Ok, so the thing is that everytime I change from page with the radio item button, I want the table of this to change to another one, but I'm not sure how this can be done, so here is the code if someone could help me.
app = dash.Dash(__name__)
app.layout = html.Div([
html.Div([
html.H1('Viviendas disponibles'),
#html.Img(src='assets/vacuna.png')
], className = 'banner'),
html.Div([
html.Div([
html.P('Selecciona la dosis', className = 'fix_label', style={'color':'black', 'margin-top': '2px'}),
dcc.RadioItems(id = 'dosis-radioitems',
labelStyle = {'display': 'inline-block'},
options = [
{'label' : 'Registro', 'value' : 'primera_dosis_cantidad'},
{'label' : 'Verificacion', 'value' : 'segunda_dosis_cantidad'},
{'label' : 'Produccion', 'value' : 'tercera_dosis_cantidad'},
], value = 'primera_dosis_cantidad',
style = {'text-aling':'center', 'color':'black'}, className = 'dcc_compon'),
], className = 'create_container2 five columns', style = {'margin-bottom': '20px'}),
], className = 'row flex-display'),
html.Div([
html.Div([
dcc.Graph(id = 'my_graph', figure = {}),
], style={'width': '49%','display': 'inline-block'}),
html.Div([
dcc.Graph(id = 'pie_graph2', figure = {}),
], style={'width': '50%','display': 'inline-block'}),
], className="row"),
html.Div([
dash_table.DataTable(df.iloc[[-1]].to_dict('records'), [{"name": i, "id": i} for i in df.columns[2:10]]),
html.Br()]),
html.Div([
html.Div([
dcc.Graph(id = 'pie_graph4', figure = {}),
], style={'width': '49%','display': 'inline-block'}),
html.Div([
dcc.Graph(id = 'pie_graph3', figure = {})
], style={'width': '49%', 'display': 'inline-block'})], className="row"),
html.Div([
dash_table.DataTable(df.iloc[[-1]].to_dict('records'), [{"name": i, "id": i} for i in df.columns[12:16]])
]),
], id='mainContainer', style={'display':'flex', 'flex-direction':'column'})
So as you can see, the main table I would like to change is the one that says: dash_table.DataTable(df.iloc[[-1]].to_dict('records'), [{"name": i, "id": i} for i in df.columns[2:10]])
So, anyone has idea on how to do this?
Related
I have a dash app that plots a dataframe which has a date component, and an entry that is either true or false. There are two graphs in the dashboard, one with the data vs date, and one with a percentage of True/False like below:
I can zoom in on the date range and select a subset clicking with the mouse.
I would like to feed this range back into the second graph.
At the moment to produce the above dashboard the relevant part of the code looks like:
from re import template
import pandas as pd
import plotly.express as px
from dash import Dash, Input, Output, dcc, html
from flask import globals
def init_dashboard(server):
evicted_df = pd.read_csv("app/data/evicted_jobs_node.csv", sep="\t")
all_df = pd.read_csv("app/data/all_jobs_node.csv", sep="\t")
all_df["datetime"] = pd.to_datetime(all_df["datetime"])
all_df = all_df.set_index(["datetime"])
all_df["evicted"] = all_df["id_job"].isin(evicted_df["id_job"])
app = Dash(__name__, server=server, routes_pathname_prefix="/dash/")
app.layout = html.Div(
[
html.Div(
className="row",
children=[
html.Div(
className="six columns",
children=[dcc.Graph(id="graph-with-dropdown")],
style=dict(width="75%"),
),
html.Div(
className="six columns",
children=[dcc.Graph(id="graph-with-dropdown2")],
style=dict(width="25%"),
),
],
style=dict(display="flex"),
),
html.Div(
className="row",
children=[
html.Div(
className="six columns",
children=[
dcc.Dropdown(
id="partition-dropdown",
options=[
"Partition (default is all)",
*all_df["partition"].unique(),
],
value="Partition (default is all)",
