Python数据可视化：一张很漂亮的商业图[Python基础]

• Z时代
• 2024-01-10
• 分类：综合

前言

本文的文字及图片来源于网络,仅供学习、交流使用,不具有任何商业用途,版权归原作者所有,如有问题请及时联系我们以作处理

以下文章来源于Lin王发林，作者：WangFalin

Python数据分析：零基础入门教学（讲解+实战）

https://www.bilibili.com/video/BV18f4y1i7q9/

前言

上个月的时候看到一张很漂亮的商业图，很喜欢，然后就忘了。刚好前两天看到一篇文章来临摹此图，于是学习了一下其思路和代码，然后拿来实践了一下，效果还可以，特此纪念，以后应该还有用得上的地方。那商业图我就不放了，然后把我的图放在这里↓

数据准备

可以看到，图中主要有4列数据组成，分别是公司logo、公司名称、所属工具和市值增长值。于是先准备数据，就是我常用的软件工具列举了一下，共20个，然后数值是使用率吧，Type是用来标记颜色的，最后一列分类是次软件的主要作用，&符号连接两个或多个主要用途。如下↓

import matplotlib.pyplot as plt
import pandas as pd
import os
os.chdir(r"E:PythonSeabornOthers")
mydata = pd.read_excel("不规则条形图数据.xlsx")

设置中文字体正常显示

mycolor = {
"Green": "#8ABD25",
"Pink": "#F57FEF",
"Yellow": "#EBE639",
"Red": "#EB3939",
"Orange": "#EBAF39",
"Blue": "#39A4EB",
"Black": "#4D6E83",
"Gray": "#A3A4A5",
}

自定义颜色，后面直接根据Type类型进行调用就行了

logosize = 0.037 #软件图标大小
right_height = 20 #右边矩形填充的高度，建议和数据行数一样多
ratio = 0.05 #这个系数会影响右边矩形整体的偏移情况，建议值是（1/行数）
ratio2 = 0.8 #这个系数影响右边矩形上面的下移程度
ratio3 = 0.005 #分类图标的水平位置
ratio4 = 0.01 #数影响右边矩形下面的上移程度
ratio5 = 0.01 #影响软件文字的上下水平

一些影响的参数，因为涉及多处，所以提出来统一修改了，还有一些参数需要里面改。

def create_fill_area(row):
# 初始化包围填充区域的上下线条y坐标
    line1, line2 = [1 - ratio*row, 1 - ratio*row], [1- ratio*(row+1), 1- ratio*(row+1)]
# 追加阴影段y坐标
    line1.append(ratio4 + (right_height - row) * (ratio2 - ratio4) / right_height)
    line2.append(ratio4 + (right_height - row - 1) * (ratio2 - ratio4) / right_height)
# 追加最后一段平行段y坐标
    line1.append(ratio4 + (right_height - row) * (ratio2 - ratio4) / right_height)
    line2.append(ratio4 + (right_height - row - 1) * (ratio2 - ratio4) / right_height)
return line1, line2

为了创建出不同条带，配合matplotlib中的fill_between。为了处理好左侧与右侧的竖直方向等分区域，我们可以在对原数据每一行循环的过程中，自定义下列函数来计算区域范围↓

