I’m trying to replicate the dashboard example here
I got 2 errors:
1) Using the “fileId_from_url” function I get the raw_fileId as empty so that when I try to access it
raw_fileId = re.findall("~[A-z]+/[0-9]+", url)[0][1: ]
I get the error
IndexError: list index out of range
2) If I manually change “/” to “:” in the urls, I can go on. When I try to create the dashboard with the line:
py.dashboard_ops.upload(my_dboard, ‘My First Dashboard with Pythonvv’)
I get the error:
raise exceptions.PlotlyRequestError(message, status_code, content)
3) What if I want to try to run it offline? If I import “import plotly.offline as pyo” I can’t use “pyo.dashboard_ops.upload” anymore.
Thanks in advance.
I add the code below
import plotly.plotly as py
py.sign_in(username='myname', api_key='mypass')
#%%
import plotly.dashboard_objs as dashboard
import IPython.display
from IPython.display import Image
my_dboard = dashboard.Dashboard()
my_dboard.get_preview()
#%%
import plotly.graph_objs as go
import numpy as np
colorscale = [[0, '#FAEE1C'], [0.33, '#F3558E'], [0.66, '#9C1DE7'], [1, '#581B98']]
trace1 = go.Scatter(
y = np.random.randn(500),
mode='markers',
marker=dict(
size='16',
color = np.random.randn(500),
colorscale=colorscale,
showscale=True
)
)
data = [trace1]
url_1 = py.plot(data, filename='scatter-for-dashboard', auto_open=False)
py.iplot(data, filename='scatter-for-dashboard')
#%%
x0 = np.random.randn(50)
x1 = np.random.randn(50) + 2
x2 = np.random.randn(50) + 4
x3 = np.random.randn(50) + 6
colors = ['#FAEE1C', '#F3558E', '#9C1DE7', '#581B98']
trace0 = go.Box(x=x0, marker={'color': colors[0]})
trace1 = go.Box(x=x1, marker={'color': colors[1]})
trace2 = go.Box(x=x2, marker={'color': colors[2]})
trace3 = go.Box(x=x3, marker={'color': colors[3]})
data = [trace0, trace1, trace2, trace3]
url_2 = py.plot(data, filename='box-plots-for-dashboard', auto_open=False)
py.iplot(data, filename='box-plots-for-dashboard')
#%%
import re
def fileId_from_url(url):
"""Return fileId from a url."""
raw_fileId = re.findall("~[A-z]+/[0-9]+", url)[0][1: ]
return raw_fileId.replace('/', ':')
def sharekey_from_url(url):
"""Return the sharekey from a url."""
if 'share_key=' not in url:
return "This url is not 'sercret'. It does not have a secret key."
return url[url.find('share_key=') + len('share_key='):]
fileId_1 = fileId_from_url(url_1)
fileId_2 = fileId_from_url(url_2)
box_a = {
'type': 'box',
'boxType': 'plot',
'fileId': fileId_1,
'title': 'scatter-for-dashboard'
}
text_for_box = ""
box_b = {
'type': 'box',
'boxType': 'text',
'text': text_for_box,
'title': 'Markdown Options for Text Box'
}
box_c = {
'type': 'box',
'boxType': 'plot',
'fileId': fileId_2,
'title': 'box-for-dashboard',
'shareKey': sharekey_from_url(url_2)
}
my_dboard.insert(box_a)
my_dboard.insert(box_b, 'above', 1)
#%%
my_dboard.get_box(1)
my_dboard.get_box(1)['title'] = 'a new title'
my_dboard.get_box(1)
my_dboard.insert(box_a, 'below', 2)
my_dboard['settings']['logoUrl'] = 'https://images.plot.ly/language-icons/api-home/python-logo.png'
my_dboard['settings']['links'] = []
my_dboard['settings']['links'].append({'title': 'Link to Plotly', 'url': 'https://plot.ly/'})
my_dboard['settings']['links'].append({'title': 'Link to Python Website', 'url': 'https://www.python.org/'})
my_dboard['settings']['foregroundColor'] = '#000000'
my_dboard['settings']['backgroundColor'] = '#adcaea'
my_dboard['settings']['headerForegroundColor'] = '#ffffff'
my_dboard['settings']['headerBackgroundColor'] = '#D232C8'
my_dboard['settings']['boxBackgroundColor'] = '#ffffff'
my_dboard['settings']['boxBorderColor'] = '#000000'
my_dboard['settings']['boxHeaderBackgroundColor'] = '#ffffff'
stacked_dboard = dashboard.Dashboard()
text_box = {
'type': 'box',
'boxType': 'text',
'text': 'empty space'
}
for _ in range(5):
stacked_dboard.insert(text_box, 'below', 1)