clearable=False,
searchable=False,
)
],
style={
"width": "50%",
"justify-content": "center",
},
),
html.Div(
className="six columns",
children=[
dcc.Dropdown(
id="node-dropdown",
options=[
"Number of Nodes (default is all)",
*sorted(
[
int(nodes)
for nodes in all_df["nodes_alloc"].unique()
]
),
],
value="Number of Nodes (default is all)",
clearable=False,
searchable=False,
)
],
style=dict(width="50%"),
),
],
style=dict(display="flex"),
),
]
)
init_callbacks(app, df, all_df)
return app.server
def init_callbacks(app, df, all_df):
#app.callback(
Output("graph-with-dropdown2", "figure"),
[Input("node-dropdown", "value"), Input("partition-dropdown", "value")],
)
def update_evicted_fig(selected_nodes, selected_partition):
if selected_nodes != "Number of Nodes (default is all)":
filtered_df = all_df[all_df["nodes_alloc"] == selected_nodes]
else:
filtered_df = all_df
if selected_partition != "Partition (default is all)":
filtered_df = filtered_df[filtered_df["partition"] == selected_partition]
x = ["Not Evicted", "Evicted"]
df1 = filtered_df.groupby(["evicted"]).count().reset_index()
fig = px.bar(
df1,
y=[
100
* filtered_df[filtered_df["evicted"] == False].size
/ filtered_df.size,
100
* filtered_df[filtered_df["evicted"] == True].size
/ filtered_df.size,
],
x=x,
color="evicted",
color_discrete_map={True: "red", False: "green"},
labels={"x": "Job Status", "y": "% of Jobs"},
)
fig.update_layout(transition_duration=500)
return fig
#app.callback(
Output("graph-with-dropdown", "figure"),
[Input("node-dropdown", "value"), Input("partition-dropdown", "value")],
)
def update_evicted_fig(selected_nodes, selected_partition):
if selected_nodes != "Number of Nodes (default is all)":
filtered_df = all_df[all_df["nodes_alloc"] == selected_nodes]
else:
filtered_df = all_df
if selected_partition != "Partition (default is all)":
filtered_df = filtered_df[filtered_df["partition"] == selected_partition]
print(
filtered_df[filtered_df["evicted"] == True]
.groupby([pd.Grouper(freq="6H")])
.sum(numeric_only=True)["node_hours"]
)
fig = px.bar(
x=filtered_df[filtered_df["evicted"] == False]
.groupby([pd.Grouper(freq="6H")])
.sum(numeric_only=True)["node_hours"]
.index,
y=filtered_df[filtered_df["evicted"] == False]
.groupby([pd.Grouper(freq="6H")])
.sum(numeric_only=True)["node_hours"],
labels={
"x": "Date",
"y": "Node hours",
},
title="Job Status",
barmode="stack",
)
fig.add_bar(
name="Evicted",
x=filtered_df[filtered_df["evicted"] == True]
.groupby([pd.Grouper(freq="6H")])
.sum(numeric_only=True)["node_hours"]
.index,
y=filtered_df[filtered_df["evicted"] == True]
.groupby([pd.Grouper(freq="6H")])
.sum(numeric_only=True)["node_hours"],
)
fig.update_layout(transition_duration=500)
return fig
return app.server
Is what I am hoping to do possible, and if so is there some documentation or a worked example someone could highlight for me?
I don't have you df so maybe you can refer my code to revise yours:
import pandas as pd
import numpy as np
import plotly.express as px
import dash
import dash_html_components as html
from dash import dcc
from dash_extensions.enrich import Input, Output, State, ServersideOutput
import dash_bootstrap_components as dbc
from dash.exceptions import PreventUpdate
df_2 = df[(df['BAS_DT'] >= '2022-01-01')]
df5 = df_2.pivot_table(values='USD_XC_BL',
index=['BAS_DT'],
aggfunc=np.sum).reset_index()
fig_3 = px.bar(df5,
x='BAS_DT',
y='USD_XC_BL',
labels='BAS_DT',
hover_name='BAS_DT', color_discrete_sequence=px.colors.qualitative.Alphabet)
fig_3.update_layout(xaxis_title="", yaxis_title="", plot_bgcolor='rgba(0,0,0,0)', margin=dict(l=0, r=0, t=0, b=0))
