I am trying to create a funnel chart using plotly and am not having any luck. Even the canned examples from plotly don't work for me, can someone please help?
from plotly import graph_objects as go
fig = go.Figure(go.Funnel(
y = ["Website visit", "Downloads", "Potential customers", "Requested price", "invoice sent"],
x = [39, 27.4, 20.6, 11, 2]))
fig.show()
I get this huge traceback error:
lueError:
Invalid value of type 'plotly.graph_objs.Funnel' received for the 'data' property of
Received value: Funnel({
'x': [39, 27.4, 20.6, 11, 2],
'y': [Website visit, Downloads, Potential customers, Requested price, invoice
sent]
})
The 'data' property is a tuple of trace instances
that may be specified as:
- A list or tuple of trace instances
(e.g. [Scatter(...), Bar(...)])
- A list or tuple of dicts of string/value properties where:
- The 'type' property specifies the trace type
One of: ['area', 'bar', 'barpolar', 'box',
'candlestick', 'carpet', 'choropleth', 'cone',
'contour', 'contourcarpet', 'funnel',
'funnelarea', 'heatmap', 'heatmapgl',
'histogram', 'histogram2d',
'histogram2dcontour', 'isosurface', 'mesh3d',
'ohlc', 'parcats', 'parcoords', 'pie',
'pointcloud', 'sankey', 'scatter',
'scatter3d', 'scattercarpet', 'scattergeo',
'scattergl', 'scattermapbox', 'scatterpolar',
'scatterpolargl', 'scatterternary', 'splom',
'streamtube', 'sunburst', 'surface', 'table',
'violin', 'volume', 'waterfall']
- All remaining properties are passed to the constructor of
the specified trace type
(e.g. [{'type': 'scatter', ...}, {'type': 'bar, ...}])
It seems like you’re using version 3, in which case you will need to use go.Figure(data=[go.Funnel(...)]) (basically wrap your funnel trace in an array... only in version 4 is this optional)
Related
I would like myval to show the name of each car for each aggregated year, ex. "chevrolet chevelle malibu".
The [object Object] thing appears to be JavaScript related.
import altair as alt
from vega_datasets import data
import pandas as pd
import pdb
df = data.cars()
alt.renderers.enable("altair_viewer")
mychart = (
alt.Chart(df)
.transform_joinaggregate(count="count(*)", myval="values(Name)", groupby=["Year"])
.mark_bar()
.encode(
x=alt.X(
"Year",
timeUnit=alt.TimeUnitParams(unit="year", step=1),
type="quantitative",
),
y=alt.Y("count", type="quantitative"),
tooltip=alt.Tooltip(["myval:N"]),
)
)
mychart.show()
This is a great question, and I'm not sure there's a satisfactory answer. The reason this is displayed as [object Object], [object Object], etc. is because the values aggregate returns a list of the entire row for each value. So the full representation would be something like this:
[{'Name': 'chevrolet chevelle malibu', 'Miles_per_Gallon': 18.0, 'Cylinders': 8, 'Displacement': 307.0, 'Horsepower': 130.0, 'Weight_in_lbs': 3504, 'Acceleration': 12.0, 'Year': 1970, 'Origin': 'USA'}, {'Name': 'buick skylark 320', 'Miles_per_Gallon': 15.0, 'Cylinders': 8, 'Displacement': 350.0, 'Horsepower': 165.0, 'Weight_in_lbs': 3693, 'Acceleration': 11.5, 'Year': 1970, 'Origin': 'USA'}, ...]
and those are just the first two entries! So clearly it won't really fit in a tooltip. For what it's worth, newer versions of Vega improve on this (which you can see by viewing the equivalent chart in the vega editor) but it's still not what you're looking for.
What you need is a way to extract just the name from each value in the list... and I'm sure that Vega-Lite transforms provide any good way to do that (the vega expression language does not have anything that resembles list comprehensions or function mapping).