fig, ax = plt.subplots(figsize=(4.8, 6))
ax.set_xlim(0, 1.11)
ax.set_ylim(0, 1)
for row in range(mydata.shape[0]):
# 定义区域填充对应的x坐标
    x = [0, 0.15, 0.215, 0.6+mydata.at[row, "Values"] / 1000]
# 生成区域填充对应的y坐标
    line1, line2 = create_fill_area(row)
# 对指定区域进行填充
    ax.fill_between(x,
                    line1,
                    line2,
                    color=mycolor[mydata.at[row, "Type"]],
                    edgecolor="none")
# 从logo文件夹下读取对应logo图片
try:
        logo = plt.imread(f"logo/{mydata.at[row, "Tools"]}.png")
except FileNotFoundError:
        logo = plt.imread(f"logo/{mydata.at[row, "Tools"]}.jpg")
# 插入软件logo
    ax_logo = ax.inset_axes((0.05, 1 - ratio*(row+1)+0.005, 0.08, logosize))
    ax_logo.imshow(logo)
    ax_logo.axis("off")
    ax_logo.set_facecolor(mycolor[mydata.at[row, "Type"]])
# 处理单个及多个功能情况下的绘制
for idx, Category in enumerate(mydata.at[row, "Category"].split("&")[::-1]):
# 读取对应功能图片
        flag = plt.imread(f"flag/{Category}.png")
# 插入功能子图
        ax_flag = ax.inset_axes((0.545-idx*0.06, 0.013+(right_height - row - 1)*((ratio2 - ratio3) / right_height), 0.1, 0.025))
        ax_flag.imshow(flag)
        ax_flag.axis("off")
        ax_flag.set_facecolor(mycolor[mydata.at[row, "Type"]])
# 绘制排名
    ax.text(0.025, (1 - ratio*row + 1 - ratio*(row+1)) / 2, str(row+1), 
            ha="center", va="center",
            fontsize=9, color="black")
# 绘制软件名称
    ax.text(0.215+ratio5, 0.5 * (ratio5 + (right_height - row - 1) * (ratio2 - ratio5) / right_height + ratio5 + (right_height - row) * (ratio2 - ratio5) / right_height), 
            mydata.at[row, "Tools"], 
            ha="left", va="center",
            fontsize=9, color="#FFFFFF", 
            weight="bold")
# 处理第一名文字在填充区域内部，其余文字在填充区域外的情况
if mydata.at[row, "Tools"] == "Exce1l":
        ax.text(1, 0.5 * (ratio3 + (right_height - row) * (ratio2 - ratio3) / right_height 
+ ratio3 + (right_height - row - 1) * (ratio2 - ratio3) / right_height)-0.0025,
""+str(mydata.at[row, "Values"]/4)+"%",
                color="white",
                fontsize=10,
                ha="right",
                va="center",
                weight="bold")
else:
# 配合归一化对字体进行大小映射
        ax.text(0.6+mydata.at[row, "Values"] / 1000 + ratio3, 
0.5 * (ratio3 + (right_height - row) * (ratio2 - ratio3) / right_height + ratio3 + (right_height - row - 1) * (ratio2 - ratio3) / right_height)-0.0025,
""+str(int(mydata.at[row, "Values"]/4))+"%",
                color=mycolor[mydata.at[row, "Type"]],
                fontsize=7+((mydata.at[row, "Values"] - mydata["Values"].min()) 
/ (mydata["Values"].max() - mydata["Values"].min())) * 5,
                ha="left",
                va="center",
                weight="bold")
# 对指定区域进行带透明度的黑色蒙版，以达到阴影效果
ax.fill_between([0.15, 0.215],
                [0, ratio4],
                [1, ratio2],
                color="black",
                alpha=0.2, # 设置透明度
                edgecolor="none")
# 补充其余文字标注
ax.text(0.215+ratio5, 0.805, "软件名称", 
        color="#565555", fontsize=6,
        ha="left")
ax.text(0.67, 0.805, "软件类型", 
        color="#565555", fontsize=6,
        ha="center")
#补充上方数值刻度
ax.text(0.6, 0.825, "0", 
        color="#a9a8a8", fontsize=8,
        ha="center")    
for i in range(1, 5):
print(i)
    ax.text(0.6+0.1*i, 0.825, f"{i*25}%", 
            color="#a9a8a8", fontsize=9,
            ha="center")   
    ax.vlines(0.6+0.1*i, 0.01, 0.82, 
              color="#dcdcdb", linewidth=0.2)
ax.set_xticks([])
ax.set_yticks([])
ax.spines["left"].set_color("none")
ax.spines["right"].set_color("none")
ax.spines["top"].set_color("none")
ax.spines["bottom"].set_color("none")
# 补充下排图例
ax_bar1 = ax.inset_axes((0.215, 0.88, 0.57, 0.02), transform=ax.transAxes)
ax_bar1.set_xlim(-0.45, 3.6)
ax_bar1.bar(range(4), height=1, width=0.8, 
            color=["#8ABD25", "#F57FEF", "#EBE639", "#EB3939"])
ax_bar1.set_xticks(range(4))
ax_bar1.set_xticklabels(["绿色系", "紫色系", "黄色系", "红色系"],
                        fontsize=7, color="#4f4e4e", weight="bold")
ax_bar1.set_yticks([])
ax_bar1.spines["left"].set_color("none")
ax_bar1.spines["right"].set_color("none")
ax_bar1.spines["top"].set_color("none")
ax_bar1.spines["bottom"].set_color("none")
ax_bar1.tick_params(color="none", pad=-2)
ax_bar1.set_facecolor("#f8f8f8")
# 补充上排图例
ax_bar2 = ax.inset_axes((0.215, 0.98, 0.57, 0.02), transform=ax.transAxes)
ax_bar2.set_xlim(-0.45, 3.6)
ax_bar2.bar(range(4), height=1, width=0.8, 
            color=["#EBAF39", "#39A4EB", "#4D6E83", "#A3A4A5"])
ax_bar2.set_xticks(range(4))
ax_bar2.set_xticklabels(["橙色系", "蓝色系", "黑色系", "灰色系"],
                        fontsize=7, color="#4f4e4e", weight="bold")
ax_bar2.set_yticks([])
ax_bar2.spines["left"].set_color("none")
ax_bar2.spines["right"].set_color("none")
ax_bar2.spines["top"].set_color("none")
ax_bar2.spines["bottom"].set_color("none")
ax_bar2.tick_params(color="none", pad=-2)
ax_bar2.set_facecolor("#f8f8f8")
ax.set_facecolor("#f8f8f8")
fig.set_facecolor("#f8f8f8")
fig.savefig("输出结果.png", dpi=800, bbox_inches="tight")