fig_3.update_xaxes(showline=False, showgrid=False),
fig_3.update_yaxes(showline=False, showgrid=False, separatethousands=True, tickformat=',.0f')
app = dash.Dash(__name__)
app.layout = html.Div([
dbc.Row([
dbc.Col([
dbc.Card([
dbc.CardBody([
dbc.Row([
dbc.Col([
html.H5('Amount by Currency', style={"text-align": "center"}),
dcc.Loading(children=[dcc.Graph(id='histogram_map', figure=fig_3)], color='#119DFF',
type='dot')
], width={'size': 12, 'offset': 0, 'order': 2}, style={"text-align": "left"}),
]),
])
]),
], xs=6),
dbc.Col([
dbc.Card([
dbc.CardBody([
dbc.Row([
dbc.Col([
html.H5('Overdue Status', style={"text-align": "center"}),
dcc.Loading(children=[dcc.Graph(id='overdue_map', figure={})], color='#119DFF', type='dot')
], width={'size': 12, 'offset': 0, 'order': 2}, style={"text-align": "left"}),
]),
])
]),
], xs=6),
], className='p-2 align-items-stretch')
])
#app.callback(
Output('overdue_map', 'figure'),
Input('histogram_map', 'clickData'))
def update_y_timeseries(clickData):
if clickData:
country_name = clickData['points'][0]['hovertext']
df_3 = df[df['BAS_DT'] == country_name]
df_4 = df_3.pivot_table(values='CLOC_CUR_XC_BL',
index=['APL_DTL_NAME'],
aggfunc=pd.Series.nunique).reset_index()
fig = px.bar(df_4,
x='APL_DTL_NAME',
y='CLOC_CUR_XC_BL'
, color_discrete_sequence=px.colors.qualitative.Alphabet)
fig.update_layout(xaxis_title="", yaxis_title="", plot_bgcolor='rgba(0,0,0,0)') # plot_bgcolor='rgba(0,0,0,0)'
fig.update_xaxes(showline=False, showgrid=False),
fig.update_yaxes(showline=False, showgrid=False, separatethousands=True)
fig.update_traces(width=0.3)
return fig
else:
raise PreventUpdate
if __name__ == "__main__":
app.run_server(debug=True)
I'm using clickData to return point as date, and then use this date to filter data and then make new bar graph.
Hope this help.
I am trying to get into using Plotly Dash and I am getting stuck on this one piece where I would like to dynamically add a user-defined number of dropdowns. Here is what I tried:
# Import required libraries
import dash
import math
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
# App Begins
app = dash.Dash(
__name__, meta_tags=[{"name": "viewport", "content": "width=device-width"}],
)
app.title = "Tool"
server = app.server
# Create global chart template
mapbox_access_token = "pk.eyJ1IjoicGxvdGx5bWFwYm94IiwiYSI6ImNrOWJqb2F4djBnMjEzbG50amg0dnJieG4ifQ.Zme1-Uzoi75IaFbieBDl3A"
layout = dict(
autosize=True,
automargin=True,
margin=dict(l=30, r=30, b=20, t=40),
hovermode="closest",
plot_bgcolor="#F9F9F9",
paper_bgcolor="#F9F9F9",
legend=dict(font=dict(size=10), orientation="h"),
title="Satellite Overview",
mapbox=dict(
accesstoken=mapbox_access_token,
style="light",
center=dict(lon=-78.05, lat=42.54),
zoom=7,
),
)
# Create app layout
app.layout = html.Div(
[
dcc.Store(id="aggregate_data"),
# empty Div to trigger javascript file for graph resizing
html.Div(id="output-clientside"),
html.Div(
[
html.Div(
[
html.Img(
src=app.get_asset_url("dash-logo.png"),
id="plotly-image",
style={
"height": "60px",
"width": "auto",
"margin-bottom": "25px",
},
)
],
className="one-third column",
),
html.Div(
[
html.Div(
[
html.H3(
"Dash Tool",
style={"margin-bottom": "0px"},
),
]
)
],
className="one-half column",
id="title",
),
],
id="header",
className="row flex-display",
style={"margin-bottom": "25px"},
),
html.Div(
[
html.Div(
[
html.P("Quantity 1:", className="control_label"),
dcc.Input(
id="quantity_1",
type="number",
placeholder=33.
),
html.P("Quantity 2:", className="control_label"),
dcc.Input(
id="quantity_2",
type="number",
placeholder=-115.