#%%
stacked_dboard['layout']['size'] = 3000
my_dboard['layout']['first']['first'] = text_for_box
py.dashboard_ops.upload(my_dboard, 'My First Dashboard with Pythonvv')
Related
I'm trying to generate a Dash app which displays historical and forecasted housing prices. I've got the forecasted data stored in a different dataframe from the historical prices, and I'd like to plot them both on the same graph in Dash, and have the graph get updated via callback when the user picks a different city from a dropdown menu. I would like both traces of the graph to update when a value is selected in the dropdown. I've tried various things but can only get one trace from one dataframe plotted for the graph in my callback:
# --- import libraries ---
import dash
import dash_table
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import numpy as np
import plotly.express as px
import plotly.graph_objects as go
from dash.dependencies import Output, Input
# --- load data ---
df_h = pd.read_csv('df_h.csv')
df_arima = pd.read_csv('df_arima.csv')
options = [] #each column in the df_h dataframe is an option for the dropdown menu
for column in df_h.columns:
options.append({'label': '{}'.format(column, column), 'value': column})
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
# --- initialize the app ---
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
# --- layout the dashboard ---
app.layout = html.Div(
children = [
html.Div([
html.Label('Select a feature from drop-down to plot'),
dcc.Dropdown(
id = 'city-dropdown',
options = options,
value = 'Denver, CO',
multi = False,
clearable = True,
searchable = True,
placeholder = 'Choose a City...'),
html.Div(id = 'forecast-container',
style = {'padding': '50px'}),
]),
],
)
# --- dropdown callback ---
#app.callback(
Output('forecast-container', 'children'),
Input('city-dropdown', 'value'))
def forecast_graph(value):
dff = df_h[['Date', value]] #'value' is identical between the two dataframes. references
dfa = df_arima[df_arima['City'] == value] # a col in dff and row values in dfa
return [
dcc.Graph(
id = 'forecast-graph',
figure = px.line(
data_frame = dff,
x = 'Date',
y = value).update_layout(
showlegend = False,
template = 'xgridoff',
yaxis = {'title': 'Median Home Price ($USD)'},
xaxis = {'title': 'Year'},
title = {'text': 'Median Home Price vs. Year for {}'.format(value),
'font': {'size': 24}, 'x': 0.5, 'xanchor': 'center'}
),
)
]
I was able to accomplish this in Plotly but can't figure out how to do it in Dash. This is what I want in Dash:
Plotly graph I am trying to reproduce in callback, that is linked to a dropdown menu
This is all I can get to work in Dash:
Only one dataframe plots in Dash
This is the code that works in plotly graph objects:
from statsmodels.tsa.arima_model import ARIMA
df_ml = pd.read_csv('df_ml.csv')
# --- data cleaning ---
df_pred = df_ml[df_ml['RegionName'] == city]
df_pred = df_pred.transpose().reset_index().drop([0])
df_pred.columns = ['Date', 'MedianHomePrice_USD']
df_pred['MedianHomePrice_USD'] = df_pred['MedianHomePrice_USD'].astype('int')
df_pred['Date'] = pd.to_datetime(df_pred['Date'])
df_pred['Date'] = df_pred['Date'].dt.strftime('%Y-%m')
df_model = df_pred.set_index('Date')
model_data = df_model['MedianHomePrice_USD']
def house_price_forecast(model_data, forecast_steps, city):
#--- ARIMA Model (autoregressive integrated moving average) ---
model = ARIMA(model_data, order = (2,1,2), freq = 'MS')
res = model.fit()
forecast = res.forecast(forecast_steps)
forecast_mean = forecast[0]
forecast_se = forecast[1]
forecast_ci = forecast[2]
df_forecast = pd.DataFrame()
df_forecast['Mean'] = forecast_mean.T
df_forecast['Lower_ci'], df_forecast['Upper_ci'] = forecast_ci.T
df_forecast['Date'] = pd.date_range(start = '2021-02', periods = forecast_steps, freq = 'MS')
