Is there a fancy name generator in nodejs to create names like heroku does for creating applications ?
I'm thinking of names like "yellow_birds", "beautifull_summer" and stuff like that.
Otherwise, are there any dictionnary to pickup cool words ?
Not specific to node, but I've found the following haiku generator here. You could adapt it the following way:
function haiku(){
var adjs = ["autumn", "hidden", "bitter", "misty", "silent", "empty", "dry",
"dark", "summer", "icy", "delicate", "quiet", "white", "cool", "spring",
"winter", "patient", "twilight", "dawn", "crimson", "wispy", "weathered",
"blue", "billowing", "broken", "cold", "damp", "falling", "frosty", "green",
"long", "late", "lingering", "bold", "little", "morning", "muddy", "old",
"red", "rough", "still", "small", "sparkling", "throbbing", "shy",
"wandering", "withered", "wild", "black", "young", "holy", "solitary",
"fragrant", "aged", "snowy", "proud", "floral", "restless", "divine",
"polished", "ancient", "purple", "lively", "nameless"]
, nouns = ["waterfall", "river", "breeze", "moon", "rain", "wind", "sea",
"morning", "snow", "lake", "sunset", "pine", "shadow", "leaf", "dawn",
"glitter", "forest", "hill", "cloud", "meadow", "sun", "glade", "bird",
"brook", "butterfly", "bush", "dew", "dust", "field", "fire", "flower",
"firefly", "feather", "grass", "haze", "mountain", "night", "pond",
"darkness", "snowflake", "silence", "sound", "sky", "shape", "surf",
"thunder", "violet", "water", "wildflower", "wave", "water", "resonance",
"sun", "wood", "dream", "cherry", "tree", "fog", "frost", "voice", "paper",
"frog", "smoke", "star"];
return adjs[Math.floor(Math.random()*(adjs.length-1))]+"_"+nouns[Math.floor(Math.random()*(nouns.length-1))];
}
Take a look to these modules:
https://github.com/faker-js/faker, can generate all kinds of fake data, also localised.
https://github.com/weaver/moniker, this one seems to do just what you need.
https://github.com/nodeca/charlatan
https://github.com/boo1ean/casual
https://github.com/seancannon/goby
Related
What exactly is the behavior of padding for group marks in Vega? At the top-most level the children groups respect the top-level padding, but this doesn't seem the case for the children's children, they don't respect their parent's padding.
For example, here I would expect to get a rectangle centered in a rectangle centered in another rectangle:
Open the Chart in the Vega Editor
Instead each rectangle seems to be anchored at the origin of the top-level coordinate system.
Note that replacing "padding": {"signal": "level_2_padding"} with "padding": {"value": 0} doesn't seem to have any effect, so I'm not even sure if inner groups can have padding?
How can I best implement nested groups that respect the parent's padding?
There is no padding property on a Group mark. Instead, you can access group properties using Field Values. Something like the following should work.
Editor
{
"$schema": "https://vega.github.io/schema/vega/v5.json",
"autosize": "none",
"config": {"group": {"stroke": "black"}},
"signals": [
{"name": "target_height", "value": 400},
{"name": "target_width", "value": 300},
{"name": "level_0_padding", "value": 64},
{"name": "level_1_padding", "update": "1/2 * level_0_padding"},
{"name": "level_2_padding", "update": "1/4 * level_0_padding"},
{"name": "level_0_height", "update": "target_height - 2*level_0_padding"},
{"name": "level_0_width", "update": "target_width - 2*level_0_padding"},
{"name": "level_1_width", "update": "level_0_width - 2*level_1_padding"},
{"name": "level_1_height", "update": "level_0_height - 2*level_1_padding"}
],
"width": {"signal": "level_0_width"},
"height": {"signal": "level_0_height"},
"padding": {"signal": "level_0_padding"},
"marks": [
{
"type": "group",
"signals": [
{
"name": "level_2_width",
"update": "level_1_width - 2*level_2_padding"
},
{
"name": "level_2_height",
"update": "level_1_height - 2*level_2_padding"
}
],
"encode": {
"update": {
"width": {"signal": "level_1_width"},
"height": {"signal": "level_1_height"},
"x": {"signal": "level_0_width-level_1_width - level_1_padding"},
"y": {"signal": "level_0_height-level_1_height - level_1_padding"},
"stroke": {"value": "red"},
"strokeOpacity": {"value": 0.5}
}
},
"marks": [
{
"type": "group",
"encode": {
"update": {
"width": {"signal": "level_2_width"},
"height": {"signal": "level_2_height"},
"x": {
"field": {"group": "width"},
"mult": 0.5,
"offset": {"signal": "-level_2_width/2"}
},
"y": {
"field": {"group": "height"},
"mult": 0.5,
"offset": {"signal": "-level_2_height/2"}
},
"stroke": {"value": "blue"},
"strokeOpacity": {"value": 0.5}
}
}
}
]
}
]
}
I'll accept David's answer, but also post my own to complement David's.