The best I can think of is something like this, to display, say, the first 4 values:
mychart = (
alt.Chart(df)
.transform_joinaggregate(count="count(*)", myval="values(Name)", groupby=["Year"])
.transform_calculate(
first_val="datum.myval[0].Name",
second_val="datum.myval[1].Name",
third_val="datum.myval[2].Name",
fourth_val="datum.myval[3].Name",
)
.mark_bar()
.encode(
x=alt.X(
"Year",
timeUnit=alt.TimeUnitParams(unit="year", step=1),
type="quantitative",
),
y=alt.Y("count", type="quantitative"),
tooltip=alt.Tooltip(["first_val:N", "second_val:N", "third_val:N", "fourth_val:N"]),
)
)
Another option would be, instead of using a tooltip, to use a second chart that updates on mouseover:
base = (
alt.Chart(df)
.transform_joinaggregate(count="count(*)", values="values(Name)", groupby=["Year"])
)
selection = alt.selection_single(fields=['Year'], on='mouseover', empty='none')
bars = (
base
.mark_bar()
.encode(
x=alt.X(
"Year:N",
timeUnit=alt.TimeUnitParams(unit="year", step=1),
type="quantitative",
),
y=alt.Y("count", type="quantitative"),
)
).add_selection(selection)
text = (
base
.transform_filter(selection)
.transform_flatten(['values'])
.transform_calculate(Name="datum.values.Name")
.mark_text()
.encode(
y=alt.Y('Name:N', axis=None),
text='Name:N'
)
).properties(width=300)
chart2 = bars | text
I'd be interested to see if anyone knows of a more complete solution.
I am trying to create an invoice from a custom object but I am getting errors from on validation .When I post, i get the following error: "
ValueError: Wrong value for account.move.line_ids: {'display_type': 'line_section', 'name': 'Phone Bill', 'product_id': 11783, 'product_uom_id': 19, 'current_reading': 66.0, 'current_date': datetime.date(2020, 11, 3), 'quantity': 17.0, 'price_unit': 565.0, 'account_id': 19, 'debit': 9605.0, 'credit': 0.0}
current_date and current_reading are custom fields i created. I am aware that Odoo automatically creates values for line_ids from invoice_line_ids if line_ids is not provided, so I am really stuck about this error.
Here's my code for creating the invoice:
class ReadingCorrection(models.TransientModel):
_name = 'reading.upload.wizard'
_description = 'Validate reading uploads'
def validate_entry(self):
active_ids = self._context.get('active_ids', []) or []
company = self.env.user.company_id
journal = self.env['account.move'].with_context(force_company=company.id, type='out_invoice')._get_default_journal()
for reads in self.env['reading.upload'].browse(active_ids):
if reads.reading >= reads.previous_reading: # and reads.state == 'draft':
account = reads.product_id.product_tmpl_id._get_product_accounts()['income']
if not account:
raise UserError(_('No account defined for product "%s".') % reads.product_id.name)
invoice = {
'type': 'out_invoice',
'invoice_date':reads.read_date,
'narration': reads.remark,
'invoice_user_id': reads.current_user.id,
'partner_id': reads.meter_id.customer_id.id,
'journal_id': 1,#journal.id,
'currency_id': reads.meter_id.customer_id.currency_id.id,
'doc_type': 'bill',
'invoice_line_ids':[(0,0, {
'name': reads.product_id.name,
'product_id': reads.product_id.id,
'product_uom_id': reads.product_id.uom_id.id,
'current_reading': reads.reading,
'previous_reading': reads.previous_reading,
'current_date': reads.read_date,
'quantity': reads.reading - reads.previous_reading,
'price_unit': reads.product_id.product_tmpl_id.lst_price,
'account_id': account.id,
})]
}
moves = self.env['account.move'].with_context(default_type='out_invoice').create(invoice)
#invoice = self.env['account.move'].sudo().create(invoice)
reads.write({'state':'uploaded'})
Any help given will be appreciated. Thanks
If you want to create invoices, in the lines you should not use the debit and credit fields since these are calculated, as it is a product line, you should not use display_type, since the line_section type is treated as an annotation and not as a price calculation line.
In the invoice data, when linking the lines 'invoice_line_ids': inv_line_ids an instruction must be specified to process the lines in your case it would be as follows 'invoice_line_ids': (0, 0, inv_line_ids) for greater information visit this page.
I am looking to get the value of the description field inside the weather.
{'coord': {'lon': 73.85, 'lat': 18.52}, 'weather': [{'id': 800, 'main': 'Clear', 'description': 'clear sky', 'icon': '01d'}], 'base': 'stations', 'main': {'temp': 305.381, 'pressure': 949.7, 'humidity': 31, 'temp_min': 305.381, 'temp_max': 305.381, 'sea_level': 1023.73, 'grnd_level': 949.7}
i have seen many posts and i am trying to do the below:
r1 = requests.get('http://api.openweathermap.org/data/2.5/weather?q=Pune,in&APPID=5ad6ec2537bfb0d574363e115c2d0041')
print(r1.status_code)
json_data = json.loads(r1.text)
print(json_data)
print("Weather is" ,json_data["weather"][0])
But the above is fetching me all the values inside the dictionary.
