这篇文章主要介绍了怎么用Python绘制有趣的可视化图表的相关知识,内容详细易懂,操作简单快捷,具有一定借鉴价值,相信大家阅读完这篇怎么用Python绘制有趣的可视化图表文章都会有所收获,下面我们一起来看看吧。
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")
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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")
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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")
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with schemdraw.Drawing() as d: d += Process(w = 5).label("Processing")
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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")
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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)
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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()
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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()
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