下面是绘图代码，都有注释说明，读一遍应该都能读懂，只是一些巧妙计算的逻辑需要理一下。这里没有绘制标题，可以借助PS添加一个完美的标题。

fig, ax = plt.subplots(figsize=(4.8, 6))
ax.set_xlim(0, 1.11)
ax.set_ylim(0, 1)
for row in range(mydata.shape[0]):
# 定义区域填充对应的x坐标
    x = [0, 0.15, 0.215, 0.6+mydata.at[row, "Values"] / 1000]
# 生成区域填充对应的y坐标
    line1, line2 = create_fill_area(row)
# 对指定区域进行填充
    ax.fill_between(x,
                    line1,
                    line2,
                    color=mycolor[mydata.at[row, "Type"]],
                    edgecolor="none")
# 从logo文件夹下读取对应logo图片
try:
        logo = plt.imread(f"logo/{mydata.at[row, "Tools"]}.png")
except FileNotFoundError:
        logo = plt.imread(f"logo/{mydata.at[row, "Tools"]}.jpg")
# 插入软件logo
    ax_logo = ax.inset_axes((0.05, 1 - ratio*(row+1)+0.005, 0.08, logosize))
    ax_logo.imshow(logo)
    ax_logo.axis("off")
    ax_logo.set_facecolor(mycolor[mydata.at[row, "Type"]])
# 处理单个及多个功能情况下的绘制
for idx, Category in enumerate(mydata.at[row, "Category"].split("&")[::-1]):
# 读取对应功能图片
        flag = plt.imread(f"flag/{Category}.png")
# 插入功能子图
        ax_flag = ax.inset_axes((0.545-idx*0.06, 0.013+(right_height - row - 1)*((ratio2 - ratio3) / right_height), 0.1, 0.025))
        ax_flag.imshow(flag)
        ax_flag.axis("off")
        ax_flag.set_facecolor(mycolor[mydata.at[row, "Type"]])
# 绘制排名
    ax.text(0.025, (1 - ratio*row + 1 - ratio*(row+1)) / 2, str(row+1), 
            ha="center", va="center",
            fontsize=9, color="black")
# 绘制软件名称
    ax.text(0.215+ratio5, 0.5 * (ratio5 + (right_height - row - 1) * (ratio2 - ratio5) / right_height + ratio5 + (right_height - row) * (ratio2 - ratio5) / right_height), 
            mydata.at[row, "Tools"], 
            ha="left", va="center",
            fontsize=9, color="#FFFFFF", 
            weight="bold")
# 处理第一名文字在填充区域内部，其余文字在填充区域外的情况
if mydata.at[row, "Tools"] == "Exce1l":
        ax.text(1, 0.5 * (ratio3 + (right_height - row) * (ratio2 - ratio3) / right_height 
+ ratio3 + (right_height - row - 1) * (ratio2 - ratio3) / right_height)-0.0025,
""+str(mydata.at[row, "Values"]/4)+"%",
                color="white",
                fontsize=10,
                ha="right",
                va="center",
                weight="bold")
else:
# 配合归一化对字体进行大小映射
        ax.text(0.6+mydata.at[row, "Values"] / 1000 + ratio3, 
0.5 * (ratio3 + (right_height - row) * (ratio2 - ratio3) / right_height + ratio3 + (right_height - row - 1) * (ratio2 - ratio3) / right_height)-0.0025,
""+str(int(mydata.at[row, "Values"]/4))+"%",
                color=mycolor[mydata.at[row, "Type"]],
                fontsize=7+((mydata.at[row, "Values"] - mydata["Values"].min()) 
