露营的话，我们肯定是需要查看一下天气，看一下是否是晴天(Sunny)，如果是下雨天(Rainy)的话，就不去，按照这种逻辑，我们来绘制一下流程图，代码如下：

import schemdraw
from schemdraw.flow import *
with schemdraw.Drawing() as d:
   d+= Start().label("Start")
   d+= Arrow().down(d.unit/2)
   # 具体是啥问题嘞
   d+= Data(w = 4).label("Go camping or not")
   d+= Arrow().down(d.unit/2)
   # 第一步 查看天气
   d+= Box(w = 4).label("Check weather first")
   d+= Arrow().down(d.unit/2)
   # 是否是晴天
   d+= (decision := Decision(w = 5, h= 5,
                      S = "True",
                       E = "False").label("See if it's sunny"))
   # 如果是真的话
   d+= Arrow().length(d.unit/2)
   d+= (true := Box(w = 5).label("Sunny, go camping"))
   d+= Arrow().length(d.unit/2)
   # 结束
   d+= (end := Ellipse().label("End"))
   # 如果不是晴天的话
   d+= Arrow().right(d.unit).at(decision.E)
   # 那如果是下雨天的话，就不能去露营咯
   d+= (false := Box(w = 5).label("Rainy, stay at home"))
   # 决策的走向
   d+= Arrow().down(d.unit*2.5).at(false.S)
   # 决策的走向
   d+= Arrow().left(d.unit*2.15)
   d.save("palindrome flowchart.jpeg", dpi = 300)

output

d7a4c851062350df259056c3b722e11827a9f4.jpg

Networkx

Networkx模块用来创建和处理复杂的图网络结构，生成多种随机网络和经典网络，分析网络结构和建立网络模型，例如在绘制人脉关系网的案例当中就可以用到networkx模块，

而例如一个公司的组织架构图，也可以用到该模块，来简单直观的绘制公司的整体架构，代码如下:

import networkx as nx
import matplotlib.pyplot as plt
import numpy as np
G = nx.DiGraph()
nodes = np.arange(0, 8).tolist()
G.add_nodes_from(nodes)
# 节点连接的信息，哪些节点的是相连接的
G.add_edges_from([(0,1), (0,2),
(1,3), (1, 4),
(2, 5), (2, 6), (2,7)])
# 节点的位置
pos = {0:(10, 10),
1:(7.5, 7.5), 2:(12.5, 7.5),
3:(6, 6), 4:(9, 6),
5:(11, 6), 6:(14, 6), 7:(17, 6)}
# 节点的标记
labels = {0:"CEO",  
         1: "Team A Lead",
         2: "Team B Lead",
         3: "Staff A",
         4: "Staff B",
         5: "Staff C",
         6: "Staff D",
         7: "Staff E"}
nx.draw_networkx(G, pos = pos, labels = labels, arrows = True,
                node_shape = "s", node_color = "white")
plt.title("Company Structure")
plt.show()

output

c405c8128bca3bd8ec262314fff11bf6f48a44.jpg

看到这里，大家可能会觉得会指出来的结果有点简单，想要添加上去些许颜色，代码如下:

nx.draw_networkx(G, pos = pos, labels = labels,  
                bbox = dict(facecolor = "skyblue",
                boxstyle = "round", ec = "silver", pad = 0.3),
                edge_color = "gray"
               )
plt.title("Company Structure")
plt.show()

output

42db07123db18344cc93248fc11f254ae3a954.jpg
责任编辑：庞桂玉 来源： AI科技大本营

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