The data set used has been modified on August 29. Please read the note below.
Hi Community Members,
We are officially launching Plotly’s Fall App-Building challenge, where we invite the community to build the most impressive multi-page app with the new Dash Pages feature. The new data contains the spirits purchase information of Iowa Class “E” liquor licensees by product and date of purchase.
Given the issues with original supermarket sales data set brough up by the commuity, we are replacing it with this new Liquor sales data. For those that have already started working on a Dash app with the supermaket data set, that data will still be accepted for the challenge, so feel free to submit your apps with that data.
To enter the Community Challenge, please download the data you would like to work with, create an app, and share it by replying to this Forum topic or by sending me a direct message before midnight Sunday, October 2. Please share the code used. Also, please share a link to the deployed app, if possible.
The winning apps will be judged according to the following categories:
App creativity
App design
Data exploration
Data science or data analysis routines (eg numerical methods, machine learning, prediction, classification, optimization)
First place prize: $125 US dollars
Second place prize: $75 US dollars
Third place prize: $50 US dollars
The winners will be announced in the next Dash Club Dispatch (October).
App Example:
Thank you @Milan for submitting the first app to this challenge and for allowing me to showcase it.
Hi! I know the competition started and all but I don’t think this dataset is very good, it seems to be fabricated and the insights we can get from the dataset are pretty limited.
kaggle discussion about why the dataset is problematic:
Yeah, you are right, I took a look into the data before seeing the comments on kaggle and came to the same conclusions. You can just delete a bunch of columns and it is not going to make any difference.
From a data science perspective there might be not much interesting about it.
Hi @adamschroeder, first of all thank you for creating this challenge. I would like to send my multiple page app that I deployed. Here is the link to the app, and below is screenshot of my app:
@adamschroeder : Thank you. Btw I have a question that have you ever tried to add dcc.Download and deploy to heroku? It worked in local but did not worked in heroku so I had to use Export instead of Download.
Hi @hoatran, thanks for sharing your app!
I have used dcc.Download before and deployed it to Heroku and was working so maybe I could help you solve whatever issue you’re having
@jhupiterz: Thank for your response.
Below is my code to update table and Download:
@app.callback([Output('table','data'),
Output('store_date','data')],
[Input('btn_6','n_clicks')],
[State('my-date-picker-range_6','start_date'),
State('my-date-picker-range_6','end_date'),
State('stores_2','value'),
State('category_2','value'),
State('items_2','value')])
def update_table(n_clicks,start_date_6,end_date_6,store,category,items):
global df_table_2
df_table_2 = df_table[(df_table['date'] >= start_date_6) & (df_table['date'] <= end_date_6)]
if store != []:
df_table_2 = df_table_2[df_table_2['store_name'].isin(store)]
if category != []:
df_table_2 = df_table_2[df_table_2['category_name'].isin(category)]
if items != []:
df_table_2 = df_table_2[df_table_2['item_description'].isin(items)]
return df_table_2.to_dict(orient='records'),df_table_2.to_dict(orient='records')
# Download not work on Heroku
@app.callback(Output('download_1','data'),
[Input('btn_7','n_clicks')],
[State('store_date','data')],
prevent_initial_call=True)
def generate_excel(n_clicks,n):
df_table_3 = df_table_2.copy()
if n_clicks > 0:
return dcc.send_data_frame(df_table_3.to_excel,filename='Data_table' + ".xlsx",index=False)
So my idea is use dropdown and Submit Button to update table then send it to Store. After that I will use Download button to download data that sent to Store. It worked in local but in Heroku, it was just Updating and nothing happened. Can you share link to your app or repo for this. Thank you.
@hoatran Thanks! I like putting filters in modal, it does not occupy too much space on default view (only one button) and looks fancy when button is clicked
hi @AIMPED
Very nice usage of Dash_Leaflet. I really like the feature that allows you to zoom in and see more markers on the map. When all the map coordinates are displayed at once, it makes it overwhelming.
Thank you @Milan for submitting the first app to this challenge and for allowing me to showcase it.
