Python数据可视化：一张很漂亮的商业图

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。