/ (mydata["Values"].max() - mydata["Values"].min())) * 5,
                ha="left",
                va="center",
                weight="bold")
# 对指定区域进行带透明度的黑色蒙版，以达到阴影效果
ax.fill_between([0.15, 0.215],
                [0, ratio4],
                [1, ratio2],
                color="black",
                alpha=0.2, # 设置透明度
                edgecolor="none")
# 补充其余文字标注
ax.text(0.215+ratio5, 0.805, "软件名称", 
        color="#565555", fontsize=6,
        ha="left")
ax.text(0.67, 0.805, "软件类型", 
        color="#565555", fontsize=6,
        ha="center")
#补充上方数值刻度
ax.text(0.6, 0.825, "0", 
        color="#a9a8a8", fontsize=8,
        ha="center")    
for i in range(1, 5):
print(i)
    ax.text(0.6+0.1*i, 0.825, f"{i*25}%", 
            color="#a9a8a8", fontsize=9,
            ha="center")   
    ax.vlines(0.6+0.1*i, 0.01, 0.82, 
              color="#dcdcdb", linewidth=0.2)
ax.set_xticks([])
ax.set_yticks([])
ax.spines["left"].set_color("none")
ax.spines["right"].set_color("none")
ax.spines["top"].set_color("none")
ax.spines["bottom"].set_color("none")
# 补充下排图例
ax_bar1 = ax.inset_axes((0.215, 0.88, 0.57, 0.02), transform=ax.transAxes)
ax_bar1.set_xlim(-0.45, 3.6)
ax_bar1.bar(range(4), height=1, width=0.8, 
            color=["#8ABD25", "#F57FEF", "#EBE639", "#EB3939"])
ax_bar1.set_xticks(range(4))
ax_bar1.set_xticklabels(["绿色系", "紫色系", "黄色系", "红色系"],
                        fontsize=7, color="#4f4e4e", weight="bold")
ax_bar1.set_yticks([])
ax_bar1.spines["left"].set_color("none")
ax_bar1.spines["right"].set_color("none")
ax_bar1.spines["top"].set_color("none")
ax_bar1.spines["bottom"].set_color("none")
ax_bar1.tick_params(color="none", pad=-2)
ax_bar1.set_facecolor("#f8f8f8")
# 补充上排图例
ax_bar2 = ax.inset_axes((0.215, 0.98, 0.57, 0.02), transform=ax.transAxes)
ax_bar2.set_xlim(-0.45, 3.6)
ax_bar2.bar(range(4), height=1, width=0.8, 
            color=["#EBAF39", "#39A4EB", "#4D6E83", "#A3A4A5"])
ax_bar2.set_xticks(range(4))
ax_bar2.set_xticklabels(["橙色系", "蓝色系", "黑色系", "灰色系"],
                        fontsize=7, color="#4f4e4e", weight="bold")
ax_bar2.set_yticks([])
ax_bar2.spines["left"].set_color("none")
ax_bar2.spines["right"].set_color("none")
ax_bar2.spines["top"].set_color("none")
ax_bar2.spines["bottom"].set_color("none")
ax_bar2.tick_params(color="none", pad=-2)
ax_bar2.set_facecolor("#f8f8f8")
ax.set_facecolor("#f8f8f8")
fig.set_facecolor("#f8f8f8")
fig.savefig("输出结果.png", dpi=800, bbox_inches="tight")

这个颜色有点艳丽，可以调整一下颜色就行了，然后用PS加个标题，底部再加点看不懂的小文字显得高端，然后基本上就大功告成了。

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