我正在编写一个破折号应用程序。 此刻我的应用看起来像这样
`
import base64
import io
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import matplotlib.pyplot
from dash.dependencies import Input, Output
import dash_table_experiments as dt
import numpy as np
app = dash.Dash()
app.scripts.config.serve_locally = True
app.layout = html.Div([
dcc.Upload(
id='upload-data',
children=html.Div([
'Drag and Drop or ',
html.A('Select Files')
]),
style={
'width': '100%',
'height': '60px',
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
'margin': '10px'
},
# Allow multiple files to be uploaded
multiple=True
),
#plot dropdowns graph and tabel
html.Div(id='output-data-upload'),
html.Div(dt.DataTable(rows=[{}]), style={'display': 'none'}),
],
)
#%%methodes
def parse_contents(contents, filename, date):
content_type, content_string = contents.split(',')
decoded = base64.b64decode(content_string)
try:
if 'csv' in filename:
# Assume that the user uploaded a CSV file
df = pd.read_csv(
io.StringIO(decoded.decode('utf-8')),sep=';',header=6)
elif 'xls' in filename:
# Assume that the user uploaded an excel file
df = pd.read_excel(io.BytesIO(decoded),sep=';',header=6)
except Exception as e:
print(e)
return html.Div([
'There was an error processing this file.'
])
available_indicators=list(df)
ind =np.delete(available_indicators,0),
print (ind)
return html.Div([
#x-Achse
html.Div('Choose Data for x-axis'),
dcc.RadioItems(
id='x_Achse',
options=[
{'label': i, 'value': i} for i in ind[0]],
),
#y-Achse
html.Label('Choose Data for y-axis'),
dcc.Dropdown(
id='y-Achse',
options=[
{'label': i, 'value': i}for i in ind[0]],
multi= True
),
#Graph
return_graph(df,1,1),
html.H5(filename),
# Use the DataTable prototype component:
# github.com/plotly/dash-table-experiments
dt.DataTable(rows=df.to_dict('records')),
html.Hr(), # horizontal line
# For debugging, display the raw contents provided by the web browser
html.Div('Raw Content'),
html.Pre(contents[0:200] + '...', style={
'whiteSpace': 'pre-wrap',
'wordBreak': 'break-all'
})
])
#%%
def return_graph(df, x_Werte, Y_Werte_Array):
return dcc.Graph(id='Liniendiagramm',
figure={
'data': [go.Scatter(
x=df['Date/Time'], #change to x_Werte
y=df['Var_01'], #change to Y_Werte_Array[0]
text=df['Var_01'], #change to Y_Werte_Array[0]
name='Var_01' #change to Y_Werte_Array[0]
),
go.Scatter(
x=df['Date/Time'], #change to x_Werte
y=df['Var_02'], #change to Y_Werte_Array[1]
text=df['Var_02'], #change to Y_Werte_Array[1]
name='Var_02' #change to Y_Werte_Array[1]
),
]
}
)
#%%
#end Methoden
#%%callback
@app.callback(Output('output-data-upload', 'children'),
[Input('upload-data', 'contents'),
Input('upload-data', 'filename'),
Input('upload-data', 'last_modified')])
def update_output(list_of_contents, list_of_names, list_of_dates):
if list_of_contents is not None:
children = [
parse_contents(c, n, d,) for c, n, d in
zip(list_of_contents, list_of_names, list_of_dates)]
return children
#%%
if __name__ == '__main__':
app.run_server(debug=True)`
现在是我的问题。 我的应用程序中的下拉菜单位于parse_contents方法中。因此，如果尝试使用回调获取下拉列表的值，则会收到错误消息。下拉菜单的选项是在此方法中计算的。 我需要一种解决方法来获得.csv文件中Tabel的标题。使用标题的值作为下拉菜单的选项，并将所选的下拉菜单值写入方法return_graph中。
最后一定要看起来 enter image description here 但是目前这两个下拉列表都没有用，并且该图表是通过静态值绘制的 抱歉，代码中的德语单词和英语不好。
答案 0 :(得分：1)
所以现在我有一个解决问题的办法。如果有人要使用它，则代码如下。请注意，在“解析内容”方法中，参数sep =';'和header = 6行设置为静态参数。
