使用 Ipywidgets 按索引交互式绘制 DataFrame

Question

我有两个数据框：

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

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

df2 = pd.DataFrame(np.array([[1, 2, 3, 4]]), columns=['a', 'b', 'c', 'd'])

我想制作一个交互式绘图，我可以通过 df 的索引下拉列表来选择 DataFrame 的行。

这是我的方法：

Index= df.index.tolist()
Nr = widgets.Dropdown(options=Nr, value=Nr[0], description='Number:', disabled=False)
button = widgets.Button(description='Plot', disabled = False, button_style='', tooltip = 'Plotting', icon='check')

out = widgets.Output(layout={'border': '1px solid black'})
box = widgets.VBox([Nr, button])
def on_button_clicked(b):
    with out:
         ax = sns.regplot(x=df_2[0], y=df.loc[[Nr]])
button.on_click(on_button_clicked, False)
display(box)

但是，我得到这个错误：'None of [Index([Dropdown(description='Nr:', index = 4, options=('Nr. 1', 'Nr. 2', 'Nr. 3', 'Nr. 4'), value = 'Nr. 1')], dtype = 'object', name='Nr')] are in the [index]'

我错过了什么？

Answer 1

seaborn.regplot 使用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
有关安装说明，请参阅 Jupyter Widgets
参考：
在 python 3.10、pandas 1.4.2、matplotlib 3.5.1、seaborn 0.11.2、notebook 6.4.8、jupyterlab 3.3.2、jupyterlab_widgets 1.0.0, ipywidgets 7.6.4

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

互动剧情

# 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

使用 Ipywidgets 按索引交互式绘制 DataFrame

Interactive Plot of DataFrame by index with Ipywidgets

python

pandas

seaborn

jupyter

ipywidgets

互动剧情