Python 使用 Ipywidgets 按索引的 DataFrame 交互式绘图

• seaborn.regplot适用于文档中指定的长格式数据.
• 回归图必须具有x轴和y轴的数值
• 安装说明见Jupyter Widgets
• Referenced:
  • Convert categorical data in pandas dataframe
  • How to make an interactive bar plot with seaborn and ipywidgets
• Tested in 100, 101, 102, 103, 104, 105, 106, 107

import ipywidgets as widgets
from ipywidgets import interact  
import pandas as pd
import numpy as np
import seaborn as sns

# create wide dataframe
df = pd.DataFrame(np.random.rand(6, 4),
                  index=['Nr. 1', 'Nr. 2', 'Nr. 3', 'Nr. 4', 'Nr. 5', 'Nr. 6'],
                  columns=['A', 'B', 'C', 'D'])

# convert the dataframe to long form
df = df.reset_index().melt(id_vars='index')

# convert the categorical value to a number with cat.codes or factorize
df['fac'], cats = df.variable.factorize() 
# df['fac'] = df.variable.astype('category').cat.codes
# cats = df.variable.unique()

# display(df.head())
   index variable     value  fac
0  Nr. 1        A  0.700304    0
1  Nr. 2        A  0.375954    0
2  Nr. 3        A  0.168559    0
3  Nr. 4        A  0.962506    0
4  Nr. 5        A  0.503662    0

交互式绘图

# get the unique values from the column used to select the data
idx = df['index'].unique()
@interact(Idx = idx)
def f(Idx):
    # select the relevant data
    data = df[df['index'].eq(Idx)]
    # plot
    ax = sns.regplot(data=data, x='fac', y='value')
    # set the x-ticks and labels
    ax.set_xticks(df.fac.unique(), cats)
    return ax