首页 > 编程语言 > 详细

Python数据可视化:一张很漂亮的商业图

时间:2020-12-25 21:27:06      阅读:47      评论:0      收藏:0      [点我收藏+]

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


 技术分享图片

 

 

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↓

技术分享图片

 

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(rE:\Python\Seaborn\Others)
mydata = pd.read_excel(不规则条形图数据.xlsx)

 

技术分享图片

 

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(flogo/{mydata.at[row, "Tools"]}.png)
    except FileNotFoundError:
        logo = plt.imread(flogo/{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(fflag/{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(flogo/{mydata.at[row, "Tools"]}.png)
    except FileNotFoundError:
        logo = plt.imread(flogo/{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(fflag/{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)

 

技术分享图片

 

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。

Python数据可视化:一张很漂亮的商业图

原文:https://www.cnblogs.com/hhh188764/p/14190477.html

(0)
(0)
   
举报
评论 一句话评论(0
关于我们 - 联系我们 - 留言反馈 - 联系我们:wmxa8@hotmail.com
© 2014 bubuko.com 版权所有
打开技术之扣,分享程序人生!