I'm trying to draw multiple series bar chart using dimple.js; My requirement is quite simple that all series should have individual bars (not stacked); scales for two series not same, One is currency value, other is count.
var v = {
[supplier: 'x', invoices: 10, invValue: 1000],
[supplier: 'y', invoices: 5, invValue: 500],
[supplier: 'z', invoices: 20, invValue: 2000],
}
I've already googled and also traversed stackoverflow where expets suggest to do data hack like this
var v = {
[supplier: 'x', kind: 'invoices', value: 10],
[supplier: 'x', kind: 'invValue', value: 1000],
[supplier: 'y', kind: 'invoices', value: 5],
[supplier: 'y', kind: 'invValue', value: 500],
[supplier: 'z', kind: 'invoices', value: 20],
[supplier: 'z', kind: 'invValue', value: 2000],
}
as the scale changes I don't go with this method. what'll be the possible alternate solutions.
And at last I understand that there's no way to implement chart with dimple.js, but as a alternative, it's easy to go with multiple line charts, also possible to do draw first series as dimple.bar, other series dimple.line chart
Related
I need to fetch key value pairs from the second object in array. Also, need to create new columns with the fetched data. I am only interested in the second object, some arrays have 3 objects, some have 4 etc. The data looks like this:
[{'adUnitCode': ca-pub, 'id': 35, 'name': ca-pub}, {'adUnitCode': hmies, 'id': 49, 'name': HMIES}, {'adUnitCode': moda, 'id': 50, 'name': moda}, {'adUnitCode': nova, 'id': 55, 'name': nova}, {'adUnitCode': listicle, 'id': 11, 'name': listicle}]
[{'adUnitCode': ca-pub, 'id': 35, 'name': ca-pub-73}, {'adUnitCode': hmiuk-jam, 'id': 23, 'name': HM}, {'adUnitCode': recipes, 'id': 26, 'name': recipes}]
[{'adUnitCode': ca-pub, 'id': 35, 'name': ca-pub-733450927}, {'adUnitCode': digital, 'id': 48, 'name': Digital}, {'adUnitCode': movies, 'id': 50, 'name': movies}, {'adUnitCode': cannes-film-festival, 'id': 57, 'name': cannes-film-festival}, {'adUnitCode': article, 'id': 57, 'name': article}]
The desired output:
adUnitCode id name
hmies 49 HMIES
hmiuk-jam 23 HM
digital 48 Digital
Below is for BigQuery Standard SQL
#standardSQL
select
json_extract_scalar(second_object, "$.adUnitCode") as adUnitCode,
json_extract_scalar(second_object, "$.id") as id,
json_extract_scalar(second_object, "$.name") as name
from `project.dataset.table`, unnest(
[json_extract_array(regexp_replace(mapping, r"(: )([\w-]+)(,|})", "\\1'\\2'\\3"))[safe_offset(1)]]
) as second_object
if applied to sample data from your question - output is
as you can see, the "trick" here is to use proper regexp in regexp_replace function. I've included now any alphabetical chars and - . you can include more as you see needed
As an alternative yo can try regexp_replace(mapping, r"(: )([^,}]+)", "\\1'\\2'") as in below example - so you will cover potentially more cases without changes in code
#standardSQL
select
json_extract_scalar(second_object, "$.adUnitCode") as adUnitCode,
json_extract_scalar(second_object, "$.id") as id,
json_extract_scalar(second_object, "$.name") as name
from `project.dataset.table`, unnest(
[json_extract_array(regexp_replace(mapping, r"(: )([^,}]+)", "\\1'\\2'"))[safe_offset(1)]]
) as second_object
I have a list:
l = [{'level': '1', 'rows': 2}, {'level': '2', 'rows': 3}]
I can conert to DataFrame, but how do I convert back?
frame = pd.DataFrame(l)
We have to_dict
frame.to_dict('r')
Out[67]: [{'level': '1', 'rows': 2}, {'level': '2', 'rows': 3}]
I have the following dataframe:
df = pd.DataFrame([{'name': 'a', 'label': 'false', 'score': 10},
{'name': 'a', 'label': 'true', 'score': 8},
{'name': 'c', 'label': 'false', 'score': 10},
{'name': 'c', 'label': 'true', 'score': 4},
{'name': 'd', 'label': 'false', 'score': 10},
{'name': 'd', 'label': 'true', 'score': 6},
])
I want to return names that have the "false" label score value higher than the score value of the "true" label with at least the double. In my example, it should return only the "c" name.