df_forecast['Date'] = df_forecast['Date'].dt.strftime('%Y-%m')
df_forecast.index = df_forecast['Date']
fig = go.Figure()
fig.add_trace(go.Scatter(x = df_pred['Date'], y = df_pred['MedianHomePrice_USD'],
mode = 'lines', name = 'Median Home Price ($USD)',
line_color = 'rgba(49, 131, 189, 0.75)', line_width = 2))
fig.add_trace(go.Scatter(x = df_forecast.index, y = df_forecast['Mean'],
mode = 'lines', line_color = '#e6550d',
name = 'Forecast mean'))
fig.add_trace(go.Scatter(x = df_forecast.index, y = df_forecast['Upper_ci'],
mode = 'lines', line_color = '#e0e0e0', fill = 'tonexty',
fillcolor = 'rgba(225,225,225, 0.3)',
name = 'Upper 95% confidence interval'))
fig.add_trace(go.Scatter(x = df_forecast.index, y = df_forecast['Lower_ci'],
mode = 'lines', line_color = '#e0e0e0', fill = 'tonexty',
fillcolor = 'rgba(225,225,225, 0.3)',
name = 'Lower 95% confidence interval'))
fig.update_layout(title = 'Median Home Price in {}, {} - {} (Predicted)'.format(
city, model_data.idxmin()[:-3], df_forecast_mean.idxmax()[:-3]),
xaxis_title = 'Year', yaxis_title = 'Median Home Price ($USD)',
template = 'xgridoff')
fig.show()
house_price_forecast(model_data, 24, 'Denver, CO') #24 month prediction
Perhaps a more succinct way of asking this question: How do I add a trace to an existing Dash graph, with data from a different dataframe, and both traces get updated when the user selects a value from a single dropdown?
Figured it out...
Don't use the syntax I used above in your callback. Put the px.line call inside a variable(fig, in this case), and then use fig.add_scatter to add data from a different dataframe to the graph. Both parts of the graph will update from the callback.
Also, fig.add_scatter doesn't have a dataframe argument, so use df.column or df[column] (ex. 'dfa.Date' below)
# --- import libraries ---
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import plotly.express as px
from dash.dependencies import Output, Input
# --- load data ---
df_h = pd.read_csv('df_h.csv')
df_h['Date'] = pd.to_datetime(df_h['Date'])
df_arima = pd.read_csv('df_arima.csv')
df_arima['Date'] = pd.to_datetime(df_arima['Date'])
df_arima['Date'] = df_arima['Date'].dt.strftime('%Y-%m')
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
# --- initialize the app ---
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div([
dcc.Graph(id = 'forecast-container')
]
)
# --- dropdown callback ---
#app.callback(
Output('forecast-container', 'figure'),
Input('city-dropdown', 'value'))
def update_figure(selected_city):
dff = df_h[['Date', selected_city]]
# dff[selected_city] = dff[selected_city].round(0)
dfa = df_arima[df_arima['City'] == selected_city]
fig = px.line(dff, x = 'Date', y = selected_city,
hover_data = {selected_city: ':$,f'})
fig.add_scatter(x = dfa.Date, y = dfa.Mean,
line_color = 'orange', name = 'Forecast Mean')
fig.add_scatter(x = dfa.Date, y = dfa.Lower_ci,
fill = 'tonexty', fillcolor = 'rgba(225,225,225, 0.3)',
marker = {'color': 'rgba(225,225,225, 0.9)'},
name = 'Lower 95% Confidence Interval')
fig.add_scatter(x = dfa.Date, y = dfa.Upper_ci,
fill = 'tonexty', fillcolor = 'rgba(225,225,225, 0.3)',
marker = {'color': 'rgba(225,225,225, 0.9)'},
name = 'Upper 95% Confidence Interval')
fig.update_layout(template = 'xgridoff',
yaxis = {'title': 'Median Home Price ($USD)'},
xaxis = {'title': 'Year'},
title = {'text': 'Median Home Price vs. Year for {}'.format(selected_city),
'font': {'size': 24}, 'x': 0.5, 'xanchor': 'center'})
return fig
if __name__ == '__main__':
app.run_server(debug = True)
Why plotly package of python can not display figure in RMarkdown but matplotlib can? For example:
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, message = FALSE, warning = FALSE)
```
```{r}
library(plotly)
subplot(
plot_ly(mpg, x = ~cty, y = ~hwy, name = 'default'),
plot_ly(mpg, x = ~cty, y = ~hwy) %>%