What's the best way to achieve that?
Thanks.
Use json_data["weather"][0]['description'] to access the description field.
I have the following python code that is to replace low-precision temperatures in a list of JSON trees, ec2_tcs['zones'] with higher precision temps from a generator, ec1_api.temperatures().
if CONF_HIGH_PRECISION:
try:
from evohomeclient import EvohomeClient as EvohomeClientVer1
ec1_api = EvohomeClientVer1(client.username, client.password)
for temp in ec1_api.temperatures(force_refresh=True):
for zone in ec2_tcs['zones']:
if str(temp['id']) == str(zone['zoneId']):
if zone['temperatureStatus']['isAvailable']:
zone['temperatureStatus']['temperature'] \
= temp['temp']
break
# TypeError: usually occurs in client library if problems with vendor's website
except TypeError:
_LOGGER.warning(
"Failed to obtain higher-precision temperatures"
)
The JSON data looks like this (an array of JSON data, 1 per 'zone'):
[
{
'zoneId': '3432521',
'name': 'Main Room'
'temperatureStatus': {'temperature': 21.5, 'isAvailable': True},
'setpointStatus': {'targetHeatTemperature': 5.0, 'setpointMode': 'FollowSchedule'},
'activeFaults': [],
}, {
...
...
}
]
and each result from the generator like this:
{'thermostat': 'EMEA_ZONE', 'id': 3432521, 'name': 'Main Room', 'temp': 21.55, 'setpoint': 5.0}
I know Python must have a better way of doing this, but I can't seem to make it fly. Any suggestions would be gratefully received.
I could 'massage' the generator, but there are good reasons why the JSON tree's schema should remain unchanged.
The primary goal is to reduce a number of nested code blocks with a very fancy one-liner!
I'm testing the flickrapi for python and have some code that randomly chooses a picture of Chinese food. It does this by getting 1 result on 1 page and using the total number of pages in that result to choose 1 result on 1 random page. Here is the code I'm using to get the images:
flickr = flickrapi.FlickrAPI(api_key='mykey', secret='mysecret', format='parsed-json', cache=False)
data1 = flickr.photos.search(tags='Chinese Food',
page=1,
per_page=1,
tag_mode='all',
media='photos',
content_type=1)
data2 = flickr.photos.search(tags='Chinese Food',
page=randint(1, data1['photos']['pages']),
per_page=1,
tag_mode='all',
media='photos',
content_type=1,
extras='url_l')
No matter what I do the result in data2 is always the exact same image returned in data1, I could get the first result from page 1 and the first result from page 3472 and the image is exactly the same every time.
Here is a sample of the data returned
//From data1
{'photos': {'page': 1, 'pages': 70007, 'perpage': 1, 'total': '70007', 'photo': [{'id': '35800805325', 'owner': '24171591#N06', 'secret': '408928a034', 'server': '4261', 'farm': 5, 'title': 'Personalized Maple Wood Chopsticks', 'ispublic': 1, 'isfriend': 0, 'isfamily': 0}]}, 'stat': 'ok'}
//From data2
{'photos': {'page': 41043, 'pages': 70007, 'perpage': 1, 'total': '70007', 'photo': [{'id': '35800805325', 'owner': '24171591#N06', 'secret': '408928a034', 'server': '4261', 'farm': 5, 'title': 'Personalized Maple Wood Chopsticks', 'ispublic': 1, 'isfriend': 0, 'isfamily': 0, 'url_l': 'https://farm5.staticflickr.com/4261/35800805325_408928a034_b.jpg', 'height_l': '859', 'width_l': '1024'}]}, 'stat': 'ok'}
Notice the id and title in both sets of data are exactly the same and the page numbers are different. I've tested this in the Flickr API explorer with the exact same parameters and I do get the same image when I specify page 1 but I also get a completely different image if I specify any other page, so this seems to be an issue with the python flickrapi implementation or one of its dependencies maybe?
I can't seem to find the issue. What is going on?
Looks like other people have been having this issue with Flickr's API since 2011 and it still hasn't been fixed. So, it doesn't seem to be related to Python or the Python Flickr module. I was able to improve the "randomness" by increasing the number of results per page which is something I didn't want to do but it's the only thing that works.