Pythonmatplotlib数据可视化：商业图表条形图

Z时代
2024-01-10
分类：综合

python

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以下文章来源于DataCharm，作者宁海涛

转载地址

https://www.zhihu.com/people/qi-shi-huan-hao-la-14/posts

绘制图标介绍

这篇推文是关于中美贸易的文章配图(具体我们这里我们不多做介绍，我们只关注配图的美观设计)，文章的插图如下：

配图是真的没话说，特别是配色(这种配色我后面会做一个Excel的配图颜色系会比这个多几个色系。大家如果需求多，我会分享出来的哦)

Python matplotlib

绘图数据

这里的数据处理步骤暂且不过多介绍，绘图数据如下

可视化

我们直接上代码，大家不会的可以详细看代码中的注释：

china_color = ["#3D71A0","#B70050","#FD9717","#B6CBDF"]
china_text = ["Aluminum waste and scrap","Pork","Fruits and nuts","Other"]
us_color = ["#3D71A0","#B70050","#FD9717","#B6CBDF","#3DAE5E","#133831"]
us_list = ["64%", "12%", "10%", "8%", "6%", ""]
us_text = ["Aluminum","Long","Pipe/tube","Stainless","Flat",""]
barWidth = .6
lefts_china = 0
lefts_us = 0
fig,ax = plt.subplots(figsize=(8,4.5),dpi=200)
for bars, col,text,text2 in zip(china["2017 exports, in actual dollars"], china_color,china["percent%"],china_text):
    ax.barh(1, bars, left=lefts_china, color=col, height=barWidth,align="center")
    lefts_china += bars
#大家注意这里：可以详细看一下
if lefts_china == china["2017 exports, in actual dollars"][0]:
        ax.text(bars/2,1,text,color="k",fontweight="extra bold",size=13,ha="center",va="center")
        ax.text(bars/2,1.4,text2,color="k",fontweight="light",size=8,ha="center",va="center")
else:
        ax.text(lefts_china-bars/2,1,text,color="k",fontweight="extra bold",size=13,ha="center",va="center")
        ax.text(lefts_china-bars/2,1.4,text2,color="k",fontweight="light",size=8,ha="center",va="center")
#添加暗黑色柱形图
ax.barh(.6,china["2017 exports, in actual dollars"].sum(),color="#172A39",height=.35,zorder=0)
for bars, col,text,text2 in zip(us["2017 imports, in actual dollars2"], us_color,us_list,us_text):
    ax.barh(3, bars, left=lefts_us, color=col, height=barWidth,align="center")
    lefts_us += bars
if lefts_us == us["2017 imports, in actual dollars2"][0]:
        ax.text(bars/2,3,text,color="k",fontweight="extra bold",size=13,ha="center",va="center")
        ax.text(bars/2,3.4,text2,color="k",fontweight="light",size=8,ha="center",va="center")
else:
        ax.text(lefts_us-bars/2,3,text,color="k",fontweight="extra bold",size=13,ha="center",va="center")
        ax.text(lefts_us-bars/2,3.4,text2,color="k",fontweight="light",size=8,ha="center",va="center")
ax.barh(2.6,us["2017 imports, in actual dollars2"].sum(),color="#172A39",height=.35,zorder=0)    
#定制化设置
ax.axis("off")
ax.axvline(x=0,ymin=.05,color="k",lw=.8)
ax.set_ylim(bottom=0,top=4)
#添加文本信息
ax.text(.02,.95,"Chinese exports covered by US Section 232 tariffs",
       transform = ax.transAxes,color="k",ha="left",va="center",size=9,fontweight="semibold")
ax.text(.3,.64,"$2.8 BILLION EXPORT VALUE,2017",
       transform = ax.transAxes,color="white",ha="left",va="center",size=8.5,fontweight="semibold")
#添加文本信息
ax.text(.02,.45,"US exports covered by Chinese retaliatory tariffs for US Section 232 tariffs",
       transform = ax.transAxes,color="k",ha="left",va="center",size=9,fontweight="semibold")
ax.text(.2,.14,"$2.4 BILLION EXPORT VALUE,2017",
       transform = ax.transAxes,color="white",ha="left",va="center",size=8.5,fontweight="semibold")
#再单独添加 semi-finished 描述部分
ax.text(us["2017 imports, in actual dollars2"].sum(),3,"<1%",ha="left",va="center",size=13,
       fontweight="extra bold")
ax.text(us["2017 imports, in actual dollars2"].sum(),3.4,"Semi-finished",ha="left",va="center",size=8,
       fontweight="light")
#添加小横线
ax.plot([us["2017 imports, in actual dollars2"][:1].sum(),us["2017 imports, in actual dollars2"].sum()],[3.55,3.55],
       color="k",lw=.6)
text_loc = us["2017 imports, in actual dollars2"][:3].sum()
ax.text(text_loc,3.64,"STEEL PRODUCTS",ha="center",va="center")
#添加刻度文本
ax.text(-.02,.2,"CHINESE
ACTION IN
EFFECT
APRIL 2",ha="right",va="center",fontweight="medium",size=11,
       transform = ax.transAxes)
ax.text(-.02,.7,"US ACTION
INEFFECT
MARCH 23",ha="right",va="center",fontweight="medium",size=11,
       transform = ax.transAxes)
#添加标题
ax.text(-.1,1.15,"How Is China Retaliating for US Nation
Security Tariffs on Steel and Aluminum?",
       transform = ax.transAxes,color="k",ha="left",va="center",size=20,fontweight="extra bold")
ax.text(.91,.05,"
Visualization by DataCharm",transform = ax.transAxes,
        ha="center", va="center",fontsize = 7,color="black")
plt.savefig(r"F:DataCharm商业艺术图表仿制PIEE_ChartsChina USPIEE_china_us02.png",width=8,height=4,
            dpi=900,bbox_inches="tight",facecolor="white")
#ax.set_axisbelow(True)
plt.show()