Here's an alternative solution specification, like David's spec it uses the "x" and "y" group properties, but I think it's a bit simpler and closer to what I need: Open the Chart in the Vega Editor
An important point that I have to mention is that using layout prevents x and y from working, that is: groups directly contained in a layout/grid may not be offset using x or y.
I'm trying to count distinct values of multiple fields By one MongoDB Aggregation query.
So here's my data:
{
"_id":ObjectID( "617b0dbacda6cbd1a0403f68")
"car_type": "suv",
"color": "red",
"num_doors": 4
},
{
"_id":ObjectID( "617b0dbacda6cbd1a04078df")
"car_type": " suv ",
"color": "blue",
"num_doors": 4
},
{
"_id":ObjectID( "617b0dbacda6cbd1a040ld45")
"car_type": "wagon",
"color": "red",
"num_doors": 4
},
{
"_id":ObjectID( "617b0dbacda6cbd1a0403dcd")
"car_type": "suv",
"color": "blue",
"num_doors": 4
},
{
"_id":ObjectID( "617b0dbacda6cbd1a0403879")
"car_type": " wagon ",
"color": "red",
"num_doors": 4
},
{
"_id":ObjectID( "617b0dbacda6cbd1a0405478")
"car_type": "wagon",
"color": "red",
"num_doors": 4
}
I want a distinct count of each color by car_type:
"car_type": "suv"
"red":2,
"blue":2
iwas able to distinct and cound all colors but i couldnt distinct them by car_type
Query
group specific first (cartype+color), to count the same colors
group less specific after (cartype), to get all colors/count for each car_type
project to fix structure and $arrayToObject to make the colors keys and the the count values
*query assumes that " wagon " was typing mistake(the extra spaces i mean), if your collection has those problems, use $trim to clear the database from those.
*query is updated to include the sum also, from the comment
Test code here
aggregate(
[{"$group":
{"_id": {"car_type": "$car_type", "color": "$color"},
"count": {"$sum": 1}}},
{"$group":
{"_id": "$_id.car_type",
"colors": {"$push": {"k": "$_id.color", "v": "$count"}}}},
{"$set": {"sum": {"$sum": "$colors.v"}}},
{"$project":
{"_id": 0,
"sum": 1,
"car_type": "$_id",
"colors": {"$arrayToObject": ["$colors"]}}},
{"$replaceRoot": {"newRoot": {"$mergeObjects": ["$colors", "$$ROOT"]}}},
{"$project": {"colors": 0}}])
I have below unstructured dictionary list which contains values of other keys in a list .
