Python可视化绘图（一）

我就是我 2023-07-24 01:50 20阅读 0赞

## 数据读取 ##

import pandas as pd
    filename = r'C:\Users\Administrator\Desktop\data.csv'
    data = pd.read_csv(filename)

## 图形常用 ##

#### 添加图形标题 ####

plt.title('2017年万科与保利地产市值对比',color = colors1,fontsize = 18)  # 添加图形标题

#### 添加X轴标签 ####

plt.xlabel('月份') # 添加X轴标签

#### 添加纵轴标签 ####

plt.ylabel('市值(亿元)') # 添加纵轴标签

#### 将图形另外保存成文件输出 ####

plt.savefig('stock1.png',bbox_inches = 'tight',dpi = 300) # 将图形另外保存

#### 显示图例 ####

plt.legend() # 显示图例

## 绘制箱线图 ##

import seaborn as sns
    import matplotlib.pyplot as plt
    plt.rcParams['font.sans-serif'] = ['SimHei']    #定义使其正常显示中文字体黑体
    plt.rcParams['axes.unicode_minus'] = False      #用来正常显示表示负号
    import pandas as pd
    plt.rcParams['font.sans-serif'] = ['SimHei']
    fig=sns.catplot(x='质量等级', y='SO2', kind='box',data=data)
    print(fig)
    plt.title('SO2和质量等级的箱线图')
    fig.savefig('p4.png')

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3RhbmRlbGlu_size_16_color_FFFFFF_t_70]

## 绘制折线图 ##

import pandas as pd
    filename = r'C:\Users\Administrator\Desktop\data.csv'
    data = pd.read_csv(filename)
    data1=data.iloc[:,1]
    import matplotlib.pyplot as plt
    plt.style.use('ggplot')  # 设置绘图风格
    fig = plt.figure(figsize = (10,6))  # 设置图框的大小
    ax1 = fig.add_subplot(1,1,1)
    data1.plot()

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3RhbmRlbGlu_size_16_color_FFFFFF_t_70 1]

## 绘制带文字的X轴坐标折线图 ##

##### 调用安装包和数据读取
    import numpy as np
    import matplotlib.pyplot as plt
    import calendar
    import pandas as pd
    filename = r'C:\Users\Administrator\Desktop\data.csv'
    data = pd.read_csv(filename)
    ##### 数据设置
    data0=data.iloc[:,0] ##要添加X轴的文字列
    data1=data.iloc[:,1] ## 数值X轴列
    data2=data.iloc[:,2] ## 数值Y列
    ##### 图形显示
    plt.plot(data1,data2)  ## 绘制数值X列和数值Y列
    plt.xticks(data1, data0[1:77],color='blue',rotation=60)  #参数x空值X轴的间隔，第二个参数控制每个间隔显示的文本，后面两个参数控制标签的颜色和旋转角度
    plt.show()  ## 展示图形

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3RhbmRlbGlu_size_16_color_FFFFFF_t_70 2]

## 日期转换：日期数据转换为季度 ##

df['quarter'] = pd.PeriodIndex(df.date, freq='Q')

## 季节箱线图 ##

import seaborn as sns
    import matplotlib.pyplot as plt
    plt.rcParams['font.sans-serif'] = ['SimHei']    #定义使其正常显示中文字体黑体
    plt.rcParams['axes.unicode_minus'] = False      #用来正常显示表示负号
    import pandas as pd
    plt.rcParams['font.sans-serif'] = ['SimHei']
    fig=sns.catplot(x='季节', y='SO2', kind='box',data=data)
    print(fig)
    plt.title('SO2和季节的箱线图')

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3RhbmRlbGlu_size_16_color_FFFFFF_t_70 3]

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[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3RhbmRlbGlu_size_16_color_FFFFFF_t_70 1]: /images/20230528/294250f59c3d4bb8adcb3a13dca91b0b.png
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