130 lines
3.0 KiB
Markdown
130 lines
3.0 KiB
Markdown
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# 数据可视化模板
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## 环境配置
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```python
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import matplotlib.pyplot as plt
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import seaborn as sns
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import plotly.express as px
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import plotly.graph_objects as go
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plt.rcParams['font.sans-serif'] = ['SimHei', 'Arial Unicode MS']
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plt.rcParams['axes.unicode_minus'] = False
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sns.set_style("whitegrid")
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```
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## 分布图
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```python
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def plot_dist(df, col):
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fig, ax = plt.subplots(1, 2, figsize=(12, 4))
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sns.histplot(df[col], kde=True, ax=ax[0])
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ax[0].axvline(df[col].mean(), c='r', ls='--', label=f'均值:{df[col].mean():.1f}')
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ax[0].legend()
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sns.boxplot(x=df[col], ax=ax[1])
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plt.tight_layout()
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return fig
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```
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## 对比图
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```python
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def plot_compare(df, cat, val):
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order = df.groupby(cat)[val].mean().sort_values(ascending=False).index
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fig, ax = plt.subplots(figsize=(10, 5))
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sns.barplot(data=df, x=cat, y=val, order=order, ax=ax)
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ax.tick_params(axis='x', rotation=45)
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for p in ax.patches:
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ax.annotate(f'{p.get_height():.1f}',
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(p.get_x() + p.get_width()/2, p.get_height()),
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ha='center', va='bottom')
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plt.tight_layout()
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return fig
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```
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## 时间序列
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```python
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def plot_trend(df, date_col, val_col):
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fig = px.line(df, x=date_col, y=val_col)
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# 添加移动平均
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df['MA7'] = df[val_col].rolling(7).mean()
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fig.add_scatter(x=df[date_col], y=df['MA7'], name='7日均线', line=dict(dash='dash'))
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fig.update_layout(hovermode='x unified')
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return fig
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```
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## 热力图
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```python
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def plot_heatmap(df):
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corr = df.select_dtypes(include=[np.number]).corr()
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plt.figure(figsize=(10, 8))
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mask = np.triu(np.ones_like(corr, dtype=bool))
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sns.heatmap(corr, mask=mask, annot=True, fmt='.2f', cmap='RdBu_r', center=0)
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plt.tight_layout()
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return plt.gcf()
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```
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## 漏斗图
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```python
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def plot_funnel(stages, values):
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fig = go.Figure(go.Funnel(
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y=stages, x=values,
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textposition="inside",
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textinfo="value+percent initial"
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))
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return fig
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# 示例
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plot_funnel(['访问','浏览','加购','支付'], [10000, 5000, 1000, 500])
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```
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## 饼图
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```python
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def plot_pie(series, title=''):
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fig, ax = plt.subplots()
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series.plot(kind='pie', autopct='%1.1f%%', ax=ax)
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ax.set_ylabel('')
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ax.set_title(title)
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return fig
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```
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## 组合仪表板
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```python
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def plot_dashboard(df, num_col, cat_col, date_col):
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fig = plt.figure(figsize=(14, 10))
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ax1 = fig.add_subplot(2, 2, 1)
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sns.histplot(df[num_col], kde=True, ax=ax1)
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ax2 = fig.add_subplot(2, 2, 2)
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df.groupby(cat_col)[num_col].mean().plot(kind='bar', ax=ax2)
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ax3 = fig.add_subplot(2, 2, 3)
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df.groupby(date_col)[num_col].sum().plot(ax=ax3)
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ax4 = fig.add_subplot(2, 2, 4)
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df[cat_col].value_counts().plot(kind='pie', ax=ax4, autopct='%1.1f%%')
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plt.tight_layout()
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return fig
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```
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## 保存图表
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```python
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plt.savefig('chart.png', dpi=300, bbox_inches='tight')
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fig.write_html('chart.html') # Plotly
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```
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