),
html.P("Number of Drop Downs:", className="control_label"),
dcc.Slider(
id="drop_downs",
min=2,
max=10,
value=2,
step=1.0,
className="dcc_control",
),
html.P("Load Inputs:", className="control_label"),
dcc.Checklist(
id='sources_flag',
options=[
{'label': 'Yes', 'value': 'Y'},
],
value=['Y'],
labelStyle={'display': 'inline-block'}
),
html.Div(id='source_dropdown_container', children=[]),
html.Div(id='source_dropdown_container_output'),
html.Div(id='source_file_container', children=[]),
html.Div(id='source_file_container_output'),
],
className="pretty_container four columns",
id="cross-filter-options",
),
],
className="row flex-display",
),
],
id="mainContainer",
style={"display": "flex", "flex-direction": "column"},
)
# Create callbacks
#app.callback(
[
Output(component_id='source_dropdown_container_output', component_property='children'),
],
[
Input(component_id='drop_downs', component_property='value'),
Input(component_id='sources_flag', component_property='value'),
]
)
def update_source_dropdowns(value, value_1):
"""Controls the number of drop-downs available to choose sources"""
if value_1 == 'Y':
children = []
for i in range(0, value):
new_dropdown = dcc.Dropdown(
id=f'''source_dropdown_{str(i)}''',
options=['GOOG', 'FB', 'TDOC', 'FANG']
)
children.append(new_dropdown)
print(children)
print(type(children))
return children
I keep running into a callback error. The drop down is constructed properly, so I am kind of confused as to why that error is being invoked.
dash.exceptions.InvalidCallbackReturnValue: The callback ..source_dropdown_container_output.children.. is a multi-output.
Expected the output type to be a list or tuple but got:
None.
Any guidance or help is appreciated. All I am trying to do is add based on user input a dynamic number of drop downs to the layout.
you have three errors in your callback
there is only one return, hence do not define Output as a list
conditional check is wrong, should be if value_1 == ['Y']:
doc.Dropdown() options argument needs to define list of dict
# Create callbacks
#app.callback(
Output(component_id='source_dropdown_container_output', component_property='children'),
[
Input(component_id='drop_downs', component_property='value'),
Input(component_id='sources_flag', component_property='value'),
]
)
def update_source_dropdowns(value, value_1):
"""Controls the number of drop-downs available to choose sources"""
print("cb", value, value_1)
if value_1 == ['Y']:
children = []
for i in range(0, value):
new_dropdown = dcc.Dropdown(
id=f'''source_dropdown_{str(i)}''',
options=[{"label":v, "value":v } for v in ['GOOG', 'FB', 'TDOC', 'FANG']],
)
children.append(new_dropdown)
print(children)
print(type(children))
return children
Inside the app.layout I have an input, and when I type some info in it, I want to change the info of the CardBody(html.H6).
Trying this way I’ve been having errors like this:
TypeError: The dash_bootstrap_components.Card component (version 0.12.0) with the ID "CardBody(children={}, id='card_title1')" detected a Component for a prop other than children
Did you forget to wrap multiple children in an array?
Prop id has value CardBody(children={}, id='card_title1')
# This is inside app.layout:
html.Div([
dcc.Dropdown(
id='dropdown',
options=[{'label':i, 'value':i} for i in df['c'].unique()],
),
html.Div(id='output')
], className='search-bar'),
html.Div(
[
dbc.Row(
[
dbc.Col(children=[
dbc.Card(dbc.CardHeader("Diretor"),
dbc.CardBody([
html.H6({}, id='card_title1', className="card-title1"),
]), inverse=True)]),
],
className="mb-4 cardsrow",
),
]
),
### Callback function:
#app.callback(
Output('card-title1', 'children'),
Input('dropdown', 'value')
)
def update_output_div(stock_slctd):
if stock_slctd in df.CNPJ_FUNDO.unique():
dff = df[df['FUNDO_CODE']==stock_slctd]
else:
dff = df[df['FUND_NAME']==stock_slctd]
name = dff.DIR.iloc[0]
return name
Instead of this:
dbc.Card(
dbc.CardHeader("Diretor"),
dbc.CardBody(
[
html.H6(
{},
id="card_title1",
className="card-title1",
),
]
),
inverse=True,
)
You should wrap multiple children in an array as the error is telling you:
dbc.Card(
children=[
dbc.CardHeader("Diretor"),
dbc.CardBody(
[
html.H6(
{},
id="card_title1",
className="card-title1",
),
]
),
],
inverse=True,
)
So I want to place my text box as shown
However, my code doesn't work and show me this instead
Heres my coding:
html.H1("Query1", style={'text-align': 'center','fontSize': 30}),
dbc.Row(
[
dbc.Col(dcc.Graph(id='graphQ', figure={}),md=8),
html.P("1"),
dbc.Col(dbc.Input(type="number", min=0, max=10, step=1),),
html.P("2"),
dbc.Col(dbc.Input(type="number", min=0, max=10, step=1)),
]),
dbc.Row(
[
html.P("1"),
dbc.Col(dbc.Input(type="number", min=0, max=10, step=1),),
html.P("2"),
dbc.Col(dbc.Input(type="number", min=0, max=10, step=1),)],
align="end",
)
])]))
Any help is appreciated!