`import base64
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objs as go
import dash_table_experiments as dte
from dash.dependencies import Input, Output
import dash
import pandas as pd
import io
app = dash.Dash()
app.scripts.config.serve_locally = True
app.config['suppress_callback_exceptions'] = True
app.layout = html.Div([
html.H5("Upload Files"),
dcc.Upload(
id='upload-data',
children=html.Div([
'Drag and Drop or ',
html.A('Select Files')
]),
style={
'width': '100%',
'height': '60px',
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
'margin': '10px'
},
),
html.Br(),
html.Div("X_Achse"),
dcc.Dropdown(id='x_Achse',
multi = False,
placeholder='Filter Column'),
html.Div('Y_Werte'),
dcc.Dropdown(id='y_Achse',
multi = True,
placeholder='Filter Column'),
html.Div(id='graph'),
html.Br(),
html.H5("Updated Table"),
html.Div(dte.DataTable(rows=[{}], id='table'))
])
# Functions
#%%
# file upload function
def parse_contents(contents, filename):
content_type, content_string = contents.split(',')
decoded = base64.b64decode(content_string)
try:
if 'csv' in filename:
# Assume that the user uploaded a CSV file
df = pd.read_csv(
io.StringIO(decoded.decode('utf-8')),sep=';',header=6)
elif 'xls' in filename:
# Assume that the user uploaded an excel file
df = pd.read_excel(io.BytesIO(decoded),sep=';',header=6)
except Exception as e:
print(e)
return None
return df
#%%
def return_graph(df, x_Werte, Y_Werte_Array):
return dcc.Graph(id='Liniendiagramm',
figure={
'data': [ #definiert die Daten welche visualisiert werden sollen
go.Scatter(
x=df[x_Werte],
y=df[Y_Werte_Array[i]],
text=df[Y_Werte_Array[i]],
name=Y_Werte_Array[i]
)
for i in range(0,len(Y_Werte_Array))
]
}
)
#%%
@app.callback(Output('graph','children'),
[Input('x_Achse','value'),
Input('y_Achse','value'),
Input('table','rows')])
def update_graph(x,y,c):
if x and y and c is not None:
print (x)
print (y)
# print (c)
dff = pd.DataFrame.from_dict(c)
# print('anfang')
# print(dff)
# print ('ende')
graph1=return_graph(dff,x,y)
# print (c)
return graph1 #return_graph(c,a,b)
#%%
# callback table creation
@app.callback(Output('table', 'rows'),
[Input('upload-data', 'contents'),
Input('upload-data', 'filename')])
def update_output(contents, filename):
if contents is not None:
df = parse_contents(contents, filename)
if df is not None:
# print (df)
return df.to_dict('records')
else:
return [{}]
else:
return [{}]
#%%
#callback update options of filter dropdown
@app.callback(Output('x_Achse', 'options'),
[Input('table', 'rows')])
def update_x_Achse( tablerows):
if tablerows is not None:
dff = pd.DataFrame(tablerows) # <- problem! dff stays empty even though table was uploaded
print ("updating... dff empty?:"), dff.empty #result is True, labels stay empty
return [{'label': i, 'value': i} for i in sorted(list(dff))]
#%%
@app.callback(Output('y_Achse', 'options'),
[Input('table', 'rows')])
def update_y_Achse( tablerows):
if tablerows is not None:
dff = pd.DataFrame(tablerows) # <- problem! dff stays empty even though table was uploaded
print ("updating... dff empty?:"), dff.empty #result is True, labels stay empty
return [{'label': i, 'value': i} for i in sorted(list(dff))]
#%%
app.css.append_css({
"external_url": "https://codepen.io/chriddyp/pen/bWLwgP.css"
})
if __name__ == '__main__':
app.run_server(debug=True)`