add_markers(alpha = 0.2, name = 'alpha'),
plot_ly(mpg, x = ~cty, y = ~hwy) %>%
add_markers(symbols = I(1), name = 'hollow')
)
```
```{python}
import plotly
import plotly.plotly as py
import plotly.graph_objs as go
import numpy as np
plotly.tools.set_credentials_file(username='xxx', api_key='xxx')
N = 500
trace0 = go.Scatter(x = np.random.randn(N), y = np.random.randn(N) + 2, name = "Above", mode = "markers",
marker = dict(size = 10, color = "rgba(152, 0, 0, .8)", line = dict(width = 2, color = "rgb(0,0,0)")))
trace1 = go.Scatter(x = np.random.randn(N), y = np.random.randn(N) - 2, name = "below", mode = "markers",
marker = dict(size = 10, color = "rgba(255, 182, 193, .9)", line = dict(width = 2, color = "rgb(0,0,0)")))
data = [trace0, trace1]
layout = dict(title = "Styled Scatter", yaxis = dict(zeroline = False), xaxis = dict(zeroline=False))
fig = dict(data = data, layout = layout)
py.iplot(fig, filename = "styled-scatter")
```
The R code can work well, but the python code can not dispay the figure, what is wrong with the code?
Here is what I did:
used plotly offline:
replace import plotly.plotly as py by import plotly.offline as py
no need to set username and api key in offline mode.
used py.plot(fig, filename = "styled-scatter.html", auto_open=False):
py.iplot() is for Jupyter notebooks (it embeds the plot directly into the Notebook)
auto_open = False argument is to avoid that the plot pops up.
embedded the html plot into the Rmarkdown by using the following:
```{r, echo=FALSE}
htmltools::includeHTML("styled-scatter.html")
```
and here is the result:
It seems that the example code on the plotly website for choropleth maps is out of date and no longer works.
The error I'm getting is:
PlotlyError: Invalid 'figure_or_data' argument. Plotly will not be able to properly parse the resulting JSON. If you want to send this 'figure_or_data' to Plotly anyway (not recommended), you can set 'validate=False' as a plot option.
Here's why you're seeing this error:
The entry at index, '0', is invalid because it does not contain a valid 'type' key-value. This is required for valid 'Data' lists.
Path To Error:
['data'][0]
The code that I'm trying to run is shown below. It is copied as-is from the plotly website. Anyone have any ideas as to how I can fix it?
import plotly.plotly as py
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv')
for col in df.columns:
df[col] = df[col].astype(str)
scl = [[0.0, 'rgb(242,240,247)'],[0.2, 'rgb(218,218,235)'],[0.4, 'rgb(188,189,220)'],\
[0.6, 'rgb(158,154,200)'],[0.8, 'rgb(117,107,177)'],[1.0, 'rgb(84,39,143)']]
df['text'] = df['state'] + '<br>' +\
'Beef '+df['beef']+' Dairy '+df['dairy']+'<br>'+\
'Fruits '+df['total fruits']+' Veggies ' + df['total veggies']+'<br>'+\
'Wheat '+df['wheat']+' Corn '+df['corn']
data = [ dict(
type='choropleth',
colorscale = scl,
autocolorscale = False,
locations = df['code'],
z = df['total exports'].astype(float),
locationmode = 'USA-states',
text = df['text'],
marker = dict(
line = dict (
color = 'rgb(255,255,255)',
width = 2
)
),
colorbar = dict(
title = "Millions USD"
)
) ]
layout = dict(
title = '2011 US Agriculture Exports by State<br>(Hover for breakdown)',
geo = dict(
scope='usa',
projection=dict( type='albers usa' ),
showlakes = True,
lakecolor = 'rgb(255, 255, 255)',
),
)
fig = dict(data=data, layout=layout)
url = py.plot(fig, filename='d3-cloropleth-map')
fig should be of the Figure type. Use the Choropleth graph object:
import plotly.graph_objs as go
...
data = [go.Choropleth(
colorscale = scl,
autocolorscale = False,
locations = df['code'],
z = df['total exports'].astype(float),
locationmode = 'USA-states',
text = df['text'],
marker = dict(
line = dict(
color = 'rgb(255,255,255)',
width = 2)),
colorbar = dict(
title = "Millions USD")
)]
...
fig = go.Figure(data=data, layout=layout)
...
