plotly-dash

问题 This maybe asking alot, but I was curious if anyone had any tips for combining these two dash scripts. The purpose would be to incorporate the drop down menu to remove/add data points on the visualization plots. The first script will visualize my data nicely and the second script with the callback function is for creating a drop down menu from the plotly tutorials. import dash import dash_core_components as dcc import dash_html_components as html import pandas as pd import plotly.graph_objs

问题 I want to embed Plotly graph in my own html file. Using Dash, I can generate the same graph into API local server. However for my own HTML file, I did not get any solution: My Dash solution: import dash import dash_core_components as dcc import dash_html_components as html app = dash.Dash() app.layout = html.Div(children=[ html.H1(children='Dash Tutorials'), dcc.Graph( id='example', figure={ 'data': [ {'x': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'y': [9, 6, 2, 1, 5, 4, 6, 8, 1, 3], 'type': 'bar',

问题 I am attempting to calculate the bearing between two lat/long. I don't have a question regarding the function/formula per se, provided: def get_bearing(lat1, long1, lat2, long2): dLon = (long2 - long1) y = math.sin(dLon) * math.cos(lat2) x = math.cos(lat1) * math.sin(lat2) - math.sin(lat1) * math.cos(lat2) * math.cos(dLon) brng = math.atan2(y, x) brng = np.rad2deg(brng) return brng the problem is that the result isn't what is expected. The intended usage of the function returns the bearing

问题 I'm running into layout difficulties with the plots on Dash. All the plots I generate with Dash seem to be auto sized to be very narrow, which makes it hard to actually view the data without some creative zooming. As an example, when I view the source on one of my dashes, it looks like it computes the height of the main plot container (svg-container) to be 450px and the height of the graph itself to be 270px (looking at the subplots). It would be nice if I could make the graph, say, 700px. My

问题 I'm running into layout difficulties with the plots on Dash. All the plots I generate with Dash seem to be auto sized to be very narrow, which makes it hard to actually view the data without some creative zooming. As an example, when I view the source on one of my dashes, it looks like it computes the height of the main plot container (svg-container) to be 450px and the height of the graph itself to be 270px (looking at the subplots). It would be nice if I could make the graph, say, 700px. My

问题 I created a tool in Dash where user pulls data from SQL Server, filters out desired rows and edits values in one of the columns. Now I have to get that filtered and edited table in a new table in SQL Server. I'm new to dash and can't find a way to export directly to SQL Server or export .csv to a specific location on disc and handle it with a SQL Server procedure from there. Has anyone had a problem like this and knows if it is even possible? I managed to export .csv , but it goes into the

问题 I want to have multiple plotly plots on 1 html page without using the tools.make_subplots method. (I dont want to use that since I find that its not easy to read and I want a unique legend & layout in each of the subplot panels). I want to define 2 figures with their own unique layouts, and arrange them arbitrarily on the page. I think I know how to do this with dash using the html.Div object, but I was wondering if there was an easy way to do this using only plotly? 回答1: I encountered the

问题 Background Dash web applications have a dash application instance, usually named app , and initiated like this: app = dash.Dash(__name__) Then, callbacks are added to the application using a callback decorator: @app.callback(...) def my_function(...): # do stuff. In most of the tutorials you find, the callbacks are defined with all of the application layout in the app.py . This of course is just the MWE way of doing things. In a real application, separating code to modules and packages would

问题 I would like to read a .csv file and return a groupby function as a callback to be displayed as a simple data table with "dash_table" library. @Lawliet's helpful answer shows how to do that with "dash_table_experiments" library. Here is where I’m stuck: import pandas as pd import dash import dash_core_components as dcc import dash_html_components as html import dash_table from dash.dependencies import Input, Output, State df = pd.read_csv( 'https://gist.githubusercontent.com/chriddyp/'

问题 I would like to read a .csv file and return a groupby function as a callback to be displayed as a simple data table with "dash_table" library. @Lawliet's helpful answer shows how to do that with "dash_table_experiments" library. Here is where I’m stuck: import pandas as pd import dash import dash_core_components as dcc import dash_html_components as html import dash_table from dash.dependencies import Input, Output, State df = pd.read_csv( 'https://gist.githubusercontent.com/chriddyp/'