I am not sure if the question i ask is strange. this is the actual dictionary payload that we receive from source which not aligned with respective entry
[
{
"dsply_nm": [
"test test",
"test test",
"",
""
],
"start_dt": [
"2021-04-21T00:01:00-04:00",
"2021-04-21T00:01:00-04:00",
"2021-04-21T00:01:00-04:00",
"2021-04-21T00:01:00-04:00"
],
"exp_dt": [
"2022-04-21T00:01:00-04:00",
"2022-04-21T00:01:00-04:00",
"2022-04-21T00:01:00-04:00",
"2022-04-21T00:01:00-04:00"
],
"hrs_pwr": [
"14",
"12",
"13",
"15"
],
"make_nm": "test",
"model_nm": "test",
"my_yr": "1980"
}
]
"the length of list cannot not be expected and it could be more than 4 sometimes or less in some keys"
#Expected:
i need to check if the above dictionary are in proper structure or not and based on that it should return the proper dictionary list associate with each item
for eg:
def get_dict_list(items):
if type(items == not structure)
result = get_associated_dict_items_mapped
return result
else:
return items
#Final result
expected_dict_list=
[{"dsply_nm":"test test","start_dt":"2021-04-21T00:01:00-04:00","exp_dt":"2022-04-21T00:01:00-04:00","hrs_pwr":"14"},
{"dsply_nm":"test test","start_dt":"2021-04-21T00:01:00-04:00","exp_dt":"2022-04-21T00:01:00-04:00","hrs_pwr":"12","make_nm": "test",model_nm": "test","my_yr": "1980"},
{"dsply_nm":"","start_dt":"2021-04-21T00:01:00-04:00","exp_dt":"2022-04-21T00:01:00-04:00","hrs_pwr":"13"},
{"dsply_nm":"","start_dt":"2021-04-21T00:01:00-04:00","exp_dt":"2022-04-21T00:01:00-04:00","hrs_pwr":"15"}
]
in above dictionary payload, below part is associated with the second dictionary items and have to map respectively
"make_nm": "test",
"model_nm": "test",
"my_yr": "1980"
}
Can anyone help on this?
Thanks
Since customer details is a list
dict(zip(customer_details[0], list(customer_details.values[0]())))
this yields:
{'insured_details': ['asset', 'asset', 'asset'],
'id': ['213', '214', '233'],
'dept': ['account', 'sales', 'market'],
'salary': ['12', '13', '14']}
I think a couple of list comprehensions will get you going. If you would like me to unwind them into more traditional for loops, just let me know.
import json
def get_dict_list(item):
first_value = list(item.values())[0]
if not isinstance(first_value, list):
return [item]
return [{key: item[key][i] for key in item.keys()} for i in range(len(first_value))]
cutomer_details = [
{
"insured_details": "asset",
"id": "xxx",
"dept": "account",
"salary": "12"
},
{
"insured_details": ["asset", "asset", "asset"],
"id":["213","214","233"],
"dept":["account","sales","market"],
"salary":["12","13","14"]
}
]
cutomer_details_cleaned = []
for detail in cutomer_details:
cutomer_details_cleaned.extend(get_dict_list(detail))
print(json.dumps(cutomer_details_cleaned, indent=4))
That should give you:
[
{
"insured_details": "asset",
"id": "xxx",
"dept": "account",
"salary": "12"
},
{
"insured_details": "asset",
"id": "213",
"dept": "account",
"salary": "12"
},
{
"insured_details": "asset",
"id": "214",
"dept": "sales",
"salary": "13"
},
{
"insured_details": "asset",
"id": "233",
"dept": "market",
"salary": "14"
}
]
How do I create a wordcloud with Altair?
Vega and vega-lite provide wordcloud functionality which I have used succesfully in the past.
Therefore it should be possible to access it from Altair if I understand correctly and
I would prefer to prefer to express the visualizations in Python rather than embedded JSON.
All the examples for Altair I have seen involve standard chart types like
scatter plots and bar graphs.
I have not seen any involving wordclouds, networks, treemaps, etc.
More specifically how would I express or at least approximate the following Vega visualization in Altair?
def wc(pages, width=2**10.5, height=2**9.5):
return {
"$schema": "https://vega.github.io/schema/vega/v3.json",
"name": "wordcloud",
"width": width,
"height": height,
"padding": 0,
"data" : [
{
'name' : 'table',
'values' : [{'text': pg.title, 'definition': pg.defn, 'count': pg.count} for pg in pages)]
}
],
"scales": [
{
"name": "color",
"type": "ordinal",
"range": ["#d5a928", "#652c90", "#939597"]
}
],
"marks": [
{
"type": "text",
"from": {"data": "table"},
"encode": {
"enter": {
"text": {"field": "text"},
"align": {"value": "center"},
"baseline": {"value": "alphabetic"},
"fill": {"scale": "color", "field": "text"},
"tooltip": {"field": "definition", "type": "nominal", 'fontSize': 32}
},
"update": {
"fillOpacity": {"value": 1}
},
},
"transform": [
{
"type": "wordcloud",
"size": [width, height],
"text": {"field": "text"},
#"rotate": {"field": "datum.angle"},
"font": "Helvetica Neue, Arial",
"fontSize": {"field": "datum.count"},
#"fontWeight": {"field": "datum.weight"},
"fontSizeRange": [2**4, 2**6],
"padding": 2**4
}
]
}
],
}
Vega(wc(pages))
Altair's API is built on the Vega-Lite grammar, which includes only a subset of the plot types available in Vega. Word clouds cannot be created in Vega-Lite, so they cannot be created in Altair.