This is what I am doing in an ipython notebook where the plotly graphs and everything gets generated without fail. After that I am taking the html form of the notebook and embedding it in a django template where everything is working other than the plotly graphs. I am not sure what needs to be done thats why I also tried installing plotly on npm and also including a reference to plotly.js through my template. Below are the codes.
import pandas as pd
import numpy as np
from plotly.offline import download_plotlyjs, init_notebook_mode, iplot
from plotly.graph_objs import *
init_notebook_mode()
data = pd.read_csv("storage/AviationDataUp.csv")
useful_columns = ['Event.Date', 'Location', 'Country', 'Latitude', 'Longitude', 'Purpose.of.Flight',\
'Total.Fatal.Injuries','Number.of.Engines','Air.Carrier']
data = data[useful_columns]
data = data[data['Country']=='United States']
accident_trace = Scattergeo(
locationmode = 'ISO-3',
lon = data['Longitude'],
lat = data['Latitude'],
mode = 'markers',
marker = dict(
size = 2,
opacity = 0.75,
color="rgb(0, 130, 250)"),
name = 'Accidents'
)
layout = dict(
title = 'Aviation Accidents in USA',
geo = dict(
scope = 'usa',
projection = dict(),
showland = True,
landcolor = 'rgb(250, 250, 250)',
subunitwidth = 1,
subunitcolor = 'rgb(217, 217, 217)',
countrywidth = 1,
countrycolor = 'rgb(217, 217, 217)',
showlakes = True,
lakecolor = 'rgb(255, 255, 255)'
) )
figure = dict(data=Data([accident_trace]), layout=layout)
iplot(figure)
I'm trying to create a plotly graph with a Scatter and Graph elements. It all goes nicely, but one issue - the two Y axis don't align around 0.
I have tried playing with different attributes, such as 'mirror' and tick0, I also tried following the examples on plotly's site, but it's mostly multiple y-axis with the same graph type.
What can I do to fix this?
import utils
import pandas as pd
import plotly.plotly as py
import plotly.graph_objs as go
import plotly
pd_data ['dt'] = ... dates
pd_data['price'] = ... prices
pd_data['car'] = ... cars
price = go.Scatter(
x = pd_data['dt'],
y = pd_data['price'],
mode = 'lines',
name = 'Price',
xaxis = 'x',
yaxis='y1',
marker = dict(
color = utils.prep_color_string('orange'),
),
line = dict(
width = utils.line_width,
),
)
car = go.Bar(
x = pd_data['dt'],
y = pd_data['car'],
#mode = 'lines',
name = 'Cars',
xaxis = 'x',
yaxis='y2',
marker = dict(
color = utils.prep_color_string('light_green'),
),
#line = dict(
# width = utils.line_width,
#),
)
data = [price, car]
layout = dict(
title = 'Price/Car',
geo = dict(
showframe = True,
showcoastlines = True,
projection = dict(
type = 'Mercator'
)
),
yaxis=dict(
title = 'Price',
tickprefix = "$",
overlaying='y2',
anchor = 'x'
),
yaxis2=dict(
title = 'Car',
dtick = 1,
#tickprefix = "",
side = 'right',
anchor = 'x',
),
)
fig = dict( data=data, layout=layout)
div = plotly.offline.plot( fig, validate=False, output_type = 'file',filename='graph.html' ,auto_open = False)
I have been struggling with this as well. Exact same problem, but I am using R. The way I figured around it was to use the rangemode="tozero" for both the yaxis and yaxis2 layouts.
I think in your case, it would look like this:
layout = dict(
title = 'Price/Car',
geo = dict(
showframe = True,
showcoastlines = True,
projection = dict(
type = 'Mercator'
)
),
yaxis=dict(
title = 'Price',
tickprefix = "$",
overlaying='y2',
anchor = 'x',
rangemode='tozero'
),
yaxis2=dict(
title = 'Car',
dtick = 1,
#tickprefix = "",
side = 'right',
anchor = 'x',
rangemode = 'tozero'
),
)
Let me know if that works for you.