First you can pivot the data, and look at the ratio, filter what you want:
new_df = df.pivot(index='name',columns='label', values='score')
new_df[new_df['false'].div(new_df['true']).gt(2)]
output:
label false true
name
c 10 4
If you only want the label, you can do:
new_df.index[new_df['false'].div(new_df['true']).gt(2)].values
which gives
array(['c'], dtype=object)
Update: Since your data is result of orig_df.groupby().count(), you could instead do:
orig_df['label'].eq('true').groupby('name').mean()
and look at the rows with values <= 1/3.
I have a multi-index pandas series as below. I want to add a new entry (new_series) to multi_df, calling it multi_df_appended. However I don't understand the change in behaviour between multi_df and multi_df_appended when I try to access a non-existing multi-index.
Below is the code that reproduces the problem. I want the penultimate line of code: multi_df_appended.loc['five', 'black', 'hard', 'square' ] to return an empty Series like it does with multi_df but instead I get the error given. What am I doing wrong here?
df = pd.DataFrame({'id' : range(1,9),
'code' : ['one', 'one', 'two', 'three',
'two', 'three', 'one', 'two'],
'colour': ['black', 'white','white','white',
'black', 'black', 'white', 'white'],
'texture': ['soft', 'soft', 'hard','soft','hard',
'hard','hard','hard'],
'shape': ['round', 'triangular', 'triangular','triangular','square',
'triangular','round','triangular']
}, columns= ['id','code','colour', 'texture', 'shape'])
multi_df = df.set_index(['code','colour','texture','shape']).sort_index()['id']
# try to access a non-existing multi-index combination:
multi_df.loc['five', 'black', 'hard', 'square' ]
Series([], dtype: int64) # returns an empty Series as desired/expected.
# append multi_df with a new row
new_series = pd.Series([9], index = [('four', 'black', 'hard', 'round')] )
multi_df_appended = multi_df.append(new_series)
# now try again to access a non-existing multi-index combination:
multi_df_appended.loc['five', 'black', 'hard', 'square' ]
error: 'MultiIndex lexsort depth 0, key was length 4' # now instead of the empty Series, I get an error!?
As #Jeff answered, if I do .sortlevel(0) and then run .loc() for an unknown index, it does not give the "lexsort depth" error:
multi_df_appended_sorted = multi_df.append(new_series).sortlevel(0)
multi_df_appended_sorted.loc['five', 'black', 'hard', 'square' ]
Series([], dtype: int64)
I there a way where by I can define the colours of bubbles in a motion chart provided by Google visualization API ? I do not want to use the default colour scheme.
Thank you in advance.
I've not found an inbuilt way to do this. However, what you can do is assign each bubble a "colour" variable. Then you can set the colour of the bubbles to this variable. I have found that for 3 bubbles, setting one to 1, another to 1.5 and the third to 3 projects reasonable well (on the default colour scheme, yellow projects very poorly). This approach gives you limited control over the colour scheme.
It's 2017 and I have yet to find a good update for this. So here is the solution I came up with. HTH.
#views.py
# Bubble Chart: ID, X, Y Color, Size
data.append(['ID', 'X', 'Y', 'Category', 'Z'])
data.append(['', 0, 0, 'Cat 1', 0]) #<-- the order of
data.append(['', 0, 0, 'Cat 2', 0]) #<-- these fakeout items
data.append(['', 0, 0, 'Cat 3', 0]) #<-- is important
data.append(['', 0, 0, 'Cat 4', 0]) #<-- Blue, Red, Orange, Green - in that order
... for r in source:
data.append(r.a, r.b, r.c, r.d, r.e)
return render(
request,
'Template.html',
{
'title':'',
'year':datetime.now().year,
'org': org,
'data': json.dumps(data),
}
#in the scripts block of template.html
<script type="text/javascript" src="https://www.gstatic.com/charts/loader.js"></script>
<script type="text/javascript">
google.charts.load('current', {'packages':['corechart']});
google.charts.setOnLoadCallback(drawChart);
function drawChart() {
var data = google.visualization.arrayToDataTable({{data|safe}});
var options = {
title: 'Bubble By Category Strategy',
hAxis: { title: 'X', ticks: [{v: 0, f:''}, {v: 1, f:'L'}, {v: 2, f:'M'}, {v: 3, f:'H'}, {v: 4, f:''}] },
vAxis: { title: 'Y', ticks: [{v: 0, f:''}, {v: 1, f:'L'}, {v: 2, f:'M'}, {v: 3, f:'H'}, {v: 4, f:''}] },
bubble: {
textStyle: {
fontSize: 11,
fontName: 'Lato',
}
}
};
var chart = new google.visualization.BubbleChart(document.getElementById('riskChart'));
chart.draw(data, options);
}
</script>