You could do something like this:
def custom_input(paragraph_text, min_value=0, max_value=10, step=1):
return html.Div(
children=[
html.P(paragraph_text, style={"paddingRight": 10}),
dbc.Input(type="number", min=min_value, max=max_value, step=step),
],
style={"display": "flex"},
)
app.layout = html.Div(
children=[
html.H1("Query1", style={"textAlign": "center", "fontSize": 30}),
dbc.Row(
[
dbc.Col(dcc.Graph(id="graphQ", figure={}), md=8),
dbc.Col(
children=[
dbc.Row(
[
dbc.Col(custom_input("1")),
dbc.Col(custom_input("2")),
],
style={"paddingBottom": 30},
),
dbc.Row(
[
dbc.Col(custom_input("1")),
dbc.Col(custom_input("2")),
],
style={"paddingBottom": 30},
),
],
md=4,
),
]
),
]
)
I've abstracted your label / input component combination into a custom function to hopefully make the layout approach more clear and the code more reusable.
So my idea here is we only need one row with two columns. Where the first column consists of the entire graph.
The second column consists of two rows where each row contains two columns, each containing a custom input.
I want to align two Dropdown menus and a DatePickerRange horizontally. But with the following code:
import dash
import dash_core_components as dcc
import dash_html_components as html
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
style_dict = dict(width='100%',
border='1.5px black solid',
height='50px',
textAlign='center',
fontSize=25)
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div(children=[
html.H1(children='Hello Dash'),
# placeholder
html.Div(style={'width': '2%', 'display': 'inline-block'}),
html.Div(
dcc.Dropdown(
id = 'start_hour',
options = [{'label': i, 'value': i} for i in list(range(0,24))],
style=style_dict,
), style={'width': '20%', 'display': 'inline-block'}),
# placeholder
html.Div(style={'width': '2%', 'display': 'inline-block'}),
html.Div(
dcc.DatePickerRange(
id='date_picker_range',
style=style_dict
), style={'width': '14%', 'display': 'inline-block', 'fontSize': 20}),
# placeholder
html.Div(style={'width': '2%', 'display': 'inline-block'}),
html.Div(
dcc.Dropdown(
id = 'end_hour',
options = [{'label': i, 'value': i} for i in list(range(0,24))],
style=style_dict
), style={'width': '20%', 'display': 'inline-block'}),
])
if __name__ == '__main__':
app.run_server(debug=False, use_reloader=False)
I got this layout:
If I zoom in I got this:
Is it possible to force the components to be aligned at the top edge, no matter how I zoom in or out?
As browser I use Firefox.
I had a problem similar to the one you are describing. I was creating a dashboard that looked like this:
dcc components without proper alignement
As you can see in the image, my dcc components, as well as their titles were not aligned correctly. I tried adding the style parameter verticalAlign and it worked as I expected. This is how the dashboard looked after adding that style parameter:
dcc components aligned
I'm attaching my dashboard Layout code so you can see where I placed the parameter mentioned:
## Dashboard layout
app.layout = html.Div( ## Master div
[
html.Div( ## Dashboard title
[
dcc.Markdown(dash_title)
]
),
html.Div( ## Select menus
[
html.Div( ## Stock select
[
dcc.Markdown(dash_stock_sel),
dcc.Dropdown(
id="select_stock",
options=[{"label": cmp, "value": tickers_base[cmp]["symbol"]} for cmp in tickers_base],
value="TSLA"
)
],
style={
"display": "inline-block",
"width": "20%"
}
),
html.Div( ## Date select dcc components
[
dcc.Markdown(dash_date_sel),
dcc.DatePickerRange(
id="select_dates",
min_date_allowed=date(2015, 1, 1),
max_date_allowed=date.today(),
initial_visible_month=date(2015, 1, 1),
end_date=date.today()
)
],
style={
"display": "inline-block",
"width": "30%",
"margin-left": "20px",
"verticalAlign": "top"
}
),
]
),
html.Div( ## Stock prices graph
[
dcc.Graph(
id="cstock_graph",
figure=stock_graph(def_company, datareader_api, def_start, def_end)
)
]
)
]
)
I hope this answer helps!