python - 散景中的交互式饼图；反应性地交换变量以绘制

Question

我对 Python 和 Bokeh 还很陌生，所以我仍在尝试掌握如何以交互方式交换变量以进行绘图。目前我正在尝试使用散景小部件创建饼图。

这是饼图的样子：-

from operator import index
from bokeh.models.widgets.markups import Div
import numpy as np
from numpy.lib import source
import pandas as pd
from bokeh.io import curdoc,show
from bokeh.layouts import column, row, gridplot
from bokeh.models import ColumnDataSource, Select, Slider, BoxSelectTool, LassoSelectTool, Tabs, Panel, LinearColorMapper, ColorBar, BasicTicker, PrintfTickFormatter, MultiSelect, DataTable, TableColumn
from bokeh.plotting import figure, curdoc
from bokeh.palettes import viridis, gray, cividis, Category20, Category20c
from bokeh.transform import factor_cmap,cumsum
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.metrics import classification_report, confusion_matrix, mean_squared_error, r2_score, recall_score, f1_score
from sklearn.preprocessing import StandardScaler, PolynomialFeatures
from sklearn.cluster import KMeans
from sklearn.svm import SVC
from sklearn.decomposition import PCA
from math import pi
from bokeh.transform import cumsum

np.random.seed(42)


print("step 1")
#define the categorical variable
category_a = ['A','B','C']
category_b = ['X','Y','Z']
print("step 2")
df_random = pd.DataFrame({
   'id': np.arange(0, 100),
   'date': pd.date_range(start='1/1/2021', periods=100, freq='D'),
   'month':np.random.randint(1, 12, 100),
   'sensor_1': np.random.uniform(0, 1,100),
   'sensor_2': np.random.uniform(10, 150, 100),
   'sensor_3': np.random.randint(0, 90, 100),
   'sensor_4': np.random.randint(0, 450, 100),
   'sensor_5': np.random.randint(0, 352, 100),
   'categorya': np.random.choice(category_a, 100, p=[0.2, 0.4, 0.4]),
   'categoryb': np.random.choice(category_b, 100, p=[0.6, 0.2, 0.2]),
})

column_choices = {
    "Sensor 1": "sensor_1",
    "Sensor 2": "sensor_2",
    "Sensor 3": "sensor_3",
    "Sensor 4": "sensor_4",
    "Sensor 5": "sensor_5"
}

column_choices_list = list(column_choices.values())

groupeddf = df_random.groupby('categorya')[column_choices_list].mean()
print(groupeddf)

groupeddf['angle'] = groupeddf['sensor_1']/groupeddf['sensor_1'].sum() * 2*pi
groupeddf['color'] = Category20c[len(groupeddf)]
source_pie = ColumnDataSource(data=groupeddf)

p_pie = figure(plot_height=350, title="Pie Chart", toolbar_location=None, tools="")

p_pie.wedge(x=0, y=1, radius=0.4,
        start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'),
        line_color="white", fill_color='color', legend='categorya', source=source_pie)



show(p_pie)

但是，我正在尝试在小部件中添加以更改df_random我绊倒的列：-

...

selecty_pie_var = Select(title="Select variable:", options=list(column_choices_list))

def callback(attr,old,new):
    df_platform['angle'] = df_platform[selecty_pie_var.value]/df_platform[selecty_pie_var.value].sum() * 2*pi
    df_platform['color'] = Category20c[len(df_platform)]
    source_pie.data = df_platform
    return source_pie

selecty_pie_var.js_on_change('value', callback)

layoutwithwidgets = row(selecty_pie_var,p_pie)

show(layoutwithwidgets)

我想，对于任何称职的 Python 用户来说，以上内容看起来都是一团糟。有人可以帮助我将小部件和饼图链接在一起，以便在我更改列时更新吗？例如，sensor_1现在正在绘制，但我希望能够将其更改为sensor_2、sensor_3等。

任何帮助是极大的赞赏 ：）

标签： pythonpandasbokeh