最终我们绘制的效果如下：

知识点

横向堆积柱形图绘制这里举一个小栗子大家看下就可以：

from matplotlib import pyplot as plt
import numpy as np
N = 5
r = range(N)
bars1 = np.random.binomial(20, .7, N)
bars2 = np.random.binomial(20, .5, N)
bars3 = np.random.binomial(20, .4, N)
colors = ["#7f6d5f", "#557f2d", "#2d7f5e"]
labels = ["Lasso", "Random Forest", "Decision Tree"]
barWidth = 1
lefts = 0
fig,ax = plt.subplots(figsize=(8,4.5),dpi=200)
for bars, col, label in zip([bars1, bars2, bars3], colors, labels):
    plt.barh(r, bars, left=lefts, color=col, edgecolor="white", height=barWidth, label=label)
    lefts += bars
plt.legend()
plt.ylim(-0.5, len(bars) - 0.5)
ax.text(.91,-.08,"
Visualization by DataCharm",transform = ax.transAxes,
        ha="center", va="center",fontsize = 7,color="black")
plt.savefig(r"F:DataCharm商业艺术图表仿制PIEE_ChartsChina USPIEE_china_example.png",width=8,height=4,
            dpi=900,bbox_inches="tight")
plt.show()

结果如下：

文本自动添加虽然代码中有明确解释，但这里我们还是单独进行展示：

for bars, col,text,text2 in zip(us["2017 imports, in actual dollars2"], us_color,us_list,us_text):
    ax.barh(3, bars, left=lefts_us, color=col, height=barWidth,align="center")
    lefts_us += bars
if lefts_us == us["2017 imports, in actual dollars2"][0]:
        ax.text(bars/2,3,text,color="k",fontweight="extra bold",size=13,ha="center",va="center")
        ax.text(bars/2,3.4,text2,color="k",fontweight="light",size=8,ha="center",va="center")
else:
        ax.text(lefts_us-bars/2,3,text,color="k",fontweight="extra bold",size=13,ha="center",va="center")
        ax.text(lefts_us-bars/2,3.4,text2,color="k",fontweight="light",size=8,ha="center",va="center")