With mad respect to #jakevdp, you can construct a word cloud (or something word cloud-like) in altair by recognizing that the elements of a word cloud chart involve:
a dataset of words and their respective quantities
text_marks encoded with each word, and optionally size and or color based on quantity
"randomly" distributing the text_marks in 2d space.
One simple option to distribute marks is to add an additional 'x' and 'y' column to data, each element being a random sample from the range of your chosen x and y domain:
import random
def shuffled_range(n): return random.sample(range(n), k=n)
n = len(words_and_counts) # words_and_counts: a pandas data frame
x = shuffled_range(n)
y = shuffled_range(n)
data = words_and_counts.assign(x=x, y=y)
This isn't perfect as it doesn't explicitly prevent word overlap, but you can play with n and do a few runs of random number generation until you find a layout that's pleasing.
Having thus prepared your data you may specify the word cloud elements like so:
base = alt.Chart(data).encode(
x=alt.X('x:O', axis=None),
y=alt.Y('y:O', axis=None)
).configure_view(strokeWidth=0) # remove border
word_cloud = base.mark_text(baseline='middle').encode(
text='word:N',
color=alt.Color('count:Q', scale=alt.Scale(scheme='goldred')),
size=alt.Size('count:Q', legend=None)
)
Here's the result applied to the same dataset used in the Vega docs:
I have an object stored in arangodb which has additional inner objects, my current use case requires that I update just one of the elements.
Store Object
{
"status": "Active",
"physicalCode": "99999",
"postalCode": "999999",
"tradingCurrency": "USD",
"taxRate": "14",
"priceVatInclusive": "No",
"type": "eCommerce",
"name": "John and Sons inc",
"description": "John and Sons inc",
"createdDate": "2015-05-25T11:04:14+0200",
"modifiedDate": "2015-05-25T11:04:14+0200",
"physicalAddress": "Corner moon and space 9 station",
"postalAddress": "PO Box 44757553",
"physicalCountry": "Mars Sector 9",
"postalCountry": "Mars Sector 9",
"createdBy": "john.doe",
"modifiedBy": "john.doe",
"users": [
{
"id": "577458630580",
"username": "john.doe"
}
],
"products": [
{
"sellingPrice": "95.00",
"inStock": "10",
"name": "School Shirt Green",
"code": "SKITO2939999995",
"warehouseId": "723468998682"
},
{
"sellingPrice": "95.00",
"inStock": "5",
"name": "School Shirt Red",
"code": "SKITO245454949495",
"warehouseId": "723468998682"
},
{
"sellingPrice": "95.00",
"inStock": "10",
"discount": "5%",
"name": "School Shirt Blue",
"code": "SKITO293949495",
"warehouseId": "723468998682"
}
]
}
I want to change just one of the products stock value
{
"sellingPrice": "95.00",
"inStock": "10",
"discount": "5%",
"name": "School Shirt Blue",
"code": "SKITO293949495",
"warehouseId": "723468998682"
}
Like update store product stock less 1 where store id = x, something to this effect
FOR store IN stores
FILTER store._key == "837108415472"
FOR product IN store.products
FILTER product.code == "SKITO293949495"
UPDATE product WITH { inStock: (product.inStock - 1) } IN store.products
Apart from the above possibly it makes sense to store product as a separate document in collection store_products. I believe in NOSQL that is the best approach to reduce document size.
Found answer
here arangodb-aql-update-single-object-in-embedded-array and there
arangodb-aql-update-for-internal-field-of-object
I however believe it is best to maintain separate documents and rather use joins when retrieving. Updates easily