import numpy as np
import pandas as pd
from bokeh.plotting import figure, gridplot
from bokeh.io import output_file, show, curdoc
from bokeh.models.widgets import FileInput, DataTable, DateFormatter, TableColumn
from pybase64 import b64decode
from bokeh.models import ColumnDataSource
import io
# output to static HTML file
output_file("./OUTPUT/001_koreksi.html", title='Koreksi Gayaberat')
def upload_fit_data(attr, old, new):
print("fit data upload succeeded")
decoded = b64decode(new)
f = io.BytesIO(decoded)
new_df = pd.read_excel(f, sheet_name='data')
# print(new_df)
data = dict(utmx=new_df['UTM X'],
utmy=new_df['UTM Y'],
elev=new_df['Elevasi'],
lat=new_df['Latitude'],
lon=new_df['Longitude'],
ta=new_df['Tinggi Alat'],
N=new_df['N'],
E=new_df['E'],
S=new_df['S'],
W=new_df['W'],
time=new_df['Time'],
kt=new_df['Koreksi Tide'],
rdgrav=new_df['Bacaan'])
source = ColumnDataSource(data)
columns = [TableColumn(field="utmx", title="UTM X"), TableColumn(field="utmy", title="UTM Y"),
TableColumn(field="elev", title="Elevasi"), TableColumn(field="lat", title="Latitude"),
TableColumn(field="lon", title="Longitude"), TableColumn(field="ta", title="Tinggi Alat"),
TableColumn(field="N", title="North"), TableColumn(field="E", title="East"),
TableColumn(field="S", title="South"), TableColumn(field="W", title="West"),
TableColumn(field="time", title="Waktu Pengukuran"), TableColumn(field="kt", title="Koreksi tide"),
TableColumn(field="rdgrav", title="Bacaan Alat")]
data_table = DataTable(source=source, columns=columns, width=500, height=300)
global data_table
# return data_table
# data_table = DataTable(source=source, columns=columns, width=500, height=300)
file_input = FileInput(accept=".xlsx")
file_input.on_change('value', upload_fit_data)
p = gridplot([file_input, data_table])
doc = curdoc()
doc.add_root(p)
问题：如何在bokeh应用程序中使用和显示“ data_table”值？如果我运行此代码，则在bokeh界面中不显示“ data_table”]
将numpy作为np导入，将熊猫从bokeh.plotting导入图形，从bokeh.io导入gridplot从bokeh.io导入output_file，显示，从bokeh.models.widgets导入curdoc。
output_file不能与bokeh serve一起使用-并且bokeh serve正是您所需要的，因为您想运行Python代码来响应Web UI中用户的操作gridplot接受一个元组列表，这些元组不仅指定项目本身，而且指定放置每个项目的位置。由于您只有两个小部件，因此column应该足够import io
from base64 import b64decode
import pandas as pd
from bokeh.io import curdoc
from bokeh.layouts import column
from bokeh.models import ColumnDataSource
from bokeh.models.widgets import FileInput, DataTable, TableColumn
column_map = dict(utmx='UTM X', utmy='UTM Y', elev='Elevasi',
lat='Latitude', lon='Longitude', ta='Tinggi Alat',
N='N', E='E', S='S', W='W', time='Time',
kt='Koreksi Tide', rdgrav='Bacaan')
source = ColumnDataSource(data={c: [] for c in column_map})
columns = [TableColumn(field="utmx", title="UTM X"), TableColumn(field="utmy", title="UTM Y"),
TableColumn(field="elev", title="Elevasi"), TableColumn(field="lat", title="Latitude"),
TableColumn(field="lon", title="Longitude"), TableColumn(field="ta", title="Tinggi Alat"),
TableColumn(field="N", title="North"), TableColumn(field="E", title="East"),
TableColumn(field="S", title="South"), TableColumn(field="W", title="West"),
TableColumn(field="time", title="Waktu Pengukuran"), TableColumn(field="kt", title="Koreksi tide"),
TableColumn(field="rdgrav", title="Bacaan Alat")]
data_table = DataTable(source=source, columns=columns, width=500, height=300)
def upload_fit_data(attr, old, new):
f = io.BytesIO(b64decode(new))
new_df = pd.read_excel(f, sheet_name='data')
source.data = {ds_c: new_df[df_c] for ds_c, df_c in column_map.items()}
file_input = FileInput(accept=".xlsx")
file_input.on_change('value', upload_fit_data)
curdoc().add_root(column(file_input, data_table))
请注意，如果您不想拥有一个交互式网页，而只想拥有一个静态HTML文件，那么您将无法使用任何Python回调。您将通过CLI指定XLSX文件，并在脚本运行时立即处理数据。